diff --git a/R/centrality.R b/R/centrality.R
index 54f9c4bbb00..58112f7bdcb 100644
--- a/R/centrality.R
+++ b/R/centrality.R
@@ -184,6 +184,8 @@ graph.diversity <- function(graph, weights = NULL, vids = V(graph)) {
 #' `evcent()` was renamed to [eigen_centrality()] to create a more
 #' consistent API.
 #' @inheritParams eigen_centrality
+#' @param directed Logical scalar, whether to consider direction of the edges
+#'   in directed graphs. It is ignored for undirected graphs.
 #' @keywords internal
 #' @export
 evcent <- function(
@@ -1312,7 +1314,7 @@ eigen_defaults <- function() {
 #' computation, see [arpack()] for more about ARPACK in igraph.
 #'
 #' @param graph Graph to be analyzed.
-#' @param directed Logical scalar, whether to consider direction of the edges
+#' @param directed `r lifecycle::badge("deprecated")` Logical scalar, whether to consider direction of the edges
 #'   in directed graphs. It is ignored for undirected graphs.
 #' @param scale `r lifecycle::badge("deprecated")` Normalization will always take
 #' place.
@@ -1329,6 +1331,17 @@ eigen_defaults <- function() {
 #'   weights spread the centrality better.
 #' @param options A named list, to override some ARPACK options. See
 #'   [arpack()] for details.
+#' @param mode How to consider edge directions in directed graphs.
+#' It is ignored for undirected graphs.
+#' Possible values:
+#'   - `"out"` the left eigenvector of the adjacency matrix is calculated,
+#' i.e. the centrality of a vertex is proportional to the sum of centralities
+#' of vertices pointing to it. This is the standard eigenvector centrality.
+#'   - `"in"` the right eigenvector of the adjacency matrix is calculated,
+#' i.e. the centrality of a vertex is proportional to the sum of centralities
+#' of vertices it points to.
+#'   - `"all"` edge directions are ignored,
+#' and the unweighted eigenvector centrality is calculated.
 #' @return A named list with components:
 #'   \describe{
 #'     \item{vector}{
@@ -1358,10 +1371,11 @@ eigen_defaults <- function() {
 #' @cdocs igraph_eigenvector_centrality
 eigen_centrality <- function(
   graph,
-  directed = FALSE,
+  directed = deprecated(),
   scale = deprecated(),
   weights = NULL,
-  options = arpack_defaults()
+  options = arpack_defaults(),
+  mode = c("out", "in", "all")
 ) {
   if (is.function(options)) {
     lifecycle::deprecate_soft(
@@ -1390,10 +1404,33 @@ eigen_centrality <- function(
     }
   }
 
+  mode <- igraph.match.arg(mode)
+
+  if (lifecycle::is_present(directed)) {
+    if (directed) {
+      lifecycle::deprecate_soft(
+        "2.2.0",
+        "eigen_centrality(directed)",
+        details = "Use the mode argument."
+      )
+      if (!lifecycle::is_present(mode)) {
+        mode <- "out"
+      }
+    } else {
+      lifecycle::deprecate_soft(
+        "2.2.0",
+        "eigen_centrality(directed)",
+        details = "Use the mode argument."
+      )
+      if (!lifecycle::is_present(mode)) {
+        mode <- "all"
+      }
+    }
+  }
+
   eigenvector_centrality_impl(
     graph = graph,
-    directed = directed,
-    scale = TRUE,
+    mode = mode,
     weights = weights,
     options = options
   )
@@ -1517,9 +1554,7 @@ diversity <- function(graph, weights = NULL, vids = V(graph)) {
 #' scores are the same as authority scores.
 #'
 #' @param graph The input graph.
-#' @param scale Logical scalar, whether to scale the result to have a maximum
-#'   score of one. If no scaling is used then the result vector has unit length
-#'   in the Euclidean norm.
+#' @param scale  `r lifecycle::badge("deprecated")` Ignored, always scaled.
 #' @param weights Optional positive weight vector for calculating weighted
 #'   scores. If the graph has a `weight` edge attribute, then this is used
 #'   by default. Pass `NA` to ignore the weight attribute. This function
@@ -1565,15 +1600,22 @@ diversity <- function(graph, weights = NULL, vids = V(graph)) {
 hits_scores <- function(
   graph,
   ...,
-  scale = TRUE,
+  scale = deprecated(),
   weights = NULL,
   options = arpack_defaults()
 ) {
   rlang::check_dots_empty()
 
+  if (lifecycle::is_present(scale)) {
+    lifecycle::deprecate_soft(
+      "2.1.5",
+      "hits_scores(scale = )",
+      details = "The function always behaves as if `scale = TRUE`.
+      The argument will be removed in the future."
+    )
+  }
   hub_and_authority_scores_impl(
     graph = graph,
-    scale = scale,
     weights = weights,
     options = options
   )
@@ -1609,7 +1651,8 @@ authority_score <- function(
     weights = weights,
     options = options
   )
-  scores$hub <- NULL
+  scores[["hub_vector"]] <- NULL
+
   rlang::set_names(scores, c("vector", "value", "options"))
 }
 
@@ -1654,7 +1697,7 @@ hub_score <- function(
     weights = weights,
     options = options
   )
-  scores$authority <- NULL
+  scores[["authority_vector"]] <- NULL
   rlang::set_names(scores, c("vector", "value", "options"))
 }
 
diff --git a/R/centralization.R b/R/centralization.R
index 6fa6678fdc5..e5e9d44aff2 100644
--- a/R/centralization.R
+++ b/R/centralization.R
@@ -56,6 +56,8 @@ centralization.evcent.tmax <- function(
 #' `centralization.evcent()` was renamed to [centr_eigen()] to create a more
 #' consistent API.
 #' @inheritParams centr_eigen
+#' @param directed logical scalar, whether to use directed shortest paths for
+#'   calculating eigenvector centrality.
 #' @keywords internal
 #' @export
 centralization.evcent <- function(
@@ -306,7 +308,7 @@ NULL
 #'
 #' # Calculate centralization from pre-computed scores
 #' deg <- degree(g)
-#' tmax <- centr_degree_tmax(g, loops = FALSE)
+#' tmax <- centr_degree_tmax(g, loops = "none")
 #' centralize(deg, tmax)
 #'
 #' # The most centralized graph according to eigenvector centrality
@@ -385,8 +387,11 @@ centr_degree <- function(
 #' @param nodes The number of vertices. This is ignored if the graph is given.
 #' @param mode This is the same as the `mode` argument of `degree()`. Ignored
 #'   if `graph` is given and the graph is undirected.
-#' @param loops Logical scalar, whether to consider loops edges when
-#'   calculating the degree.
+#' @param loops Character string,
+#'   `"none"` (the default) ignores loop edges;
+#'   `"once"` counts each loop edge only once;
+#'   `"twice"` counts each loop edge twice in undirected graphs.
+#' and once in directed graphs.
 #' @return Real scalar, the theoretical maximum (unnormalized) graph degree
 #'   centrality score for graphs with given order and other parameters.
 #'
@@ -397,8 +402,8 @@ centr_degree <- function(
 #' @examples
 #' # A BA graph is quite centralized
 #' g <- sample_pa(1000, m = 4)
-#' centr_degree(g, normalized = FALSE)$centralization %>%
-#'   `/`(centr_degree_tmax(g, loops = FALSE))
+#' centr_degree(g, normalized = FALSE)$centralization /
+#'   centr_degree_tmax(g, loops = "twice")
 #' centr_degree(g, normalized = TRUE)$centralization
 centr_degree_tmax <- function(
   graph = NULL,
@@ -412,7 +417,7 @@ centr_degree_tmax <- function(
       what = "centr_degree_tmax(loops = 'must be explicit')",
       details = "The default value (currently `FALSE`) will be dropped in the next release. Add an explicit value for the `loops` argument."
     )
-    loops <- FALSE
+    loops <- "none"
   }
 
   # Argument checks
@@ -420,8 +425,6 @@ centr_degree_tmax <- function(
 
   nodes <- as.numeric(nodes)
 
-  loops <- as.logical(loops)
-
   # Function call
   res <- centralization_degree_tmax_impl(
     graph,
@@ -611,12 +614,22 @@ centr_clo_tmax <- function(
 #' See [centralize()] for a summary of graph centralization.
 #'
 #' @param graph The input graph.
-#' @param directed logical scalar, whether to use directed shortest paths for
-#'   calculating eigenvector centrality.
+#' @param directed `r lifecycle::badge("deprecated")` Use `mode` instead.
 #' @param scale `r lifecycle::badge("deprecated")` Ignored. Computing
 #' eigenvector centralization requires normalized eigenvector centrality scores.
 #' @param options This is passed to [eigen_centrality()], the options
 #'   for the ARPACK eigensolver.
+#' @param mode How to consider edge directions in directed graphs.
+#' It is ignored for undirected graphs.
+#' Possible values:
+#'   - `"out"` the left eigenvector of the adjacency matrix is calculated,
+#' i.e. the centrality of a vertex is proportional to the sum of centralities
+#' of vertices pointing to it. This is the standard eigenvector centrality.
+#'   - `"in"` the right eigenvector of the adjacency matrix is calculated,
+#' i.e. the centrality of a vertex is proportional to the sum of centralities
+#' of vertices it points to.
+#'   - `"all"` edge directions are ignored,
+#' and the unweighted eigenvector centrality is calculated.
 #' @param normalized Logical scalar. Whether to normalize the graph level
 #'   centrality score by dividing by the theoretical maximum.
 #' @return A named list with the following components:
@@ -659,10 +672,11 @@ centr_clo_tmax <- function(
 #' @cdocs igraph_centralization_eigenvector_centrality
 centr_eigen <- function(
   graph,
-  directed = FALSE,
+  directed = deprecated(),
   scale = deprecated(),
   options = arpack_defaults(),
-  normalized = TRUE
+  normalized = TRUE,
+  mode = c("out", "in", "all")
 ) {
   if (lifecycle::is_present(scale)) {
     lifecycle::deprecate_soft(
@@ -673,12 +687,35 @@ centr_eigen <- function(
     )
   }
 
+  mode <- igraph.match.arg(mode)
+
+  if (lifecycle::is_present(directed)) {
+    if (directed) {
+      lifecycle::deprecate_soft(
+        "2.2.0",
+        "eigen_centrality(directed)",
+        details = "Use the mode argument."
+      )
+      if (!lifecycle::is_present(mode)) {
+        mode <- "out"
+      }
+    } else {
+      lifecycle::deprecate_soft(
+        "2.2.0",
+        "eigen_centrality(directed)",
+        details = "Use the mode argument."
+      )
+      if (!lifecycle::is_present(mode)) {
+        mode <- "all"
+      }
+    }
+  }
+
   centralization_eigenvector_centrality_impl(
     graph = graph,
-    directed = directed,
     options = options,
     normalized = normalized,
-    scale = TRUE
+    mode = mode
   )
 }
 
@@ -693,7 +730,9 @@ centr_eigen <- function(
 #' @param directed logical scalar, whether to consider edge directions
 #'   during the calculation. Ignored in undirected graphs.
 #' @param scale `r lifecycle::badge("deprecated")` Ignored. Computing
-#' eigenvector centralization requires normalized eigenvector centrality scores.
+#'   eigenvector centralization requires normalized eigenvector centrality scores.
+#' @param mode This is the same as the `mode` argument of
+#'   `degree()`.
 #' @return Real scalar, the theoretical maximum (unnormalized) graph
 #'   eigenvector centrality score for graphs with given vertex count and
 #'   other parameters.
@@ -712,8 +751,9 @@ centr_eigen <- function(
 centr_eigen_tmax <- function(
   graph = NULL,
   nodes = 0,
-  directed = FALSE,
-  scale = deprecated()
+  directed = deprecated(),
+  scale = deprecated(),
+  mode = c("out", "in", "all")
 ) {
   if (lifecycle::is_present(scale)) {
     lifecycle::deprecate_soft(
@@ -723,11 +763,33 @@ centr_eigen_tmax <- function(
       The argument will be removed in the future."
     )
   }
+  mode <- igraph.match.arg(mode)
+
+  if (lifecycle::is_present(directed)) {
+    if (directed) {
+      lifecycle::deprecate_soft(
+        "2.2.0",
+        "eigen_centrality(directed)",
+        details = "Use the mode argument."
+      )
+      if (!lifecycle::is_present(mode)) {
+        mode <- "out"
+      }
+    } else {
+      lifecycle::deprecate_soft(
+        "2.2.0",
+        "eigen_centrality(directed)",
+        details = "Use the mode argument."
+      )
+      if (!lifecycle::is_present(mode)) {
+        mode <- "all"
+      }
+    }
+  }
 
   centralization_eigenvector_centrality_tmax_impl(
     graph = graph,
     nodes = nodes,
-    directed = directed,
-    scale = TRUE
+    mode = mode
   )
 }
diff --git a/R/community.R b/R/community.R
index af6497a92c6..ba92e3afe7a 100644
--- a/R/community.R
+++ b/R/community.R
@@ -2345,6 +2345,10 @@ cluster_leading_eigen <- function(
 #' @param fixed Logical vector denoting which labels are fixed. Of course this
 #'   makes sense only if you provided an initial state, otherwise this element
 #'   will be ignored. Also note that vertices without labels cannot be fixed.
+#' @param lpa_variant Which variant of the label propagation algorithm to run.
+#'   - `"dominance"` (default) check for dominance of all nodes after each iteration.
+#'   - `"retention"` keep current label if among dominant labels, only check if labels changed.
+#'   - `"fast"` sample from dominant labels, only check neighbors.
 #' @return `cluster_label_prop()` returns a
 #'   [communities()] object, please see the [communities()]
 #'   manual page for details.
@@ -2373,7 +2377,8 @@ cluster_label_prop <- function(
   ...,
   mode = c("out", "in", "all"),
   initial = NULL,
-  fixed = NULL
+  fixed = NULL,
+  lpa_variant = c("dominance", "retention", "fast")
 ) {
   if (...length() > 0) {
     lifecycle::deprecate_soft(
@@ -2395,7 +2400,7 @@ cluster_label_prop <- function(
     return(inject(cluster_label_prop0(!!!dots)))
   }
 
-  cluster_label_prop0(graph, weights, mode, initial, fixed)
+  cluster_label_prop0(graph, weights, mode, initial, fixed, lpa_variant)
 }
 
 cluster_label_prop0 <- function(
@@ -2403,13 +2408,15 @@ cluster_label_prop0 <- function(
   weights = NULL,
   mode = c("out", "in", "all"),
   initial = NULL,
-  fixed = NULL
+  fixed = NULL,
+  lpa_variant = c("dominance", "retention", "fast")
 ) {
   # Argument checks
   ensure_igraph(graph)
 
   # Necessary because evaluated later
   mode <- igraph.match.arg(mode)
+  lpa_variant <- igraph.match.arg(lpa_variant)
 
   # Function call
   membership <- community_label_propagation_impl(
@@ -2417,8 +2424,10 @@ cluster_label_prop0 <- function(
     mode = mode,
     weights = weights,
     initial = initial,
-    fixed = fixed
+    fixed = fixed,
+    lpa.variant = lpa_variant
   )
+
   res <- list()
   if (igraph_opt("add.vertex.names") && is_named(graph)) {
     res$names <- V(graph)$name
diff --git a/R/console.R b/R/console.R
index 882e7d3b6b1..47e748b3402 100644
--- a/R/console.R
+++ b/R/console.R
@@ -95,18 +95,26 @@ console <- function() {
 #' @inheritParams .igraph.progress
 #' @dev
 .igraph.status <- function(message) {
-  type <- igraph_opt("verbose")
-  if (is.logical(type) && type) {
-    message(message, appendLF = FALSE)
-  } else {
-    switch(
-      type,
-      "tk" = message(message, appendLF = FALSE),
-      "tkconsole" = .igraph.progress.tkconsole.message(message, start = TRUE),
-      stop("Cannot interpret 'verbose' option, this should not happen")
-    )
-  }
-  0L
+  # Catch all errors
+  tryCatch(
+    {
+      type <- igraph::igraph_opt("verbose")
+      if (is.logical(type) && type) {
+        message(message, appendLF = FALSE)
+      } else {
+        switch(
+          type,
+          "tk" = message(message, appendLF = FALSE),
+          "tkconsole" = .igraph.progress.tkconsole.message(
+            message,
+            start = TRUE
+          ),
+          stop("Cannot interpret 'verbose' option, this should not happen")
+        )
+      }
+    },
+    error = function(e) {}
+  )
 }
 
 #' @importFrom utils txtProgressBar setTxtProgressBar
diff --git a/R/games.R b/R/games.R
index 0d848daabca..862d416bcbc 100644
--- a/R/games.R
+++ b/R/games.R
@@ -938,10 +938,6 @@ sample_pa <- function(
     ))
   }
 
-  if (is.null(out.seq)) {
-    out.seq <- numeric()
-  }
-
   algorithm <- igraph.match.arg(algorithm)
   algorithm1 <- switch(
     algorithm,
@@ -1081,7 +1077,8 @@ sample_gnm <- function(n, m, directed = FALSE, loops = FALSE) {
     as.numeric(n),
     as.numeric(m),
     as.logical(directed),
-    as.logical(loops)
+    as.logical(loops),
+    FALSE
   )
 
   if (igraph_opt("add.params")) {
@@ -3076,7 +3073,7 @@ sample_fitness_pl <- function(
   multiple = FALSE,
   finite.size.correction = TRUE
 ) {
-  static_power_law_game_impl(
+  res <- static_power_law_game_impl(
     no.of.nodes = no.of.nodes,
     no.of.edges = no.of.edges,
     exponent.out = exponent.out,
@@ -3085,6 +3082,13 @@ sample_fitness_pl <- function(
     multiple = multiple,
     finite.size.correction = finite.size.correction
   )
+
+  if (igraph_opt("add.params")) {
+    res$loops <- loops
+    res$multiple <- multiple
+  }
+
+  res
 }
 
 
diff --git a/R/interface.R b/R/interface.R
index 44e0efc67c0..5ae535c82c5 100644
--- a/R/interface.R
+++ b/R/interface.R
@@ -366,6 +366,13 @@ neighbors <- function(graph, v, mode = c("out", "in", "all", "total")) {
 #' @param mode Whether to query outgoing (\sQuote{out}), incoming
 #'   (\sQuote{in}) edges, or both types (\sQuote{all}). This is
 #'   ignored for undirected graphs.
+#' @param loops Specifies how to treat loop edges.
+#' `"none"` removes loop edges from the result.
+#' `"once"` makes each loop edge appear only once in the result.
+#' `"twice"` makes loop edges appear twice in the result
+#' if the graph is undirected or `mode` is set to `"all"`
+#' (and once otherwise as returning them twice
+#' does not make sense for directed graphs).
 #' @return An edge sequence containing the incident edges of
 #'   the input vertex.
 #'
@@ -376,26 +383,30 @@ neighbors <- function(graph, v, mode = c("out", "in", "all", "total")) {
 #' g <- make_graph("Zachary")
 #' incident(g, 1)
 #' incident(g, 34)
-incident <- function(graph, v, mode = c("all", "out", "in", "total")) {
+incident <- function(
+  graph,
+  v,
+  mode = c("all", "out", "in", "total"),
+  loops = c("twice", "none", "once")
+) {
   ensure_igraph(graph)
   if (is_directed(graph)) {
     mode <- igraph.match.arg(mode)
-    mode <- switch(mode, "out" = 1, "in" = 2, "all" = 3, "total" = 3)
   } else {
-    mode <- 1
+    mode <- "out"
   }
+  loops <- igraph.match.arg(loops)
   v <- as_igraph_vs(graph, v)
   if (length(v) == 0) {
     stop("No vertex was specified")
   }
-  on.exit(.Call(R_igraph_finalizer))
-  res <- .Call(R_igraph_incident, graph, v - 1, as.numeric(mode)) + 1L
 
-  if (igraph_opt("return.vs.es")) {
-    res <- create_es(graph, res)
-  }
-
-  res
+  incident_impl(
+    graph,
+    vid = v,
+    mode = mode,
+    loops = loops
+  )
 }
 
 #' Check whether a graph is directed
diff --git a/R/make.R b/R/make.R
index 7547b44e593..3d607cee373 100644
--- a/R/make.R
+++ b/R/make.R
@@ -384,7 +384,7 @@ graph.lcf <- function(n, shifts, repeats = 1) {
   # nocov start
   lifecycle::deprecate_soft("2.1.0", "graph.lcf()", "graph_from_lcf()")
   # Use the _impl function
-  lcf_vector_impl(n = n, shifts = shifts, repeats = repeats)
+  lcf_impl(n = n, shifts = shifts, repeats = repeats)
 } # nocov end
 
 #' Create a lattice graph
@@ -2609,7 +2609,7 @@ full_citation_graph <- function(...) {
 #' g2 <- make_graph("Franklin")
 #' isomorphic(g1, g2)
 #' @export
-#' @cdocs igraph_lcf_vector
+#' @cdocs igraph_lcf
 graph_from_lcf <- function(
   shifts,
   ...,
@@ -2637,7 +2637,7 @@ graph_from_lcf <- function(
     )
   }
 
-  lcf_vector_impl(n = n, shifts = shifts, repeats = repeats)
+  lcf_impl(n = n, shifts = shifts, repeats = repeats)
 }
 ## -----------------------------------------------------------------
 
diff --git a/R/minimum.spanning.tree.R b/R/minimum.spanning.tree.R
index 4a47836555d..e5edb8eaf63 100644
--- a/R/minimum.spanning.tree.R
+++ b/R/minimum.spanning.tree.R
@@ -58,7 +58,7 @@ minimum.spanning.tree <- function(
 #'   distances.
 #' @param algorithm The algorithm to use for calculation. `unweighted` can
 #'   be used for unweighted graphs, and `prim` runs Prim's algorithm for
-#'   weighted graphs.  If this is `NULL` then igraph will select the
+#'   weighted graphs.  By default igraph will select the
 #'   algorithm automatically: if the graph has an edge attribute called
 #'   `weight` or the `weights` argument is not `NULL` then Prim's
 #'   algorithm is chosen, otherwise the unweighted algorithm is used.
@@ -79,29 +79,17 @@ minimum.spanning.tree <- function(
 #' g <- sample_gnp(100, 3 / 100)
 #' g_mst <- mst(g)
 #'
-mst <- function(graph, weights = NULL, algorithm = NULL, ...) {
+mst <- function(
+  graph,
+  weights = NULL,
+  algorithm = c("automatic", "unweighted", "prim", "kruskal"),
+  ...
+) {
   ensure_igraph(graph)
-
-  if (is.null(algorithm)) {
-    if (!is.null(weights) || "weight" %in% edge_attr_names(graph)) {
-      algorithm <- "prim"
-    } else {
-      algorithm <- "unweighted"
-    }
-  }
-
-  if (algorithm == "unweighted") {
-    on.exit(.Call(R_igraph_finalizer))
-    .Call(R_igraph_minimum_spanning_tree_unweighted, graph)
-  } else if (algorithm == "prim") {
-    if (is.null(weights) && !"weight" %in% edge_attr_names(graph)) {
-      cli::cli_abort("edges weights must be supplied for Prim's algorithm.")
-    } else if (is.null(weights)) {
-      weights <- E(graph)$weight
-    }
-    on.exit(.Call(R_igraph_finalizer))
-    .Call(R_igraph_minimum_spanning_tree_prim, graph, as.numeric(weights))
-  } else {
-    cli::cli_abort("Invalid {.arg algorithm}.")
-  }
+  algorithm <- igraph.match.arg(algorithm)
+  minimum_spanning_tree_impl(
+    graph,
+    weights = weights,
+    method = algorithm
+  )
 }
diff --git a/R/other.R b/R/other.R
index a28d2cf8c8c..921d11d57b8 100644
--- a/R/other.R
+++ b/R/other.R
@@ -224,5 +224,5 @@ igraph.i.spMatrix <- function(M) {
 #' @export
 #' @cdocs igraph_convex_hull
 convex_hull <- function(data) {
-  convex_hull_2d_impl(data = data)
+  convex_hull_impl(data = data)
 }
diff --git a/R/paths.R b/R/paths.R
index 857bbf8bf04..c7ccd32f42c 100644
--- a/R/paths.R
+++ b/R/paths.R
@@ -127,7 +127,6 @@ all_simple_paths <- function(
       mode = mode
     )
   )
-  res <- get.all.simple.paths.pp(res)
 
   if (igraph_opt("return.vs.es")) {
     res <- lapply(res, unsafe_create_vs, graph = graph, verts = V(graph))
@@ -276,7 +275,7 @@ max_cardinality <- function(graph) {
 #' eccentricity(g)
 #' @family paths
 #' @export
-#' @cdocs igraph_eccentricity_dijkstra
+#' @cdocs igraph_eccentricity
 eccentricity <- function(
   graph,
   vids = V(graph),
@@ -300,7 +299,7 @@ eccentricity <- function(
     }
   }
 
-  eccentricity_dijkstra_impl(graph, vids = vids, weights = weights, mode = mode)
+  eccentricity_impl(graph, vids = vids, weights = weights, mode = mode)
 }
 
 
@@ -331,7 +330,7 @@ eccentricity <- function(
 #' radius(g)
 #' @family paths
 #' @export
-#' @cdocs igraph_radius_dijkstra
+#' @cdocs igraph_radius
 radius <- function(
   graph,
   ...,
@@ -354,7 +353,7 @@ radius <- function(
     }
   }
 
-  radius_dijkstra_impl(graph, weights = weights, mode = mode)
+  radius_impl(graph, weights = weights, mode = mode)
 }
 
 #' Central vertices of a graph
@@ -383,14 +382,14 @@ radius <- function(
 #' graph_center(ring)
 #'
 #' @export
-#' @cdocs igraph_graph_center_dijkstra
+#' @cdocs igraph_graph_center
 graph_center <- function(
   graph,
   ...,
   weights = NULL,
   mode = c("all", "out", "in", "total")
 ) {
-  graph_center_dijkstra_impl(
+  graph_center_impl(
     graph = graph,
     ...,
     weights = weights,
diff --git a/R/pp.R b/R/pp.R
deleted file mode 100644
index d452b97fa12..00000000000
--- a/R/pp.R
+++ /dev/null
@@ -1,24 +0,0 @@
-#   IGraph R package
-#   Copyright (C) 2014  Gabor Csardi <csardi.gabor@gmail.com>
-#   334 Harvard street, Cambridge, MA 02139 USA
-#
-#   This program is free software; you can redistribute it and/or modify
-#   it under the terms of the GNU General Public License as published by
-#   the Free Software Foundation; either version 2 of the License, or
-#   (at your option) any later version.
-#
-#   This program is distributed in the hope that it will be useful,
-#   but WITHOUT ANY WARRANTY; without even the implied warranty of
-#   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-#   GNU General Public License for more details.
-#
-#   You should have received a copy of the GNU General Public License
-#   along with this program; if not, write to the Free Software
-#   Foundation, Inc.,  51 Franklin Street, Fifth Floor, Boston, MA
-#   02110-1301 USA
-#
-###################################################################
-
-get.all.simple.paths.pp <- function(vect) {
-  .Call(R_igraph_get_all_simple_paths_pp, vect)
-}
diff --git a/R/rewire.R b/R/rewire.R
index 44354e904b2..86783aafe04 100644
--- a/R/rewire.R
+++ b/R/rewire.R
@@ -41,7 +41,7 @@
 rewire <- function(graph, with) {
   if (!is(with, "igraph_rewiring_method")) {
     cli::cli_abort(
-      "{.arg with} must be an igraph rewiring method, 
+      "{.arg with} must be an igraph rewiring method,
       not {.obj_type_friendly {with}}."
     )
   }
diff --git a/R/similarity.R b/R/similarity.R
index b86fd2f9c3e..0feaa99ee46 100644
--- a/R/similarity.R
+++ b/R/similarity.R
@@ -26,7 +26,11 @@
 #' 25(3):211-230, 2003.
 #'
 #' @param graph The input graph.
-#' @param vids The vertex ids for which the similarity is calculated.
+#' @param vids lifecycle::badge("deprecated")
+#' @param vids_from The vertex IDs of the first set of vertices of the pairs
+#' for which the calculation will be done.
+#' @param vids_to The vertex IDs of the second set of vertices of the pairs
+#' for which the calculation will be done.
 #' @param mode The type of neighboring vertices to use for the calculation,
 #'   possible values: \sQuote{`out`}, \sQuote{`in`},
 #'   \sQuote{`all`}.
@@ -52,7 +56,7 @@
 #' similarity(g, method = "jaccard")
 similarity <- function(
   graph,
-  vids = V(graph),
+  vids = deprecated(),
   mode = c(
     "all",
     "out",
@@ -64,16 +68,47 @@ similarity <- function(
     "jaccard",
     "dice",
     "invlogweighted"
-  )
+  ),
+  vids_from = V(graph),
+  vids_to = vids_from
 ) {
-  method <- igraph.match.arg(method)
-  if (method == "jaccard") {
-    similarity_jaccard_impl(graph, vids, mode, loops)
-  } else if (method == "dice") {
-    similarity_dice_impl(graph, vids, mode, loops)
-  } else if (method == "invlogweighted") {
-    similarity_inverse_log_weighted_impl(graph, vids, mode)
+  if (lifecycle::is_present(vids)) {
+    lifecycle::deprecate_soft(
+      "similarity(vids =)",
+      I("similarity(vids_from =, vids_to =)"),
+      when = "3.0.0"
+    )
+    if (!lifecycle::is_present(vids_from)) {
+      vids_from <- vids
+      vids_to <- vids_from
+    }
   }
+
+  method <- igraph.match.arg(method)
+
+  switch(
+    method,
+    jaccard = similarity_jaccard_impl(
+      graph,
+      vit.from = vids_from,
+      vit.to = vids_to,
+      mode = mode,
+      loops = loops
+    ),
+    dice = similarity_dice_impl(
+      graph,
+      vit.from = vids_from,
+      vit.to = vids_to,
+      mode = mode,
+      loops = loops
+    ),
+    invlogweighted = similarity_inverse_log_weighted_impl(
+      graph,
+      vit.from = vids_from,
+      vit.to = vids_to,
+      mode = mode
+    )
+  )
 }
 
 #' Similarity measures of two vertices (Jaccard)
@@ -83,6 +118,7 @@ similarity <- function(
 #'
 #' Please use [similarity()] with `method = "jaccard"` instead.
 #' @inheritParams similarity
+#' @param vids The vertex ids for which the similarity is calculated.
 #' @keywords internal
 #' @export
 similarity.jaccard <- function(
@@ -114,6 +150,7 @@ similarity.jaccard <- function(
 #'
 #' Please use [similarity()] with `method = "dice"` instead.
 #' @inheritParams similarity
+#' @param vids The vertex ids for which the similarity is calculated.
 #' @keywords internal
 #' @export
 similarity.dice <- function(
@@ -145,6 +182,7 @@ similarity.dice <- function(
 #'
 #' Please use [similarity()] with `method = "invlogweighted"` instead.
 #' @inheritParams similarity
+#' @param vids The vertex ids for which the similarity is calculated.
 #' @keywords internal
 #' @export
 similarity.invlogweighted <- function(
diff --git a/R/simple.R b/R/simple.R
index 78132bd4dc5..f05142ff5a5 100644
--- a/R/simple.R
+++ b/R/simple.R
@@ -71,6 +71,11 @@ is.simple <- function(graph) {
 #'   `remove.multiple=TRUE`. In this case many edges might be mapped to a
 #'   single one in the new graph, and their attributes are combined. Please see
 #'   [attribute.combination()] for details on this.
+#' @param directed Boolean.Whether to consider the directions of edges.
+#' The default, `TRUE`  means that edge directions will be considered.
+#' `FALSE` means that edge directions will be ignored and a directed graph
+#' with at least one mutual edge pair will be considered non-simple.
+#' Ignored for undirected graphs.
 #' @return a new graph object with the edges deleted.
 #' @author Gabor Csardi \email{csardi.gabor@@gmail.com}
 #' @seealso [which_loop()], [which_multiple()] and
@@ -84,6 +89,11 @@ is.simple <- function(graph) {
 #' is_simple(simplify(g, remove.loops = FALSE))
 #' is_simple(simplify(g, remove.multiple = FALSE))
 #' is_simple(simplify(g))
+#'
+#' # directed argument
+#' g <- graph_from_literal(1 +-+ 2 -+ 3)
+#' is_simple(g)
+#' is_simple(g, directed = FALSE)
 #' @family simple
 #' @family functions for manipulating graph structure
 #' @family isomorphism
diff --git a/R/structural-properties.R b/R/structural-properties.R
index b99ba9e37f5..21f26dd2e48 100644
--- a/R/structural-properties.R
+++ b/R/structural-properties.R
@@ -758,23 +758,13 @@ diameter <- function(
 ) {
   ensure_igraph(graph)
 
-  if (is.null(weights) && "weight" %in% edge_attr_names(graph)) {
-    weights <- E(graph)$weight
-  }
-  if (!is.null(weights) && any(!is.na(weights))) {
-    weights <- as.numeric(weights)
-  } else {
-    weights <- NULL
-  }
-
-  on.exit(.Call(R_igraph_finalizer))
-  .Call(
-    R_igraph_diameter,
+  res <- diameter_impl(
     graph,
-    as.logical(directed),
-    as.logical(unconnected),
-    weights
+    weights = weights,
+    directed = directed,
+    unconnected = unconnected
   )
+  res$res
 }
 
 #' @rdname diameter
@@ -851,9 +841,29 @@ farthest_vertices <- function(
 
 #' @export
 #' @rdname distances
-#' @cdocs igraph_average_path_length_dijkstra
-mean_distance <- average_path_length_dijkstra_impl
+#' @cdocs igraph_average_path_length
+mean_distance <- function(
+  graph,
+  weights = NULL,
+  directed = TRUE,
+  unconnected = TRUE,
+  details = FALSE
+) {
+  res <- average_path_length_impl(
+    graph,
+    weights = weights,
+    directed = directed,
+    unconn = unconnected,
+    details = details
+  )
 
+  if (details) {
+    res$unconnected <- res$unconn_pair
+    res$unconn_pair <- NULL
+  }
+
+  res
+}
 
 #' Degree and degree distribution of the vertices
 #'
@@ -866,7 +876,11 @@ mean_distance <- average_path_length_dijkstra_impl
 #' @param mode Character string, \dQuote{out} for out-degree, \dQuote{in} for
 #'   in-degree or \dQuote{total} for the sum of the two. For undirected graphs
 #'   this argument is ignored. \dQuote{all} is a synonym of \dQuote{total}.
-#' @param loops Logical; whether the loop edges are also counted.
+#' @param loops Character string,
+#' `"none"` ignores loop edges;
+#' `"once"` counts each loop edge only once;
+#' `"twice"` (the default) counts each loop edge twice in undirected graphs
+#' and once in directed graphs.
 #' @param normalized Logical scalar, whether to normalize the degree.  If
 #'   `TRUE` then the result is divided by \eqn{n-1}, where \eqn{n} is the
 #'   number of vertices in the graph.
@@ -897,19 +911,33 @@ degree <- function(
   graph,
   v = V(graph),
   mode = c("all", "out", "in", "total"),
-  loops = TRUE,
+  loops = c("twice", "none", "once"),
   normalized = FALSE
 ) {
   ensure_igraph(graph)
-  v <- as_igraph_vs(graph, v)
   mode <- igraph.match.arg(mode)
 
+  if (is.logical(loops)) {
+    lifecycle::deprecate_soft(
+      "2.2.0",
+      "degree(loops = 'must be a character string')"
+    )
+    if (loops) {
+      loops <- "twice"
+    } else {
+      loops <- "none"
+    }
+  }
+
+  loops <- igraph.match.arg(loops)
+
   res <- degree_impl(
     graph,
     vids = v,
     mode = mode,
     loops = loops
   )
+
   if (normalized) {
     res <- res / (vcount(graph) - 1)
   }
@@ -922,8 +950,36 @@ degree <- function(
 #' @rdname degree
 #' @export
 #' @cdocs igraph_maxdegree
-max_degree <- maxdegree_impl
+max_degree <- function(
+  graph,
+  ...,
+  v = V(graph),
+  mode = c("all", "out", "in", "total"),
+  loops = c("twice", "none", "once")
+) {
+  ensure_igraph(graph)
+  mode <- igraph.match.arg(mode)
+
+  if (is.logical(loops)) {
+    lifecycle::deprecate_soft(
+      "2.2.0",
+      "max_degree(loops = 'must be a character string')"
+    )
+    if (loops) {
+      loops <- "twice"
+    } else {
+      loops <- "none"
+    }
+  }
+  loops <- igraph.match.arg(loops)
 
+  maxdegree_impl(
+    graph,
+    v = v,
+    mode = mode,
+    loops = loops
+  )
+}
 #' @rdname degree
 #' @param cumulative Logical; whether the cumulative degree distribution is to
 #'   be calculated.
diff --git a/R/topology.R b/R/topology.R
index 14bc4bd81f3..9012a65fa80 100644
--- a/R/topology.R
+++ b/R/topology.R
@@ -1122,7 +1122,7 @@ canonical_permutation <- function(
   colors = NULL,
   sh = c("fm", "f", "fs", "fl", "flm", "fsm")
 ) {
-  canonical_permutation_impl(
+  canonical_permutation_bliss_impl(
     graph = graph,
     colors = if (missing(colors)) missing_arg() else colors,
     sh = sh
@@ -1274,7 +1274,7 @@ count_automorphisms <- function(
   colors = NULL,
   sh = c("fm", "f", "fs", "fl", "flm", "fsm")
 ) {
-  count_automorphisms_impl(
+  count_automorphisms_bliss_impl(
     graph = graph,
     colors = if (missing(colors)) missing_arg() else colors,
     sh = sh
@@ -1305,24 +1305,6 @@ count_automorphisms <- function(
 #'   vertices, or, if there is no such vertex attribute, it simply assumes that
 #'   all vertices have the same color. Pass NULL explicitly if the graph has a
 #'   `color` vertex attribute but you do not want to use it.
-#' @param sh The splitting heuristics for the BLISS algorithm. Possible values
-#'   are:
-#'   \sQuote{`f`}:
-#'     first non-singleton cell,
-#'   \sQuote{`fl`}:
-#'     first largest non-singleton cell,
-#'   \sQuote{`fs`}:
-#'     first smallest non-singleton cell,
-#'   \sQuote{`fm`}:
-#'     first maximally non-trivially connected
-#'     non-singleton cell,
-#'   \sQuote{`flm`}:
-#'     first largest maximally
-#'     non-trivially connected non-singleton cell,
-#'   \sQuote{`fsm`}:
-#'     first smallest maximally non-trivially connected non-singleton cell.
-#' @param details Specifies whether to provide additional details about the
-#'   BLISS internals in the result.
 #' @return When `details` is `FALSE`, a list of vertex permutations
 #'   that form a generating set of the automorphism group of the input graph.
 #'   When `details` is `TRUE`, a named list with two members:
diff --git a/R/trees.R b/R/trees.R
index 49e0e3d45f7..3852dac3e8c 100644
--- a/R/trees.R
+++ b/R/trees.R
@@ -145,7 +145,7 @@ to_prufer <- function(graph) {
 #' @param graph The input graph to sample from. Edge directions are ignored if
 #'   the graph is directed.
 #' @param vid When the graph is disconnected, this argument specifies how to
-#'   handle the situation. When the argument is zero (the default), the sampling
+#'   handle the situation. When the argument is `NULL` (the default), the sampling
 #'   will be performed component-wise, and the result will be a spanning forest.
 #'   When the argument contains a vertex ID, only the component containing the
 #'   given vertex will be processed, and the result will be a spanning tree of the
@@ -164,4 +164,7 @@ to_prufer <- function(graph) {
 #' @family trees
 #' @export
 #' @cdocs igraph_random_spanning_tree
-sample_spanning_tree <- random_spanning_tree_impl
+sample_spanning_tree <- function(graph, vid = NULL) {
+  vid <- vid %||% 0
+  random_spanning_tree_impl(graph, vid)
+}
diff --git a/R/triangles.R b/R/triangles.R
index 8321e044795..1745ab62254 100644
--- a/R/triangles.R
+++ b/R/triangles.R
@@ -97,7 +97,7 @@ triangles <- function(graph) {
 
 #' @export
 #' @rdname count_triangles
-#' @cdocs igraph_adjacent_triangles
+#' @cdocs igraph_count_adjacent_triangles
 count_triangles <- function(graph, vids = V(graph)) {
   count_adjacent_triangles_impl(
     graph = graph,
diff --git a/src/rinterface_extra.c b/src/rinterface_extra.c
index 5e08a4021b1..1f6d7763ffb 100644
--- a/src/rinterface_extra.c
+++ b/src/rinterface_extra.c
@@ -21,6 +21,8 @@
 
 */
 
+#include "igraph_random.h"
+#include "igraph_sampling.h"
 #include "rinterface.h"
 #include "rrandom.h"
 
@@ -43,6 +45,11 @@
 #include <sanitizer/asan_interface.h>
 #endif
 
+
+#define RNG_BEGIN()    GetRNGstate()
+#define RNG_END()      PutRNGstate()
+
+
 enum igraph_t_idx {
   igraph_t_idx_n = 0,
   igraph_t_idx_directed = 1,
@@ -132,6 +139,11 @@ void igraph_vector_int_list_destroy_pv(void *pv_ptr)
   igraph_vector_int_list_destroy((igraph_vector_int_list_t*) pv_ptr);
 }
 
+void igraph_es_destroy_pv(void* pv_ptr)
+{
+  igraph_es_destroy((igraph_es_t*) pv_ptr);
+}
+
 igraph_error_t R_get_int_scalar(SEXP sexp, R_xlen_t index, igraph_integer_t *res)
 {
   if (Rf_xlength(sexp) <= index)
@@ -377,7 +389,7 @@ void R_igraph_attribute_clean_preserve_list(void) {
   }
 }
 
-igraph_error_t R_igraph_attribute_init(igraph_t *graph, igraph_vector_ptr_t *attr) {
+igraph_error_t R_igraph_attribute_init(igraph_t *graph, const igraph_attribute_record_list_t *attr) {
   SEXP result, names, gal;
   int px = 0;
 
@@ -404,12 +416,12 @@ igraph_error_t R_igraph_attribute_init(igraph_t *graph, igraph_vector_ptr_t *att
   graph->attr=result;
 
   /* Add graph attributes */
-  igraph_integer_t attrno= attr==NULL ? 0 : igraph_vector_ptr_size(attr);
+  igraph_integer_t attrno= attr==NULL ? 0 : igraph_attribute_record_list_size(attr);
   SET_VECTOR_ELT(result, 1, NEW_LIST(attrno));
   gal=VECTOR_ELT(result, 1);
   PROTECT(names=NEW_CHARACTER(attrno)); px++;
   for (igraph_integer_t i=0; i<attrno; i++) {
-    igraph_attribute_record_t *rec=VECTOR(*attr)[i];
+    igraph_attribute_record_t *rec=igraph_attribute_record_list_get_ptr(attr, i);
     igraph_vector_t *vec;
     igraph_vector_bool_t *log;
     igraph_strvector_t *strvec;
@@ -417,21 +429,21 @@ igraph_error_t R_igraph_attribute_init(igraph_t *graph, igraph_vector_ptr_t *att
     SET_VECTOR_ELT(gal, i, R_NilValue);
     switch (rec->type) {
     case IGRAPH_ATTRIBUTE_NUMERIC:
-      vec=(igraph_vector_t*) rec->value;
+      vec = rec->value.as_vector;
       if (igraph_vector_size(vec) > 0) {
         SET_VECTOR_ELT(gal, i, NEW_NUMERIC(1));
         REAL(VECTOR_ELT(gal, i))[0]=VECTOR(*vec)[0];
       }
       break;
     case IGRAPH_ATTRIBUTE_BOOLEAN:
-      log=(igraph_vector_bool_t*) rec->value;
+      log = rec->value.as_vector_bool;
       if (igraph_vector_bool_size(log) > 0) {
         SET_VECTOR_ELT(gal, i, NEW_LOGICAL(1));
         LOGICAL(VECTOR_ELT(gal, i))[0]=VECTOR(*log)[0];
       }
       break;
     case IGRAPH_ATTRIBUTE_STRING:
-      strvec=(igraph_strvector_t*) rec->value;
+      strvec = rec->value.as_strvector;
       if (igraph_strvector_size(strvec) > 0) {
         SET_VECTOR_ELT(gal, i, NEW_CHARACTER(1));
         SET_STRING_ELT(VECTOR_ELT(gal,i), 0, Rf_mkChar(igraph_strvector_get(strvec, 0)));
@@ -487,22 +499,22 @@ igraph_error_t R_igraph_attribute_copy(igraph_t *to, const igraph_t *from,
   return 0;
 }
 
-SEXP R_igraph_attribute_add_vertices_append1(igraph_vector_ptr_t *nattr,
+SEXP R_igraph_attribute_add_vertices_append1(const igraph_attribute_record_list_t *nattr,
                                              int j, int nv) {
 
   SEXP app = R_NilValue;
-  igraph_attribute_record_t *tmprec=VECTOR(*nattr)[j-1];
+  igraph_attribute_record_t *tmprec=igraph_attribute_record_list_get_ptr(nattr, j-1);
   igraph_integer_t len = 0;
 
   switch (tmprec->type) {
   case IGRAPH_ATTRIBUTE_NUMERIC:
-    len = igraph_vector_size(tmprec->value);
+    len = igraph_vector_size(tmprec->value.as_vector);
     break;
   case IGRAPH_ATTRIBUTE_BOOLEAN:
-    len = igraph_vector_bool_size(tmprec->value);
+    len = igraph_vector_bool_size(tmprec->value.as_vector_bool);
     break;
   case IGRAPH_ATTRIBUTE_STRING:
-    len = igraph_strvector_size(tmprec->value);
+    len = igraph_strvector_size(tmprec->value.as_strvector);
     break;
   case IGRAPH_ATTRIBUTE_OBJECT:
     igraph_error("R objects not implemented yet", __FILE__, __LINE__,
@@ -525,13 +537,13 @@ SEXP R_igraph_attribute_add_vertices_append1(igraph_vector_ptr_t *nattr,
   switch (tmprec->type) {
   case IGRAPH_ATTRIBUTE_NUMERIC:
     PROTECT(app=NEW_NUMERIC(nv));
-    igraph_vector_copy_to(tmprec->value, REAL(app));
+    igraph_vector_copy_to(tmprec->value.as_vector, REAL(app));
     break;
   case IGRAPH_ATTRIBUTE_BOOLEAN:
-    PROTECT(app=R_igraph_vector_bool_to_SEXP(tmprec->value));
+    PROTECT(app=R_igraph_vector_bool_to_SEXP(tmprec->value.as_vector_bool));
     break;
   default: /* IGRAPH_ATTRIBUTE_STRING */
-    PROTECT(app=R_igraph_strvector_to_SEXP(tmprec->value));
+    PROTECT(app=R_igraph_strvector_to_SEXP(tmprec->value.as_strvector));
     break;
   }
 
@@ -540,7 +552,7 @@ SEXP R_igraph_attribute_add_vertices_append1(igraph_vector_ptr_t *nattr,
 }
 
 void R_igraph_attribute_add_vertices_append(SEXP val, igraph_integer_t nv,
-                                            igraph_vector_ptr_t *nattr) {
+                                            const igraph_attribute_record_list_t *nattr) {
   SEXP names;
   igraph_integer_t valno, nattrno;
   SEXP rep = R_NilValue;
@@ -551,7 +563,7 @@ void R_igraph_attribute_add_vertices_append(SEXP val, igraph_integer_t nv,
   if (nattr==NULL) {
     nattrno=0;
   } else {
-    nattrno=igraph_vector_ptr_size(nattr);
+    nattrno=igraph_attribute_record_list_size(nattr);
   }
 
   for (igraph_integer_t i=0; i<valno; i++) {
@@ -560,7 +572,7 @@ void R_igraph_attribute_add_vertices_append(SEXP val, igraph_integer_t nv,
     igraph_bool_t l=0;
     igraph_integer_t j;
     for (j=0; !l && j<nattrno; j++) {
-      igraph_attribute_record_t *tmp=VECTOR(*nattr)[j];
+      igraph_attribute_record_t *tmp=igraph_attribute_record_list_get_ptr(nattr, j);
       l=!strcmp(sexpname, tmp->name);
     }
     if (l) {
@@ -596,7 +608,7 @@ SEXP R_igraph_attribute_add_vertices_dup(SEXP attr) {
 }
 
 igraph_error_t R_igraph_attribute_add_vertices(igraph_t *graph, igraph_integer_t nv,
-                                    igraph_vector_ptr_t *nattr) {
+                                    const igraph_attribute_record_list_t *nattr) {
   SEXP attr=graph->attr;
   SEXP val, rep=0, names, newnames;
   igraph_vector_int_t news;
@@ -612,7 +624,7 @@ igraph_error_t R_igraph_attribute_add_vertices(igraph_t *graph, igraph_integer_t
   if (nattr==NULL) {
     nattrno=0;
   } else {
-    nattrno=igraph_vector_ptr_size(nattr);
+    nattrno=igraph_attribute_record_list_size(nattr);
   }
   origlen=igraph_vcount(graph)-nv;
 
@@ -621,7 +633,7 @@ igraph_error_t R_igraph_attribute_add_vertices(igraph_t *graph, igraph_integer_t
   if (igraph_vector_int_init(&news, 0)) Rf_error("Out of memory");
   IGRAPH_FINALLY_PV(igraph_vector_int_destroy, &news);
   for (igraph_integer_t i=0; i<nattrno; i++) {
-    igraph_attribute_record_t *nattr_entry=VECTOR(*nattr)[i];
+    igraph_attribute_record_t *nattr_entry=igraph_attribute_record_list_get_ptr(nattr, i);
     const char *nname=nattr_entry->name;
     igraph_bool_t l=0;
     for (igraph_integer_t j=0; !l && j<valno; j++) {
@@ -642,7 +654,7 @@ igraph_error_t R_igraph_attribute_add_vertices(igraph_t *graph, igraph_integer_t
     SEXP l4 = PROTECT(Rf_lang3(l1, l2, l3));
     PROTECT(rep = Rf_eval(l4, R_GlobalEnv));
     for (igraph_integer_t i=0; i<newattrs; i++) {
-      igraph_attribute_record_t *tmp = VECTOR(*nattr)[VECTOR(news)[i]];
+      igraph_attribute_record_t *tmp = igraph_attribute_record_list_get_ptr(nattr, VECTOR(news)[i]);
       SET_VECTOR_ELT(app, i, rep);
       SET_STRING_ELT(newnames, i, Rf_mkChar(tmp->name));
     }
@@ -827,22 +839,22 @@ SEXP R_igraph_attribute_add_edges_dup(SEXP attr) {
   return newattr;
 }
 
-SEXP R_igraph_attribute_add_edges_append1(igraph_vector_ptr_t *nattr, igraph_integer_t j,
+SEXP R_igraph_attribute_add_edges_append1(const igraph_attribute_record_list_t *nattr, igraph_integer_t j,
                                           igraph_integer_t ne) {
 
   SEXP app = R_NilValue;
-  igraph_attribute_record_t *tmprec=VECTOR(*nattr)[j-1];
+  igraph_attribute_record_t *tmprec=igraph_attribute_record_list_get_ptr(nattr, j-1);
   igraph_integer_t len = 0;
 
   switch(tmprec->type) {
   case IGRAPH_ATTRIBUTE_NUMERIC:
-    len = igraph_vector_size(tmprec->value);
+    len = igraph_vector_size(tmprec->value.as_vector);
     break;
   case IGRAPH_ATTRIBUTE_BOOLEAN:
-    len = igraph_vector_bool_size(tmprec->value);
+    len = igraph_vector_bool_size(tmprec->value.as_vector_bool);
     break;
   case IGRAPH_ATTRIBUTE_STRING:
-    len = igraph_strvector_size(tmprec->value);
+    len = igraph_strvector_size(tmprec->value.as_strvector);
     break;
   case IGRAPH_ATTRIBUTE_OBJECT:
     igraph_error("R objects not implemented yet", __FILE__, __LINE__,
@@ -865,13 +877,15 @@ SEXP R_igraph_attribute_add_edges_append1(igraph_vector_ptr_t *nattr, igraph_int
   switch (tmprec->type) {
   case IGRAPH_ATTRIBUTE_NUMERIC:
     PROTECT(app=NEW_NUMERIC(ne));
-    igraph_vector_copy_to(tmprec->value, REAL(app));
+    igraph_vector_copy_to(tmprec->value.as_vector, REAL(app));
     break;
   case IGRAPH_ATTRIBUTE_BOOLEAN:
-    PROTECT(app=R_igraph_vector_bool_to_SEXP(tmprec->value));
+    PROTECT(app=R_igraph_vector_bool_to_SEXP(tmprec->value.as_vector_bool));
     break;
-  default: /* IGRAPH_ATTRIBUTE_STRING */
-    PROTECT(app=R_igraph_strvector_to_SEXP(tmprec->value));
+  case IGRAPH_ATTRIBUTE_STRING:
+    PROTECT(app=R_igraph_strvector_to_SEXP(tmprec->value.as_strvector));
+    break;
+  default:
     break;
   }
 
@@ -881,7 +895,7 @@ SEXP R_igraph_attribute_add_edges_append1(igraph_vector_ptr_t *nattr, igraph_int
 
 void R_igraph_attribute_add_edges_append(SEXP eal,
                                          const igraph_vector_int_t *edges,
-                                         igraph_vector_ptr_t *nattr) {
+                                         const igraph_attribute_record_list_t *nattr) {
   SEXP names;
   igraph_integer_t ealno;
   igraph_integer_t ne=igraph_vector_int_size(edges)/2, nattrno;
@@ -893,7 +907,7 @@ void R_igraph_attribute_add_edges_append(SEXP eal,
   if (nattr==NULL) {
     nattrno=0;
   } else {
-    nattrno=igraph_vector_ptr_size(nattr);
+    nattrno=igraph_attribute_record_list_size(nattr);
   }
 
   for (igraph_integer_t i=0; i<ealno; i++) {
@@ -902,7 +916,7 @@ void R_igraph_attribute_add_edges_append(SEXP eal,
     igraph_bool_t l=0;
     igraph_integer_t j;
     for (j=0; !l && j<nattrno; j++) {
-      igraph_attribute_record_t *tmp=VECTOR(*nattr)[j];
+      igraph_attribute_record_t *tmp=igraph_attribute_record_list_get_ptr(nattr, j);
       l=!strcmp(sexpname, tmp->name);
     }
     if (l) {
@@ -930,7 +944,7 @@ void R_igraph_attribute_add_edges_append(SEXP eal,
 }
 
 igraph_error_t R_igraph_attribute_add_edges(igraph_t *graph, const igraph_vector_int_t *edges,
-                                igraph_vector_ptr_t *nattr) {
+                                const igraph_attribute_record_list_t *nattr) {
   SEXP attr=graph->attr;
   SEXP eal, names, newnames;
   igraph_vector_int_t news;
@@ -950,14 +964,14 @@ igraph_error_t R_igraph_attribute_add_edges(igraph_t *graph, const igraph_vector
   if (nattr==NULL) {
     nattrno=0;
   } else {
-    nattrno=igraph_vector_ptr_size(nattr);
+    nattrno=igraph_attribute_record_list_size(nattr);
   }
   origlen=igraph_ecount(graph)-ne;
 
   /* First add the new attributes, if any */
   newattrs=0;
   for (igraph_integer_t i=0; i<nattrno; i++) {
-    igraph_attribute_record_t *nattr_entry=VECTOR(*nattr)[i];
+    igraph_attribute_record_t *nattr_entry=igraph_attribute_record_list_get_ptr(nattr, i);
     const char *nname=nattr_entry->name;
     igraph_bool_t l=0;
     for (igraph_integer_t j=0; !l && j<ealno; j++) {
@@ -979,7 +993,7 @@ igraph_error_t R_igraph_attribute_add_edges(igraph_t *graph, const igraph_vector
     SEXP rep = PROTECT(Rf_eval(l4, R_GlobalEnv));
     for (igraph_integer_t i=0; i<newattrs; i++) {
       igraph_attribute_record_t *tmp=
-        VECTOR(*nattr)[VECTOR(news)[i]];
+        igraph_attribute_record_list_get_ptr(nattr, VECTOR(news)[i]);
       SET_VECTOR_ELT(app, i, rep);
       SET_STRING_ELT(newnames, i, Rf_mkChar(tmp->name));
     }
@@ -1905,7 +1919,7 @@ igraph_error_t R_igraph_attribute_combine_vertices(const igraph_t *graph,
 
   /* Create the TODO list first */
   PROTECT(names=GET_NAMES(val)); px++;
-  TODO=igraph_Calloc(valno, igraph_integer_t);
+  TODO=IGRAPH_CALLOC(valno, igraph_integer_t);
   if (!TODO) {
     UNPROTECT(px);
     IGRAPH_ERROR("Cannot combine edge attributes",
@@ -2079,7 +2093,7 @@ igraph_error_t R_igraph_attribute_combine_edges(const igraph_t *graph,
                  IGRAPH_ENOMEM);
   }
   IGRAPH_FINALLY(igraph_free, TODO);
-  funcs=igraph_Calloc(ealno, igraph_function_pointer_t);
+  funcs=IGRAPH_CALLOC(ealno, igraph_function_pointer_t);
   if (!funcs) {
     UNPROTECT(px);
     IGRAPH_ERROR("Cannot combine edge attributes",
@@ -2352,7 +2366,7 @@ void checkInterruptFn(void *dummy) {
   R_CheckUserInterrupt();
 }
 
-igraph_error_t R_igraph_interrupt_handler(void *data) {
+igraph_bool_t R_igraph_interrupt_handler(void) {
   /* We need to call R_CheckUserInterrupt() regularly to enable interruptions.
    * However, if an interruption is pending, R_CheckUserInterrupt() will
    * longjmp back to the top level so we cannot clean up ourselves by calling
@@ -2368,9 +2382,9 @@ igraph_error_t R_igraph_interrupt_handler(void *data) {
    */
   if (R_ToplevelExec(checkInterruptFn, NULL) == FALSE) {
     IGRAPH_FINALLY_FREE();
-    return IGRAPH_INTERRUPTED;
+    return true;
   }
-  return IGRAPH_SUCCESS;
+  return false;
 }
 
 igraph_error_t R_igraph_progress_handler(const char *message, double percent,
@@ -2394,17 +2408,15 @@ igraph_error_t R_igraph_progress_handler(const char *message, double percent,
 }
 
 igraph_error_t R_igraph_status_handler(const char *message, void *data) {
-  SEXP l1 = PROTECT(Rf_install("getNamespace"));
-  SEXP l2 = PROTECT(Rf_ScalarString(PROTECT(Rf_mkChar("igraph"))));
-  SEXP l3 = PROTECT(Rf_lang2(l1, l2));
-  SEXP rho = PROTECT(Rf_eval(l3, R_BaseEnv));
-
-  SEXP l4 = PROTECT(Rf_install(".igraph.status"));
+  SEXP l1 = PROTECT(Rf_install(":::"));
+  SEXP l2 = PROTECT(Rf_install("igraph"));
+  SEXP l3 = PROTECT(Rf_install(".igraph.status"));
+  SEXP l4 = PROTECT(Rf_lang3(l1, l2, l3));
   SEXP l5 = PROTECT(Rf_ScalarString(PROTECT(Rf_mkChar(message))));
   SEXP l6 = PROTECT(Rf_lang2(l4, l5));
-  PROTECT(Rf_eval(l6, rho));
+  PROTECT(Rf_eval(l6, R_BaseEnv));
 
-  UNPROTECT(10);
+  UNPROTECT(8);
   return 0;
 }
 
@@ -2660,7 +2672,7 @@ SEXP R_igraph_matrix_to_SEXP(const igraph_matrix_t *m) {
   }
 
   PROTECT(result=NEW_NUMERIC(igraph_matrix_size(m)));
-  igraph_matrix_copy_to(m, REAL(result));
+  igraph_matrix_copy_to(m, REAL(result), IGRAPH_COLUMN_MAJOR);
   PROTECT(dim=NEW_INTEGER(2));
   INTEGER(dim)[0] = (int) nrow;
   INTEGER(dim)[1] = (int) ncol;
@@ -2727,7 +2739,7 @@ SEXP R_igraph_matrix_complex_to_SEXP(const igraph_matrix_complex_t *m) {
   }
 
   PROTECT(result=NEW_COMPLEX(igraph_matrix_complex_size(m)));
-  igraph_matrix_complex_copy_to(m, (igraph_complex_t*) COMPLEX(result));
+  igraph_matrix_complex_copy_to(m, (igraph_complex_t*) COMPLEX(result), IGRAPH_COLUMN_MAJOR);
   PROTECT(dim=NEW_INTEGER(2));
   INTEGER(dim)[0] = (int) nrow;
   INTEGER(dim)[1] = (int) ncol;
@@ -3257,7 +3269,7 @@ SEXP R_igraph_sparsemat_to_SEXP_cc(const igraph_sparsemat_t *sp) {
     igraph_vector_t x;
     R_SEXP_to_vector_int_copy(VECTOR_ELT(res, 2), &p);
     R_SEXP_to_vector_int_copy(VECTOR_ELT(res, 3), &i);
-    igraph_vector_view(&x, REAL(VECTOR_ELT(res, 4)), nz);
+    x = igraph_vector_view(REAL(VECTOR_ELT(res, 4)), nz);
     igraph_sparsemat_getelements_sorted(sp, &i, &p, &x);
   }
 
@@ -3323,7 +3335,7 @@ void R_igraph_SEXP_to_vector_list(SEXP vectorlist, igraph_vector_list_t *list) {
   for (igraph_integer_t i=0; i<length; i++) {
     igraph_vector_t *v=&vecs[i];
     SEXP el=VECTOR_ELT(vectorlist, i);
-    igraph_vector_view(v, REAL(el), Rf_xlength(el));
+    *v = igraph_vector_view(REAL(el), Rf_xlength(el));
   }
 }
 
@@ -3362,13 +3374,13 @@ void R_igraph_SEXP_to_matrixlist(SEXP matrixlist, igraph_matrix_list_t *list) {
     igraph_matrix_t *v=&vecs[i];
     SEXP el=VECTOR_ELT(matrixlist, i);
     SEXP dim=GET_DIM(el);
-    igraph_matrix_view(v, REAL(el), INTEGER(dim)[0], INTEGER(dim)[1]);
+    *v = igraph_matrix_view(REAL(el), INTEGER(dim)[0], INTEGER(dim)[1]);
   }
 }
 
 igraph_error_t R_igraph_SEXP_to_strvector(SEXP rval, igraph_strvector_t *sv) {
   const igraph_integer_t length = Rf_xlength(rval);
-  sv->stor_begin=(char**) R_alloc((size_t) length, sizeof(char*));
+  sv->stor_begin=(const char**) R_alloc((size_t) length, sizeof(char*));
   sv->stor_end=sv->stor_begin+length;
   sv->end=sv->stor_end;
   for (igraph_integer_t i=0; i<length; i++) {
@@ -3875,27 +3887,6 @@ SEXP R_igraph_ecount(SEXP graph) {
   return result;
 }
 
-SEXP R_igraph_incident(SEXP graph, SEXP pvid, SEXP pmode) {
-
-  igraph_t g;
-  igraph_vector_int_t neis;
-  SEXP result;
-  igraph_real_t vid;
-  igraph_neimode_t mode;
-
-  igraph_vector_int_init(&neis, 0);
-  vid=REAL(pvid)[0];
-  mode = (igraph_neimode_t) Rf_asInteger(pmode);
-  R_SEXP_to_igraph(graph, &g);
-  IGRAPH_R_CHECK(igraph_incident(&g, &neis, (igraph_integer_t) vid, mode));
-
-  PROTECT(result=R_igraph_vector_int_to_SEXP(&neis));
-  igraph_vector_int_destroy(&neis);
-
-  UNPROTECT(1);
-  return result;
-}
-
 SEXP R_igraph_delete_edges(SEXP graph, SEXP edges) {
 
   igraph_es_t es;
@@ -3971,29 +3962,6 @@ SEXP R_igraph_create(SEXP edges, SEXP pn, SEXP pdirected) {
   return result;
 }
 
-SEXP R_igraph_diameter(SEXP graph, SEXP pdirected, SEXP punconnected,
-                       SEXP pweights) {
-
-  igraph_t g;
-  igraph_bool_t directed=LOGICAL(pdirected)[0];
-  igraph_bool_t unconnected=LOGICAL(punconnected)[0];
-  igraph_vector_t weights;
-  igraph_real_t res;
-  SEXP result;
-
-  R_SEXP_to_igraph(graph, &g);
-  if (!Rf_isNull(pweights)) {
-    R_SEXP_to_vector(pweights, &weights);
-  }
-  IGRAPH_R_CHECK(igraph_diameter_dijkstra(&g, Rf_isNull(pweights) ? 0 : &weights, &res, 0, 0, 0, 0, directed, unconnected));
-
-  PROTECT(result=NEW_NUMERIC(1));
-  REAL(result)[0]=res;
-
-  UNPROTECT(1);
-  return result;
-}
-
 SEXP R_igraph_get_diameter(SEXP graph, SEXP pdirected, SEXP punconnected,
                            SEXP pweights) {
 
@@ -4010,7 +3978,7 @@ SEXP R_igraph_get_diameter(SEXP graph, SEXP pdirected, SEXP punconnected,
     R_SEXP_to_vector(pweights, &weights);
   }
   igraph_vector_int_init(&res, 0);
-  IGRAPH_R_CHECK(igraph_diameter_dijkstra(&g, Rf_isNull(pweights) ? 0 : &weights, &dialen, 0, 0, &res, 0, directed, unconnected));
+  IGRAPH_R_CHECK(igraph_diameter(&g, Rf_isNull(pweights) ? 0 : &weights, &dialen, 0, 0, &res, 0, directed, unconnected));
 
   PROTECT(result=R_igraph_vector_int_to_SEXP(&res));
   igraph_vector_int_destroy(&res);
@@ -4034,7 +4002,7 @@ SEXP R_igraph_farthest_points(SEXP graph, SEXP pdirected, SEXP punconnected,
   if (!Rf_isNull(pweights)) {
     R_SEXP_to_vector(pweights, &weights);
   }
-  IGRAPH_R_CHECK(igraph_diameter_dijkstra(&g, Rf_isNull(pweights) ? 0 : &weights, &len, &from, &to, 0, 0, directed, unconnected));
+  IGRAPH_R_CHECK(igraph_diameter(&g, Rf_isNull(pweights) ? 0 : &weights, &len, &from, &to, 0, 0, directed, unconnected));
 
   PROTECT(result=NEW_NUMERIC(3));
   if (from < 0) {
@@ -4146,19 +4114,14 @@ static igraph_error_t distances_johnson(const igraph_t *graph,
   }
   if (mode == IGRAPH_ALL && negw) {
     /* Reject undirected grahs with negative weights, just like igraph_shortest_paths_johnson() would. */
-    IGRAPH_ERROR("Undirected graph with negative weight.", IGRAPH_ENEGLOOP);
+    IGRAPH_ERROR("Undirected graph with negative weight.", IGRAPH_ENEGCYCLE);
   }
   if (! negw) {
     /* Fall back to Dijstra when there are no negative weights, just like igraph_shortest_paths_johnson() would. */
     return igraph_distances_dijkstra(graph, res, from, to, weights, mode);
   }
   /* We simulate mode=IN by swapping to/from and transposing the result matrix. */
-  if (mode == IGRAPH_IN) {
-    IGRAPH_CHECK(igraph_distances_johnson(graph, res, to, from, weights));
-    IGRAPH_CHECK(igraph_matrix_transpose(res));
-  } else {
-    IGRAPH_CHECK(igraph_distances_johnson(graph, res, from, to, weights));
-  }
+  IGRAPH_CHECK(igraph_distances_johnson(graph, res, to, from, weights, mode));
   return IGRAPH_SUCCESS;
 }
 
@@ -4198,7 +4161,7 @@ SEXP R_igraph_shortest_paths(SEXP graph, SEXP pvids, SEXP pto,
     }
     break;
   case 1:                       /* unweighted */
-    IGRAPH_R_CHECK(igraph_distances(&g, &res, vs, to, mode));
+    IGRAPH_R_CHECK(igraph_distances(&g, NULL, &res, vs, to, mode));
     break;
   case 2:                       /* dijkstra */
     IGRAPH_R_CHECK(igraph_distances_dijkstra(&g, &res, vs, to, pw, mode));
@@ -4524,39 +4487,6 @@ SEXP R_igraph_layout_lgl(SEXP graph, SEXP pmaxiter, SEXP pmaxdelta,
   return result;
 }
 
-SEXP R_igraph_minimum_spanning_tree_unweighted(SEXP graph) {
-
-  igraph_t g;
-  igraph_t mst;
-  SEXP result;
-
-  R_SEXP_to_igraph(graph, &g);
-  IGRAPH_R_CHECK(igraph_minimum_spanning_tree_unweighted(&g, &mst));
-  PROTECT(result=R_igraph_to_SEXP(&mst));
-  IGRAPH_I_DESTROY(&mst);
-
-  UNPROTECT(1);
-  return result;
-}
-
-SEXP R_igraph_minimum_spanning_tree_prim(SEXP graph, SEXP pweights) {
-
-  igraph_t g;
-  igraph_t mst;
-  igraph_vector_t weights;
-  SEXP result;
-
-  R_SEXP_to_vector(pweights, &weights);
-
-  R_SEXP_to_igraph(graph, &g);
-  IGRAPH_R_CHECK(igraph_minimum_spanning_tree_prim(&g, &mst, &weights));
-  PROTECT(result=R_igraph_to_SEXP(&mst));
-  IGRAPH_I_DESTROY(&mst);
-
-  UNPROTECT(1);
-  return result;
-}
-
 SEXP R_igraph_get_shortest_paths(SEXP graph, SEXP pfrom, SEXP pto,
                                  SEXP pmode, SEXP pno, SEXP weights,
                                  SEXP output, SEXP ppred, SEXP pinbound,
@@ -4611,7 +4541,7 @@ SEXP R_igraph_get_shortest_paths(SEXP graph, SEXP pfrom, SEXP pto,
     }
     break;
   case 1:                       /* unweighted */
-    IGRAPH_R_CHECK(igraph_get_shortest_paths(&g, verts ? &list : 0, edges ? &elist : 0, from, to, mode, pred ? &predvec : 0, inbound ? &inboundvec : 0));
+    IGRAPH_R_CHECK(igraph_get_shortest_paths(&g, pw, verts ? &list : 0, edges ? &elist : 0, from, to, mode, pred ? &predvec : 0, inbound ? &inboundvec : 0));
     break;
   case 2:                       /* dijkstra */
     IGRAPH_R_CHECK(igraph_get_shortest_paths_dijkstra(&g, verts ? &list : 0, edges ? &elist : 0, from, to, pw, mode, pred ? &predvec : 0, inbound ? &inboundvec : 0));
@@ -5615,7 +5545,7 @@ SEXP R_igraph_edges(SEXP graph, SEXP eids) {
   R_SEXP_to_igraph(graph, &g);
   R_SEXP_to_igraph_es(eids, &g, &es, &es_data);
   igraph_vector_int_init(&res, 0);
-  IGRAPH_R_CHECK(igraph_edges(&g, es, &res));
+  IGRAPH_R_CHECK(igraph_edges(&g, es, &res, false));
 
   PROTECT(result=R_igraph_vector_int_to_SEXP(&res));
   igraph_vector_int_destroy(&res);
@@ -5733,11 +5663,11 @@ SEXP R_igraph_rewire(SEXP graph, SEXP pn, SEXP pmode) {
 
   igraph_t g;
   igraph_integer_t n=(igraph_integer_t) REAL(pn)[0];
-  igraph_rewiring_t mode=REAL(pmode)[0];
+  igraph_edge_type_sw_t mode=REAL(pmode)[0];
   SEXP result;
 
   R_SEXP_to_igraph_copy(graph, &g);
-  IGRAPH_R_CHECK(igraph_rewire(&g, n, mode));
+  IGRAPH_R_CHECK(igraph_rewire(&g, n, mode, /* stats= */ NULL));
   PROTECT(result=R_igraph_to_SEXP(&g));
   IGRAPH_I_DESTROY(&g);
 
@@ -5823,7 +5753,10 @@ SEXP R_igraph_vs_nei(SEXP graph, SEXP px, SEXP pv, SEXP pmode) {
   while (!IGRAPH_VIT_END(vv)) {
     igraph_integer_t neis_size;
 
-    IGRAPH_R_CHECK(igraph_neighbors(&g, &neis, IGRAPH_VIT_GET(vv), mode));
+    // FIXME: expose
+    igraph_bool_t loops = false;
+    igraph_bool_t multiple = false;
+    IGRAPH_R_CHECK(igraph_neighbors(&g, &neis, IGRAPH_VIT_GET(vv), mode, loops, multiple));
 
     neis_size = igraph_vector_int_size(&neis);
     for (igraph_integer_t i=0; i < neis_size; i++) {
@@ -5904,7 +5837,9 @@ SEXP R_igraph_es_adj(SEXP graph, SEXP x, SEXP pv, SEXP pmode) {
   while (!IGRAPH_VIT_END(vv)) {
     igraph_integer_t adje_size;
 
-    IGRAPH_R_CHECK(igraph_incident(&g, &adje, IGRAPH_VIT_GET(vv), mode));
+    // FIXME: expose
+    igraph_bool_t loops = false;
+    IGRAPH_R_CHECK(igraph_incident(&g, &adje, IGRAPH_VIT_GET(vv), mode, loops));
     adje_size = igraph_vector_int_size(&adje);
 
     for (igraph_integer_t i=0; i < adje_size; i++) {
@@ -6335,8 +6270,8 @@ SEXP R_igraph_spinglass_my_community(SEXP graph, SEXP weights,
   igraph_vector_int_t community;
   igraph_real_t cohesion;
   igraph_real_t adhesion;
-  igraph_integer_t inner_links;
-  igraph_integer_t outer_links;
+  igraph_real_t inner_links;
+  igraph_real_t outer_links;
 
   SEXP result, names;
 
@@ -6486,9 +6421,10 @@ SEXP R_igraph_watts_strogatz_game(SEXP pdim, SEXP psize, SEXP pnei, SEXP pp,
   igraph_real_t p=REAL(pp)[0];
   igraph_bool_t loops=LOGICAL(ploops)[0];
   igraph_bool_t multiple=LOGICAL(pmultiple)[0];
+  igraph_edge_type_sw_t allowed_edge_types = (loops ? IGRAPH_LOOPS_SW : 0) | (multiple ? IGRAPH_MULTI_SW : IGRAPH_SIMPLE_SW);
   SEXP result;
 
-  IGRAPH_R_CHECK(igraph_watts_strogatz_game(&g, dim, size, nei, p, loops, multiple));
+  IGRAPH_R_CHECK(igraph_watts_strogatz_game(&g, dim, size, nei, p, allowed_edge_types));
   PROTECT(result=R_igraph_to_SEXP(&g));
   IGRAPH_I_DESTROY(&g);
 
@@ -6534,7 +6470,7 @@ SEXP R_igraph_maximal_cliques(SEXP graph, SEXP psubset,
   igraph_vector_int_list_init(&list, 0);
   igraph_maximal_cliques_subset(&g, Rf_isNull(psubset) ? 0 : &subset,
                                 &list, /*no=*/ 0, /*file=*/ 0,
-                                minsize, maxsize);
+                                minsize, maxsize, /*max_results=*/ 0);
   igraph_vector_int_destroy(&subset);
   IGRAPH_FINALLY_CLEAN(1);
 
@@ -6574,7 +6510,7 @@ SEXP R_igraph_maximal_cliques_file(SEXP graph, SEXP psubset, SEXP file,
                                 __LINE__, IGRAPH_EFILE); }
   igraph_maximal_cliques_subset(&g, Rf_isNull(psubset) ? 0 : &subset,
                                 /*ptr=*/ 0, /*no=*/ 0, /*file=*/ stream,
-                                minsize, maxsize);
+                                minsize, maxsize, /*max_results=*/ 0);
   fclose(stream);
   igraph_vector_int_destroy(&subset);
   IGRAPH_FINALLY_CLEAN(1);
@@ -6614,7 +6550,7 @@ SEXP R_igraph_maximal_cliques_count(SEXP graph, SEXP psubset,
                                         /* Call igraph */
   igraph_maximal_cliques_subset(&c_graph, Rf_isNull(psubset) ? 0 : &subset,
                                 /*ptr=*/ 0, &c_no, /*file=*/ 0,
-                                c_min_size, c_max_size);
+                                c_min_size, c_max_size, /*max_results=*/ 0);
 
   igraph_vector_int_destroy(&subset);
   IGRAPH_FINALLY_CLEAN(1);
@@ -6637,7 +6573,7 @@ SEXP R_igraph_independent_vertex_sets(SEXP graph,
 
   R_SEXP_to_igraph(graph, &g);
   igraph_vector_int_list_init(&list, 0);
-  IGRAPH_R_CHECK(igraph_independent_vertex_sets(&g, &list, minsize, maxsize));
+  IGRAPH_R_CHECK(igraph_independent_vertex_sets(&g, &list, minsize, maxsize, /*max_results=*/ 0));
   PROTECT(result=R_igraph_vector_int_list_to_SEXP(&list));
   igraph_vector_int_list_destroy(&list);
 
@@ -6667,7 +6603,7 @@ SEXP R_igraph_maximal_independent_vertex_sets(SEXP graph) {
 
   R_SEXP_to_igraph(graph, &g);
   igraph_vector_int_list_init(&list,0);
-  IGRAPH_R_CHECK(igraph_maximal_independent_vertex_sets(&g, &list));
+  IGRAPH_R_CHECK(igraph_maximal_independent_vertex_sets(&g, &list, /*min_size=*/ 0, /*max_size=*/ 0, /*max_results=*/ 0));
   PROTECT(result=R_igraph_vector_int_list_to_SEXP(&list));
   igraph_vector_int_list_destroy(&list);
 
@@ -6861,7 +6797,9 @@ SEXP R_igraph_community_edge_betweenness(SEXP graph, SEXP pweights,
     ppmembership=&membership;
     igraph_vector_int_init(&membership, 0);
   }
-  IGRAPH_R_CHECK(igraph_community_edge_betweenness(&g, &res, ppeb, ppmerges, ppbridges, ppmodularity, ppmembership, directed, ppweights));
+  // FIXME: expose
+  igraph_vector_t *pplengths = NULL;
+  IGRAPH_R_CHECK(igraph_community_edge_betweenness(&g, &res, ppeb, ppmerges, ppbridges, ppmodularity, ppmembership, directed, ppweights, pplengths));
 
   PROTECT(result=NEW_LIST(6));
   SET_VECTOR_ELT(result, 0, R_igraph_vector_int_to_SEXP(&res));
@@ -7043,15 +6981,15 @@ SEXP R_igraph_get_adjlist(SEXP graph, SEXP pmode, SEXP ploops, SEXP pmultiple) {
   SEXP result;
   igraph_integer_t no_of_nodes;
   igraph_vector_int_t neis;
-  igraph_integer_t loops=(igraph_integer_t) REAL(ploops)[0];
-  igraph_integer_t multiple=(igraph_integer_t) REAL(pmultiple)[0];
+  igraph_loops_t loops=(igraph_loops_t) REAL(ploops)[0];
+  igraph_bool_t multiple=(igraph_bool_t) REAL(pmultiple)[0];
 
   R_SEXP_to_igraph(graph, &g);
   no_of_nodes=igraph_vcount(&g);
   igraph_vector_int_init(&neis, 0);
   PROTECT(result=NEW_LIST(no_of_nodes));
   for (igraph_integer_t i=0; i<no_of_nodes; i++) {
-    igraph_i_neighbors(&g, &neis, i, mode, (igraph_loops_t) loops, (igraph_multiple_t) multiple);
+    igraph_neighbors(&g, &neis, i, mode, loops, multiple);
     SET_VECTOR_ELT(result, i, R_igraph_vector_int_to_SEXP(&neis));
   }
   igraph_vector_int_destroy(&neis);
@@ -7067,14 +7005,14 @@ SEXP R_igraph_get_adjedgelist(SEXP graph, SEXP pmode, SEXP ploops) {
   SEXP result;
   igraph_integer_t no_of_nodes;
   igraph_vector_int_t neis;
-  igraph_integer_t loops=(igraph_integer_t) REAL(ploops)[0];
+  igraph_bool_t loops=(igraph_bool_t) REAL(ploops)[0];
 
   R_SEXP_to_igraph(graph, &g);
   no_of_nodes=igraph_vcount(&g);
   igraph_vector_int_init(&neis, 0);
   PROTECT(result=NEW_LIST(no_of_nodes));
   for (igraph_integer_t i=0; i<no_of_nodes; i++) {
-    igraph_i_incident(&g, &neis, (igraph_integer_t) i, mode, (igraph_loops_t) loops);
+    igraph_incident(&g, &neis, i, mode, loops);
     SET_VECTOR_ELT(result, i, R_igraph_vector_int_to_SEXP(&neis));
   }
   igraph_vector_int_destroy(&neis);
@@ -7650,7 +7588,7 @@ SEXP R_igraph_community_leading_eigenvector(SEXP graph, SEXP steps,
   igraph_real_t c_modularity;
   igraph_vector_t c_eigenvalues;
   igraph_vector_list_t c_eigenvectors;
-  igraph_vector_t c_history;
+  igraph_vector_int_t c_history;
   SEXP merges;
   SEXP membership;
   SEXP modularity;
@@ -7668,7 +7606,7 @@ SEXP R_igraph_community_leading_eigenvector(SEXP graph, SEXP steps,
     pweights=&v_weights; R_SEXP_to_vector(weights, &v_weights);
   }
   if (0 != igraph_matrix_int_init(&c_merges, 0, 0)) {
-  igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
+    igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
   }
   IGRAPH_FINALLY(igraph_matrix_int_destroy, &c_merges);
   if (c_start) {
@@ -7682,13 +7620,13 @@ SEXP R_igraph_community_leading_eigenvector(SEXP graph, SEXP steps,
   c_steps=(igraph_integer_t) REAL(steps)[0];
   R_SEXP_to_igraph_arpack_options(options, &c_options);
   if (0 != igraph_vector_init(&c_eigenvalues, 0)) {
-  igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
+    igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
   }
   if (0 != igraph_vector_list_init(&c_eigenvectors, 0)) {
-  igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
+    igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
   }
-  if (0 != igraph_vector_init(&c_history, 0)) {
-  igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
+  if (0 != igraph_vector_int_init(&c_history, 0)) {
+    igraph_error("", __FILE__, __LINE__, IGRAPH_ENOMEM);
   }
                                         /* Call igraph */
   IGRAPH_R_CHECK(igraph_community_leading_eigenvector(&c_graph, pweights, &c_merges, &c_membership, c_steps, &c_options, &c_modularity, c_start, &c_eigenvalues, &c_eigenvectors, &c_history, Rf_isNull(callback) ? 0 : R_igraph_i_levc_callback, &callback_data));
@@ -7709,8 +7647,8 @@ SEXP R_igraph_community_leading_eigenvector(SEXP graph, SEXP steps,
   igraph_vector_destroy(&c_eigenvalues);
   PROTECT(eigenvectors=R_igraph_vector_list_to_SEXP(&c_eigenvectors));
   igraph_vector_list_destroy(&c_eigenvectors);
-  PROTECT(history=R_igraph_vector_to_SEXP(&c_history));
-  igraph_vector_destroy(&c_history);
+  PROTECT(history=R_igraph_vector_int_to_SEXP(&c_history));
+  igraph_vector_int_destroy(&c_history);
   SET_VECTOR_ELT(result, 0, merges);
   SET_VECTOR_ELT(result, 1, membership);
   SET_VECTOR_ELT(result, 2, options);
@@ -7767,7 +7705,6 @@ SEXP R_igraph_subisomorphic_lad(SEXP pattern, SEXP target, SEXP domains,
   igraph_vector_int_t c_map;
   igraph_vector_int_list_t c_maps;
   igraph_bool_t c_induced;
-  igraph_integer_t c_time_limit;
   igraph_bool_t c_qmap;
   igraph_bool_t c_qall_maps;
   SEXP iso;
@@ -7809,9 +7746,9 @@ SEXP R_igraph_subisomorphic_lad(SEXP pattern, SEXP target, SEXP domains,
   }
 
   c_induced=LOGICAL(induced)[0];
-  c_time_limit=(igraph_integer_t) REAL(time_limit)[0];
+  // FIXME: Deprecate time_limit
                                         /* Call igraph */
-  IGRAPH_R_CHECK(igraph_subisomorphic_lad(&c_pattern, &c_target, (Rf_isNull(domains) ? 0 : &c_domains), &c_iso, (Rf_isNull(map) ? 0 : &c_map), (Rf_isNull(maps) ? 0 : &c_maps), c_induced, c_time_limit));
+  IGRAPH_R_CHECK(igraph_subisomorphic_lad(&c_pattern, &c_target, (Rf_isNull(domains) ? 0 : &c_domains), &c_iso, (Rf_isNull(map) ? 0 : &c_map), (Rf_isNull(maps) ? 0 : &c_maps), c_induced));
 
                                         /* Convert output */
   igraph_vector_int_list_destroy(&c_domains);
@@ -8515,27 +8452,6 @@ int igraphhcass2(int n, const int *ia, const int *ib,
   return 0;
 } /* hcass2_ */
 
-SEXP R_igraph_get_all_simple_paths_pp(SEXP vector) {
-  SEXP result;
-  igraph_integer_t no=0, n=Rf_xlength(vector);
-  double *vec=REAL(vector), *p=vec, *pp=vec;
-  for (igraph_integer_t i=0; i<n; i++) {
-    if (vec[i] == 0) { no++; }
-  }
-
-  PROTECT(result=NEW_LIST(no));
-  for (igraph_integer_t i=0; i<no; i++) {
-    SEXP svec;
-    while (*p != 0) { p++; }
-    SET_VECTOR_ELT(result, i, svec=NEW_NUMERIC(p-pp));
-    memcpy(REAL(svec), pp, (p-pp) * sizeof(double));
-    pp = ++p;
-  }
-
-  UNPROTECT(1);
-  return result;
-}
-
 SEXP R_igraph_address(SEXP object) {
   char s[64];
   snprintf(s, 64, "%p", (void*) object);
@@ -8634,7 +8550,7 @@ SEXP R_igraph_add_env(SEXP graph) {
   // Get the emptyenv function
   SEXP empty_env_fun = PROTECT(Rf_findVarInFrame(base_ns, Rf_install("emptyenv"))); px++;
   // Call emptyenv()
-  SEXP empty_env = PROTECT(Rf_eval(PROTECT(Rf_lang1(empty_env_fun)), R_GlobalEnv)); px++; px++;
+  SEXP empty_env = PROTECT(Rf_eval(Rf_lang1(empty_env_fun), R_GlobalEnv)); px++;
   // Evaluate the call
   SEXP env = PROTECT(R_NewEnv(empty_env, 0, 0)); px++;
 
@@ -8662,3 +8578,27 @@ SEXP R_igraph_add_env(SEXP graph) {
 SEXP R_igraph_get_graph_id(SEXP graph) {
   return Rf_findVar(Rf_install("myid"), R_igraph_graph_env(graph));
 }
+
+igraph_error_t igraph_sample_sphere_surface(igraph_integer_t dim,
+                                            igraph_integer_t n,
+                                            igraph_real_t radius,
+                                            igraph_bool_t positive,
+                                            igraph_matrix_t *res) {
+  return igraph_rng_sample_sphere_surface(igraph_rng_default(), dim, n, radius,
+                                          positive, res);
+}
+
+igraph_error_t igraph_sample_sphere_volume(igraph_integer_t dim,
+                                           igraph_integer_t n,
+                                           igraph_real_t radius,
+                                           igraph_bool_t positive,
+                                           igraph_matrix_t *res) {
+  return igraph_rng_sample_sphere_volume(igraph_rng_default(), dim, n, radius,
+                                         positive, res);
+}
+
+igraph_error_t igraph_sample_dirichlet(igraph_integer_t n,
+                                       const igraph_vector_t *alpha,
+                                       igraph_matrix_t *res) {
+  return igraph_rng_sample_dirichlet(igraph_rng_default(), n, alpha, res);
+}
diff --git a/tests/testthat/_snaps/aaa-auto.md b/tests/testthat/_snaps/aaa-auto.md
index b820114a9e0..27225b3a2d1 100644
--- a/tests/testthat/_snaps/aaa-auto.md
+++ b/tests/testthat/_snaps/aaa-auto.md
@@ -55,30 +55,6 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# delete_vertices_idx_impl basic
-
-    Code
-      delete_vertices_idx_impl(g, 1)
-    Output
-      $graph
-      IGRAPH D--- 2 0 -- 
-      + edges:
-      
-      $idx
-      [1] 0 1 2
-      
-      $invidx
-      [1] 1 2
-      
-
-# delete_vertices_idx_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
 # vcount_impl basic
 
     Code
@@ -500,25 +476,6 @@
       Error in `kautz_impl()`:
       ! At vendor/cigraph/src/constructors/kautz.c:xx : `m' and `n' should be non-negative in a Kautz graph, Invalid value
 
-# lcf_vector_impl basic
-
-    Code
-      lcf_vector_impl(10, c(3, -3, 4), 2)
-    Output
-      IGRAPH U--- 10 16 -- LCF graph
-      + attr: name (g/c)
-      + edges:
-       [1] 1-- 2 1-- 4 1--10 2-- 3 2-- 5 2-- 9 3-- 4 3-- 7 4-- 5 4-- 7 5-- 6 6-- 7
-      [13] 6--10 7-- 8 8-- 9 9--10
-
-# lcf_vector_impl errors
-
-    Code
-      x
-    Condition
-      Error in `lcf_vector_impl()`:
-      ! At vendor/cigraph/src/graph/type_indexededgelist.c:xx : Number of vertices must not be negative. Invalid value
-
 # mycielski_graph_impl basic
 
     Code
@@ -636,7 +593,7 @@
       + attr: name (g/c), out.deg (g/n), in.deg (g/x), allowed.edge.types
       | (g/n), method (g/n)
       + edges:
-      [1] 2--3 1--3 1--2
+      [1] 1--3 2--3 1--2
 
 ---
 
@@ -779,7 +736,7 @@
       x
     Condition
       Error in `erdos_renyi_game_gnp_impl()`:
-      ! At vendor/cigraph/src/games/erdos_renyi.c:xx : Invalid number of vertices. Invalid value
+      ! At vendor/cigraph/src/games/erdos_renyi.c:xx : Invalid number of vertices for G(n,p) model. Invalid value
 
 # erdos_renyi_game_gnm_impl basic
 
@@ -805,7 +762,7 @@
       x
     Condition
       Error in `erdos_renyi_game_gnm_impl()`:
-      ! At vendor/cigraph/src/games/erdos_renyi.c:xx : Invalid number of vertices. Invalid value
+      ! At vendor/cigraph/src/games/erdos_renyi.c:xx : Invalid number of vertices for G(n,m) model. Invalid value
 
 # growing_random_game_impl basic
 
@@ -951,11 +908,11 @@
     Code
       simple_interconnected_islands_game_impl(2, 3, 0.5, 1)
     Output
-      IGRAPH U--- 6 5 -- Interconnected islands model
+      IGRAPH U--- 6 6 -- Interconnected islands model
       + attr: name (g/c), islands.n (g/n), islands.size (g/n), islands.pin
       | (g/n), n.inter (g/n)
       + edges:
-      [1] 1--2 1--3 2--3 3--6 5--6
+      [1] 1--2 1--3 2--3 2--6 4--5 4--6
 
 # simple_interconnected_islands_game_impl errors
 
@@ -1209,7 +1166,7 @@
       x
     Condition
       Error in `correlated_pair_game_impl()`:
-      ! At vendor/cigraph/src/games/erdos_renyi.c:xx : Invalid number of vertices. Invalid value
+      ! At vendor/cigraph/src/games/erdos_renyi.c:xx : Invalid number of vertices for G(n,p) model. Invalid value
 
 # dot_product_game_impl basic
 
@@ -1217,7 +1174,7 @@
       dot_product_game_impl(matrix(0.5, 5, 2))
     Condition
       Warning in `dot_product_game_impl()`:
-      At vendor/cigraph/src/games/dotproduct.c:90 : Greater than 1 connection probability in dot-product graph.
+      At vendor/cigraph/src/games/dotproduct.c:86 : Greater than 1 connection probability in dot-product graph.
     Output
       IGRAPH U--- 2 1 -- 
       + edge:
@@ -1229,7 +1186,7 @@
       dot_product_game_impl(matrix(0.5, 5, 2), directed = TRUE)
     Condition
       Warning in `dot_product_game_impl()`:
-      At vendor/cigraph/src/games/dotproduct.c:90 : Greater than 1 connection probability in dot-product graph.
+      At vendor/cigraph/src/games/dotproduct.c:86 : Greater than 1 connection probability in dot-product graph.
     Output
       IGRAPH D--- 2 2 -- 
       + edges:
@@ -1243,80 +1200,6 @@
       Error in `dot_product_game_impl()`:
       ! REAL() can only be applied to a 'numeric', not a 'NULL'
 
-# sample_sphere_surface_impl basic
-
-    Code
-      sample_sphere_surface_impl(3, 5)
-    Output
-                 [,1]      [,2]      [,3]      [,4]       [,5]
-      [1,] 0.87877523 0.8206548 0.1430028 0.6349227 0.99933629
-      [2,] 0.05165973 0.5261159 0.1145481 0.2979741 0.02649327
-      [3,] 0.47443162 0.2229974 0.9830712 0.7128005 0.02500179
-
----
-
-    Code
-      sample_sphere_surface_impl(3, 5, radius = 2, positive = FALSE)
-    Output
-                 [,1]       [,2]       [,3]        [,4]     [,5]
-      [1,] -0.4904253 -1.4825368 -0.5141332  1.95644246 0.369407
-      [2,] -1.6787252  1.1329528 -0.7872709 -0.41498660 1.953509
-      [3,] -0.9702395  0.7200713  1.7651832 -0.01090904 0.217584
-
-# sample_sphere_surface_impl errors
-
-    Code
-      x
-    Condition
-      Error in `sample_sphere_surface_impl()`:
-      ! At vendor/cigraph/src/games/dotproduct.c:xx : Sphere must be at least two dimensional to sample from surface. Invalid value
-
-# sample_sphere_volume_impl basic
-
-    Code
-      sample_sphere_volume_impl(3, 5)
-    Output
-                 [,1]      [,2]       [,3]      [,4]       [,5]
-      [1,] 0.67165090 0.6105364 0.09806950 0.4132698 0.73325518
-      [2,] 0.03948371 0.3914105 0.07855561 0.1939507 0.01943923
-      [3,] 0.36260970 0.1659017 0.67417787 0.4639603 0.01834487
-
----
-
-    Code
-      sample_sphere_volume_impl(3, 5, radius = 2, positive = FALSE)
-    Output
-                   [,1]       [,2]       [,3]      [,4]       [,5]
-      [1,]  1.903629152 -1.3795904 -1.2061886 0.9035986 -1.1692436
-      [2,] -0.159619927  0.2402815 -0.1258477 0.1842403 -1.4940836
-      [3,]  0.003829883  1.2440192  0.6204597 1.5776103  0.4096058
-
-# sample_sphere_volume_impl errors
-
-    Code
-      x
-    Condition
-      Error in `sample_sphere_volume_impl()`:
-      ! At vendor/cigraph/src/games/dotproduct.c:xx : Sphere must be at least two dimensional to sample from surface. Invalid value
-
-# sample_dirichlet_impl basic
-
-    Code
-      sample_dirichlet_impl(5, c(1, 1, 1))
-    Output
-                [,1]      [,2]       [,3]      [,4]      [,5]
-      [1,] 0.6298008 0.4168413 0.29594281 0.2432340 0.1516815
-      [2,] 0.1093984 0.3461600 0.08924333 0.4251328 0.3561426
-      [3,] 0.2608008 0.2369988 0.61481386 0.3316331 0.4921759
-
-# sample_dirichlet_impl errors
-
-    Code
-      x
-    Condition
-      Error in `sample_dirichlet_impl()`:
-      ! At vendor/cigraph/src/games/dotproduct.c:xx : Number of samples should be non-negative, got -1. Invalid value
-
 # are_adjacent_impl basic
 
     Code
@@ -1411,7 +1294,7 @@
 # get_shortest_path_impl basic
 
     Code
-      get_shortest_path_impl(g, 1, 3)
+      get_shortest_path_impl(g, from = 1, to = 3)
     Output
       $vertices
       + 3/3 vertices:
@@ -1477,7 +1360,7 @@
 # get_all_shortest_paths_impl basic
 
     Code
-      get_all_shortest_paths_impl(g, 1, 3)
+      get_all_shortest_paths_impl(g, from = 1, to = 3)
     Output
       $vpaths
       $vpaths[[1]]
@@ -2133,7 +2016,7 @@
       transitivity_barrat_impl(g)
     Condition
       Warning in `transitivity_barrat_impl()`:
-      At vendor/cigraph/src/properties/triangles.c:913 : No weights given for Barrat's transitivity, unweighted version is used.
+      At vendor/cigraph/src/properties/triangles.c:889 : No weights given for Barrat's transitivity, unweighted version is used.
     Output
       [1] NaN   0 NaN
 
@@ -2143,7 +2026,7 @@
       transitivity_barrat_impl(g, mode = "zero")
     Condition
       Warning in `transitivity_barrat_impl()`:
-      At vendor/cigraph/src/properties/triangles.c:913 : No weights given for Barrat's transitivity, unweighted version is used.
+      At vendor/cigraph/src/properties/triangles.c:889 : No weights given for Barrat's transitivity, unweighted version is used.
     Output
       [1] 0 0 0
 
@@ -2209,7 +2092,7 @@
 ---
 
     Code
-      maxdegree_impl(g, mode = "in", loops = FALSE)
+      maxdegree_impl(g, mode = "in", loops = "twice")
     Output
       [1] 2
 
@@ -2529,10 +2412,10 @@
 ---
 
     Code
-      eigenvector_centrality_impl(g, directed = TRUE, scale = FALSE)
+      eigenvector_centrality_impl(g, mode = "out")
     Output
       $vector
-      [1] 0.5000000 0.7071068 0.5000000
+      [1] 0.7071068 1.0000000 0.7071068
       
       $value
       [1] 1.414214
@@ -2611,7 +2494,7 @@
 # hub_and_authority_scores_impl basic
 
     Code
-      hub_and_authority_scores_impl(g)
+      suppressWarnings(hub_and_authority_scores_impl(g))
     Output
       $hub
       [1] 1 1 1 1 1
@@ -2685,83 +2568,6 @@
       
       
 
----
-
-    Code
-      hub_and_authority_scores_impl(g, scale = FALSE)
-    Output
-      $hub
-      [1] 0.4472136 0.4472136 0.4472136 0.4472136 0.4472136
-      
-      $authority
-      [1] 0.4472136 0.4472136 0.4472136 0.4472136 0.4472136
-      
-      $value
-      [1] 16
-      
-      $options
-      $options$bmat
-      [1] "I"
-      
-      $options$n
-      [1] 5
-      
-      $options$which
-      [1] "LA"
-      
-      $options$nev
-      [1] 1
-      
-      $options$tol
-      [1] 0
-      
-      $options$ncv
-      [1] 0
-      
-      $options$ldv
-      [1] 0
-      
-      $options$ishift
-      [1] 1
-      
-      $options$maxiter
-      [1] 3000
-      
-      $options$nb
-      [1] 1
-      
-      $options$mode
-      [1] 1
-      
-      $options$start
-      [1] 1
-      
-      $options$sigma
-      [1] 0
-      
-      $options$sigmai
-      [1] 0
-      
-      $options$info
-      [1] 0
-      
-      $options$iter
-      [1] 1
-      
-      $options$nconv
-      [1] 1
-      
-      $options$numop
-      [1] 4
-      
-      $options$numopb
-      [1] 0
-      
-      $options$numreo
-      [1] 4
-      
-      
-
 # hub_and_authority_scores_impl errors
 
     Code
@@ -2959,7 +2765,7 @@
 ---
 
     Code
-      strength_impl(g, mode = "in", loops = FALSE)
+      strength_impl(g, mode = "in", loops = "twice")
     Output
       [1] 1 2 1
 
@@ -3011,7 +2817,7 @@
 ---
 
     Code
-      centralization_degree_impl(g, mode = "in", loops = FALSE, normalized = FALSE)
+      centralization_degree_impl(g, mode = "in", loops = "twice", normalized = FALSE)
     Output
       $res
       [1] 1 2 1
@@ -3031,28 +2837,6 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# centralization_degree_tmax_impl basic
-
-    Code
-      centralization_degree_tmax_impl(nodes = 3, loops = TRUE)
-    Output
-      [1] 6
-
----
-
-    Code
-      centralization_degree_tmax_impl(nodes = 3, mode = "in", loops = FALSE)
-    Output
-      [1] 4
-
-# centralization_degree_tmax_impl errors
-
-    Code
-      x
-    Condition
-      Error in `centralization_degree_tmax_impl()`:
-      ! At vendor/cigraph/src/centrality/centralization.c:xx : Number of vertices must not be negative. Invalid value
-
 # centralization_betweenness_impl basic
 
     Code
@@ -3256,7 +3040,7 @@
 ---
 
     Code
-      centralization_eigenvector_centrality_impl(g, directed = TRUE, normalized = FALSE)
+      centralization_eigenvector_centrality_impl(g, mode = "out", normalized = FALSE)
     Output
       $vector
       [1] 0.7071068 1.0000000 0.7071068
@@ -3346,12 +3130,12 @@
     Code
       centralization_eigenvector_centrality_tmax_impl(nodes = 3)
     Output
-      [1] 1
+      [1] 2
 
 ---
 
     Code
-      centralization_eigenvector_centrality_tmax_impl(nodes = 3, directed = TRUE)
+      centralization_eigenvector_centrality_tmax_impl(nodes = 3, mode = "out")
     Output
       [1] 2
 
@@ -3529,78 +3313,10 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# eccentricity_dijkstra_impl basic
-
-    Code
-      eccentricity_dijkstra_impl(g)
-    Output
-      [1] 2 1 2
-
----
-
-    Code
-      eccentricity_dijkstra_impl(g, mode = "in")
-    Output
-      [1] 2 1 2
-
-# eccentricity_dijkstra_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
-# graph_center_dijkstra_impl basic
-
-    Code
-      graph_center_dijkstra_impl(g)
-    Output
-      + 1/3 vertex:
-      [1] 2
-
----
-
-    Code
-      graph_center_dijkstra_impl(g, mode = "in")
-    Output
-      + 1/3 vertex:
-      [1] 2
-
-# graph_center_dijkstra_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
-# radius_dijkstra_impl basic
-
-    Code
-      radius_dijkstra_impl(g)
-    Output
-      [1] 1
-
----
-
-    Code
-      radius_dijkstra_impl(g, mode = "in")
-    Output
-      [1] 1
-
-# radius_dijkstra_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
 # pseudo_diameter_impl basic
 
     Code
-      pseudo_diameter_impl(g, 1)
+      pseudo_diameter_impl(g, start.vid = 1)
     Output
       $diameter
       [1] 2
@@ -3615,7 +3331,7 @@
 ---
 
     Code
-      pseudo_diameter_impl(g, 1, directed = FALSE, unconnected = FALSE)
+      pseudo_diameter_impl(g, start.vid = 1, directed = FALSE, unconnected = FALSE)
     Output
       $diameter
       [1] 2
@@ -3635,44 +3351,6 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# pseudo_diameter_dijkstra_impl basic
-
-    Code
-      pseudo_diameter_dijkstra_impl(g, start.vid = 1)
-    Output
-      $diameter
-      [1] 2
-      
-      $from
-      [1] 0
-      
-      $to
-      [1] 2
-      
-
----
-
-    Code
-      pseudo_diameter_dijkstra_impl(g, start.vid = 1, directed = FALSE, unconnected = FALSE)
-    Output
-      $diameter
-      [1] 2
-      
-      $from
-      [1] 0
-      
-      $to
-      [1] 2
-      
-
-# pseudo_diameter_dijkstra_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
 # diversity_impl basic
 
     Code
@@ -3790,23 +3468,6 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# transitive_closure_dag_impl basic
-
-    Code
-      transitive_closure_dag_impl(g)
-    Output
-      IGRAPH D--- 3 3 -- 
-      + edges:
-      [1] 1->3 1->2 2->3
-
-# transitive_closure_dag_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
 # transitive_closure_impl basic
 
     Code
@@ -4045,7 +3706,7 @@
       x
     Condition
       Error in `bipartite_game_gnp_impl()`:
-      ! At vendor/cigraph/src/misc/bipartite.c:xx : Invalid number of vertices for bipartite graph. Invalid value
+      ! At vendor/cigraph/src/misc/bipartite.c:xx : Invalid number of vertices for bipartite G(n,p) model. Invalid value
 
 # bipartite_game_gnm_impl basic
 
@@ -4081,7 +3742,7 @@
       x
     Condition
       Error in `bipartite_game_gnm_impl()`:
-      ! At vendor/cigraph/src/misc/bipartite.c:xx : Invalid number of vertices for bipartite graph. Invalid value
+      ! At vendor/cigraph/src/misc/bipartite.c:xx : Invalid number of vertices for bipartite G(n,m) model. Invalid value
 
 # get_laplacian_impl basic
 
@@ -5120,7 +4781,7 @@
 ---
 
     Code
-      similarity_dice_impl(g, vids = 1:2, mode = "in", loops = TRUE)
+      similarity_dice_impl(g, vit.from = 1:2, mode = "in", loops = TRUE)
     Output
            [,1] [,2]
       [1,]  1.0  0.8
@@ -5219,7 +4880,7 @@
 ---
 
     Code
-      similarity_jaccard_impl(g, vids = 1:2, mode = "in", loops = TRUE)
+      similarity_jaccard_impl(g, vit.from = 1:2, mode = "in", loops = TRUE)
     Output
                 [,1]      [,2]
       [1,] 1.0000000 0.6666667
@@ -5371,7 +5032,7 @@
 # community_label_propagation_impl basic
 
     Code
-      community_label_propagation_impl(g)
+      community_label_propagation_impl(g, lpa.variant = "dominance")
     Output
       [1] 0 0 0
 
@@ -5379,7 +5040,7 @@
 
     Code
       community_label_propagation_impl(g, mode = "in", weights = c(1, 2), initial = 1:
-        3, fixed = c(TRUE, FALSE, TRUE))
+        3, fixed = c(TRUE, FALSE, TRUE), lpa.variant = "retention")
     Output
       [1] 0 1 1
 
@@ -5466,7 +5127,7 @@
 # community_leiden_impl basic
 
     Code
-      community_leiden_impl(g, weights = c(1, 2), vertex.weights = c(1, 2, 3),
+      community_leiden_impl(g, weights = c(1, 2), vertex.out.weights = c(1, 2, 3),
       resolution = 0.5, beta = 0.1, start = TRUE, n.iterations = 1, membership = 1:3)
     Output
       $membership
@@ -5524,7 +5185,7 @@
 ---
 
     Code
-      community_infomap_impl(g, e.weights = c(1, 2), v.weights = c(1, 2, 3),
+      community_infomap_impl(g, edge.weights = c(1, 2), vertex.weights = c(1, 2, 3),
       nb.trials = 2)
     Output
       $membership
@@ -6075,7 +5736,7 @@
       triad_census_impl(g)
     Condition
       Warning in `triad_census_impl()`:
-      At vendor/cigraph/src/misc/motifs.c:1157 : Triad census called on an undirected graph. All connections will be treated as mutual.
+      At vendor/cigraph/src/misc/motifs.c:1170 : Triad census called on an undirected graph. All connections will be treated as mutual.
     Output
        [1] 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
 
@@ -7188,7 +6849,7 @@
 ---
 
     Code
-      canonical_permutation_impl(g, colors = c(1, 2, 3), sh = "fl")
+      canonical_permutation_impl(g, colors = c(1, 2, 3))
     Output
       $labeling
       [1] 1 2 3
@@ -7384,7 +7045,7 @@
 ---
 
     Code
-      count_automorphisms_impl(g, colors = c(1, 2, 3), sh = "fl")
+      count_automorphisms_impl(g, colors = c(1, 2, 3))
     Output
       $nof_nodes
       [1] 1
@@ -7426,7 +7087,7 @@
 ---
 
     Code
-      automorphism_group_impl(g, colors = c(1, 2, 3), sh = "fl", details = TRUE)
+      automorphism_group_impl(g, colors = c(1, 2, 3))
     Output
       $generators
       list()
@@ -9452,30 +9113,6 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# convex_hull_2d_impl basic
-
-    Code
-      convex_hull_2d_impl(matrix(1:6, ncol = 2))
-    Output
-      $resverts
-      [1] 1 3
-      
-      $rescoords
-           [,1] [,2]
-      [1,]    1    4
-      [2,]    3    6
-      
-
-# convex_hull_2d_impl errors
-
-    Code
-      x
-    Condition
-      Warning in `convex_hull_2d_impl()`:
-      NAs introduced by coercion
-      Error in `convex_hull_2d_impl()`:
-      ! REAL() can only be applied to a 'numeric', not a 'character'
-
 # dim_select_impl basic
 
     Code
@@ -9941,99 +9578,6 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# deterministic_optimal_imitation_impl basic
-
-    Code
-      deterministic_optimal_imitation_impl(g, 1, quantities = c(1, 2, 3), strategies = c(
-        1, 2, 3))
-    Output
-      [1] 2 2 3
-
----
-
-    Code
-      deterministic_optimal_imitation_impl(g, 1, optimality = "minimum", quantities = c(
-        1, 2, 3), strategies = c(1, 2, 3), mode = "in")
-    Output
-      [1] 1 2 3
-
-# deterministic_optimal_imitation_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
-# moran_process_impl basic
-
-    Code
-      moran_process_impl(g, weights = c(1, 1), quantities = c(1, 2, 3), strategies = c(
-        1, 2, 3), mode = "in")
-    Output
-      $quantities
-      [1] 1 3 3
-      
-      $strategies
-      [1] 1 3 3
-      
-
-# moran_process_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
-# roulette_wheel_imitation_impl basic
-
-    Code
-      roulette_wheel_imitation_impl(g, 1, TRUE, quantities = c(1, 2, 3), strategies = c(
-        1, 2, 3))
-    Output
-      [1] 1 2 3
-
----
-
-    Code
-      roulette_wheel_imitation_impl(g, 1, FALSE, quantities = c(1, 2, 3), strategies = c(
-        1, 2, 3), mode = "in")
-    Output
-      [1] 3 2 3
-
-# roulette_wheel_imitation_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
-# stochastic_imitation_impl basic
-
-    Code
-      stochastic_imitation_impl(g, 1, algo = 1, quantities = c(1, 2, 3), strategies = c(
-        1, 2, 3))
-    Output
-      [1] 1 2 3
-
----
-
-    Code
-      stochastic_imitation_impl(g, 1, algo = 2, quantities = c(1, 2, 3), strategies = c(
-        1, 2, 3), mode = "in")
-    Output
-      [1] 1 2 3
-
-# stochastic_imitation_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
 # invalidate_cache_impl basic
 
     Code
@@ -10051,36 +9595,12 @@
       Error in `ensure_igraph()`:
       ! Must provide a graph object (provided `NULL`).
 
-# vertex_path_from_edge_path_impl basic
-
-    Code
-      vertex_path_from_edge_path_impl(g, start = 1, edge.path = c(1, 2))
-    Output
-      + 3/3 vertices:
-      [1] 1 2 3
-
----
-
-    Code
-      vertex_path_from_edge_path_impl(g, start = 1, edge.path = c(1), mode = "in")
-    Output
-      + 2/3 vertices:
-      [1] 1 2
-
-# vertex_path_from_edge_path_impl errors
-
-    Code
-      x
-    Condition
-      Error in `ensure_igraph()`:
-      ! Must provide a graph object (provided `NULL`).
-
 # version_impl basic
 
     Code
       version_impl_clean()
     Output
-      [1] "0.10.17"
+      [1] "1.0.0"
 
 # version_impl errors
 
diff --git a/tests/testthat/_snaps/centrality.md b/tests/testthat/_snaps/centrality.md
index 62a6c46264f..febfd202987 100644
--- a/tests/testthat/_snaps/centrality.md
+++ b/tests/testthat/_snaps/centrality.md
@@ -10,6 +10,9 @@
       arpack_defaults was deprecated in igraph 1.6.0.
       i Please use `arpack_defaults()` instead.
       i So the function arpack_defaults(), not an object called arpack_defaults.
+      Warning:
+      The `scale` argument of `hits_scores()` is deprecated as of igraph 2.1.5.
+      i The function always behaves as if `scale = TRUE`. The argument will be removed in the future.
 
 # `hub_score()` works
 
@@ -23,6 +26,9 @@
       arpack_defaults was deprecated in igraph 1.6.0.
       i Please use `arpack_defaults()` instead.
       i So the function arpack_defaults(), not an object called arpack_defaults.
+      Warning:
+      The `scale` argument of `hits_scores()` is deprecated as of igraph 2.1.5.
+      i The function always behaves as if `scale = TRUE`. The argument will be removed in the future.
 
 # eigen_centrality() deprecated scale argument
 
@@ -48,7 +54,7 @@
       arpack(f, options = list(nev = 2, ncv = 4), sym = TRUE)
     Condition
       Error in `arpack()`:
-      ! At vendor/cigraph/src/linalg/arpack.c:1102 : ARPACK error, N must be positive
+      ! At vendor/cigraph/src/linalg/arpack.c:1025 : N must be positive, ARPACK error
 
 ---
 
diff --git a/tests/testthat/_snaps/incidence.md b/tests/testthat/_snaps/incidence.md
index dbb1ba9a91e..541b8034a6d 100644
--- a/tests/testthat/_snaps/incidence.md
+++ b/tests/testthat/_snaps/incidence.md
@@ -6,7 +6,7 @@
       IGRAPH UN-B 8 7 -- 
       + attr: type (v/l), name (v/c)
       + edges (vertex names):
-      [1] A--c A--d B--b B--c B--e C--b C--d
+      [1] B--b C--b A--c B--c A--d C--d B--e
 
 ---
 
@@ -26,7 +26,7 @@
       IGRAPH UN-B 8 10 -- 
       + attr: type (v/l), name (v/c)
       + edges (vertex names):
-       [1] A--c A--d A--d A--e B--b B--e C--b C--c C--c C--e
+       [1] B--b C--b A--c C--c C--c A--d A--d A--e B--e C--e
 
 # graph_from_biadjacency_matrix() works -- sparse
 
diff --git a/tests/testthat/_snaps/interface.md b/tests/testthat/_snaps/interface.md
index d394032f7a6..1c13eac2c5e 100644
--- a/tests/testthat/_snaps/interface.md
+++ b/tests/testthat/_snaps/interface.md
@@ -33,3 +33,21 @@
       Error in `el_to_vec()`:
       ! The columns of the data.frame are of different type (character and double)
 
+# incident() works
+
+    Code
+      incident(g, 1)
+    Output
+      + 16/78 edges:
+       [1] 1-- 2 1-- 3 1-- 4 1-- 5 1-- 6 1-- 7 1-- 8 1-- 9 1--11 1--12 1--13 1--14
+      [13] 1--18 1--20 1--22 1--32
+
+---
+
+    Code
+      incident(g, 34)
+    Output
+      + 17/78 edges:
+       [1]  9--34 10--34 14--34 15--34 16--34 19--34 20--34 21--34 23--34 24--34
+      [11] 27--34 28--34 29--34 30--34 31--34 32--34 33--34
+
diff --git a/tests/testthat/_snaps/minimum.spanning.tree.md b/tests/testthat/_snaps/minimum.spanning.tree.md
index 9cdfaeb90d6..d14e5554966 100644
--- a/tests/testthat/_snaps/minimum.spanning.tree.md
+++ b/tests/testthat/_snaps/minimum.spanning.tree.md
@@ -4,5 +4,6 @@
       mst(g, algorithm = "undefined")
     Condition
       Error in `mst()`:
-      ! Invalid `algorithm`.
+      ! `algorithm` must be one of "automatic", "unweighted", "prim", or "kruskal", not "undefined".
+      i Did you mean "unweighted"?
 
diff --git a/tests/testthat/test-aaa-auto.R b/tests/testthat/test-aaa-auto.R
index b51a615c7b2..a6f6732b83a 100644
--- a/tests/testthat/test-aaa-auto.R
+++ b/tests/testthat/test-aaa-auto.R
@@ -43,21 +43,6 @@ test_that("copy_impl errors", {
   expect_snapshot_igraph_error(copy_impl(NULL))
 })
 
-# 4. delete_vertices_idx_impl
-
-test_that("delete_vertices_idx_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  g <- empty_impl(3)
-  expect_snapshot(delete_vertices_idx_impl(g, 1))
-})
-
-test_that("delete_vertices_idx_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(delete_vertices_idx_impl(NULL, 1))
-})
-
 # 5. vcount_impl
 
 test_that("vcount_impl basic", {
@@ -338,18 +323,6 @@ test_that("kautz_impl errors", {
   expect_snapshot_igraph_error(kautz_impl(-1, 3))
 })
 
-# 23. lcf_vector_impl
-test_that("lcf_vector_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot(lcf_vector_impl(10, c(3, -3, 4), 2))
-})
-test_that("lcf_vector_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(lcf_vector_impl(-1, c(3, -3, 4), 2))
-})
-
 # 24. mycielski_graph_impl
 test_that("mycielski_graph_impl basic", {
   withr::local_seed(20250909)
@@ -843,55 +816,6 @@ test_that("dot_product_game_impl errors", {
   expect_snapshot_igraph_error(dot_product_game_impl(NULL))
 })
 
-# 52. sample_sphere_surface_impl
-
-test_that("sample_sphere_surface_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot(sample_sphere_surface_impl(3, 5))
-  expect_snapshot(sample_sphere_surface_impl(
-    3,
-    5,
-    radius = 2,
-    positive = FALSE
-  ))
-})
-
-test_that("sample_sphere_surface_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(sample_sphere_surface_impl(-1, 5))
-})
-
-# 53. sample_sphere_volume_impl
-
-test_that("sample_sphere_volume_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot(sample_sphere_volume_impl(3, 5))
-  expect_snapshot(sample_sphere_volume_impl(3, 5, radius = 2, positive = FALSE))
-})
-
-test_that("sample_sphere_volume_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(sample_sphere_volume_impl(-1, 5))
-})
-
-# 54. sample_dirichlet_impl
-
-test_that("sample_dirichlet_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot(sample_dirichlet_impl(5, c(1, 1, 1)))
-})
-
-test_that("sample_dirichlet_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(sample_dirichlet_impl(-1, c(1, 1, 1)))
-})
-
 # 55. are_adjacent_impl
 
 test_that("are_adjacent_impl basic", {
@@ -950,13 +874,13 @@ test_that("get_shortest_path_impl basic", {
   withr::local_seed(20250909)
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
-  expect_snapshot(get_shortest_path_impl(g, 1, 3))
+  expect_snapshot(get_shortest_path_impl(g, from = 1, to = 3))
 })
 
 test_that("get_shortest_path_impl errors", {
   withr::local_seed(20250909)
   local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(get_shortest_path_impl(NULL, 1, 3))
+  expect_snapshot_igraph_error(get_shortest_path_impl(NULL, from = 1, to = 3))
 })
 
 # 59. get_shortest_path_bellman_ford_impl
@@ -995,13 +919,17 @@ test_that("get_all_shortest_paths_impl basic", {
   withr::local_seed(20250909)
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
-  expect_snapshot(get_all_shortest_paths_impl(g, 1, 3))
+  expect_snapshot(get_all_shortest_paths_impl(g, from = 1, to = 3))
 })
 
 test_that("get_all_shortest_paths_impl errors", {
   withr::local_seed(20250909)
   local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(get_all_shortest_paths_impl(NULL, 1, 3))
+  expect_snapshot_igraph_error(get_all_shortest_paths_impl(
+    NULL,
+    from = 1,
+    to = 3
+  ))
 })
 
 # 62. get_all_shortest_paths_dijkstra_impl
@@ -1431,7 +1359,7 @@ test_that("maxdegree_impl basic", {
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
   expect_snapshot(maxdegree_impl(g))
-  expect_snapshot(maxdegree_impl(g, mode = "in", loops = FALSE))
+  expect_snapshot(maxdegree_impl(g, mode = "in", loops = "twice"))
 })
 
 test_that("maxdegree_impl errors", {
@@ -1660,11 +1588,7 @@ test_that("eigenvector_centrality_impl basic", {
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
   expect_snapshot(eigenvector_centrality_impl(g))
-  expect_snapshot(eigenvector_centrality_impl(
-    g,
-    directed = TRUE,
-    scale = FALSE
-  ))
+  expect_snapshot(eigenvector_centrality_impl(g, mode = "out"))
 })
 
 test_that("eigenvector_centrality_impl errors", {
@@ -1679,8 +1603,7 @@ test_that("hub_and_authority_scores_impl basic", {
   withr::local_seed(20250909)
   local_igraph_options(print.id = FALSE)
   g <- make_full_graph(5)
-  expect_snapshot(hub_and_authority_scores_impl(g))
-  expect_snapshot(hub_and_authority_scores_impl(g, scale = FALSE))
+  expect_snapshot(suppressWarnings(hub_and_authority_scores_impl(g)))
 })
 
 test_that("hub_and_authority_scores_impl errors", {
@@ -1824,7 +1747,7 @@ test_that("strength_impl basic", {
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
   expect_snapshot(strength_impl(g))
-  expect_snapshot(strength_impl(g, mode = "in", loops = FALSE))
+  expect_snapshot(strength_impl(g, mode = "in", loops = "twice"))
 })
 
 test_that("strength_impl errors", {
@@ -1862,7 +1785,7 @@ test_that("centralization_degree_impl basic", {
   expect_snapshot(centralization_degree_impl(
     g,
     mode = "in",
-    loops = FALSE,
+    loops = "twice",
     normalized = FALSE
   ))
 })
@@ -1873,27 +1796,6 @@ test_that("centralization_degree_impl errors", {
   expect_snapshot_igraph_error(centralization_degree_impl(NULL))
 })
 
-# 136. centralization_degree_tmax_impl
-
-test_that("centralization_degree_tmax_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot(centralization_degree_tmax_impl(nodes = 3, loops = TRUE))
-  expect_snapshot(centralization_degree_tmax_impl(
-    nodes = 3,
-    mode = "in",
-    loops = FALSE
-  ))
-})
-
-test_that("centralization_degree_tmax_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(
-    centralization_degree_tmax_impl(nodes = -1, loops = TRUE)
-  )
-})
-
 # 137. centralization_betweenness_impl
 
 test_that("centralization_betweenness_impl basic", {
@@ -1981,7 +1883,7 @@ test_that("centralization_eigenvector_centrality_impl basic", {
   expect_snapshot(centralization_eigenvector_centrality_impl(g))
   expect_snapshot(centralization_eigenvector_centrality_impl(
     g,
-    directed = TRUE,
+    mode = "out",
     normalized = FALSE
   ))
 })
@@ -2002,7 +1904,7 @@ test_that("centralization_eigenvector_centrality_tmax_impl basic", {
   expect_snapshot(centralization_eigenvector_centrality_tmax_impl(nodes = 3))
   expect_snapshot(centralization_eigenvector_centrality_tmax_impl(
     nodes = 3,
-    directed = TRUE
+    mode = "out"
   ))
 })
 
@@ -2155,64 +2057,16 @@ test_that("contract_vertices_impl errors", {
   expect_snapshot_igraph_error(contract_vertices_impl(NULL, c(1, 1, 2)))
 })
 
-# 150. eccentricity_dijkstra_impl
-
-test_that("eccentricity_dijkstra_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(eccentricity_dijkstra_impl(g))
-  expect_snapshot(eccentricity_dijkstra_impl(g, mode = "in"))
-})
-
-test_that("eccentricity_dijkstra_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(eccentricity_dijkstra_impl(NULL))
-})
-
-# 151. graph_center_dijkstra_impl
-
-test_that("graph_center_dijkstra_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(graph_center_dijkstra_impl(g))
-  expect_snapshot(graph_center_dijkstra_impl(g, mode = "in"))
-})
-
-test_that("graph_center_dijkstra_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(graph_center_dijkstra_impl(NULL))
-})
-
-# 152. radius_dijkstra_impl
-
-test_that("radius_dijkstra_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(radius_dijkstra_impl(g))
-  expect_snapshot(radius_dijkstra_impl(g, mode = "in"))
-})
-
-test_that("radius_dijkstra_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(radius_dijkstra_impl(NULL))
-})
-
 # 153. pseudo_diameter_impl
 
 test_that("pseudo_diameter_impl basic", {
   withr::local_seed(20250909)
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
-  expect_snapshot(pseudo_diameter_impl(g, 1))
+  expect_snapshot(pseudo_diameter_impl(g, start.vid = 1))
   expect_snapshot(pseudo_diameter_impl(
     g,
-    1,
+    start.vid = 1,
     directed = FALSE,
     unconnected = FALSE
   ))
@@ -2224,29 +2078,6 @@ test_that("pseudo_diameter_impl errors", {
   expect_snapshot_igraph_error(pseudo_diameter_impl(NULL, 1))
 })
 
-# 154. pseudo_diameter_dijkstra_impl
-
-test_that("pseudo_diameter_dijkstra_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(pseudo_diameter_dijkstra_impl(g, start.vid = 1))
-  expect_snapshot(pseudo_diameter_dijkstra_impl(
-    g,
-    start.vid = 1,
-    directed = FALSE,
-    unconnected = FALSE
-  ))
-})
-
-test_that("pseudo_diameter_dijkstra_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(
-    pseudo_diameter_dijkstra_impl(NULL, start.vid = 1)
-  )
-})
-
 # 155. diversity_impl
 
 test_that("diversity_impl basic", {
@@ -2331,21 +2162,6 @@ test_that("average_local_efficiency_impl errors", {
   expect_snapshot_igraph_error(average_local_efficiency_impl(NULL))
 })
 
-# 160. transitive_closure_dag_impl
-
-test_that("transitive_closure_dag_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3, directed = TRUE)
-  expect_snapshot(transitive_closure_dag_impl(g))
-})
-
-test_that("transitive_closure_dag_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(transitive_closure_dag_impl(NULL))
-})
-
 # 161. transitive_closure_impl
 
 test_that("transitive_closure_impl basic", {
@@ -3234,7 +3050,7 @@ test_that("similarity_dice_impl basic", {
   expect_snapshot(similarity_dice_impl(g))
   expect_snapshot(similarity_dice_impl(
     g,
-    vids = 1:2,
+    vit.from = 1:2,
     mode = "in",
     loops = TRUE
   ))
@@ -3322,7 +3138,7 @@ test_that("similarity_jaccard_impl basic", {
   expect_snapshot(similarity_jaccard_impl(g))
   expect_snapshot(similarity_jaccard_impl(
     g,
-    vids = 1:2,
+    vit.from = 1:2,
     mode = "in",
     loops = TRUE
   ))
@@ -3466,13 +3282,17 @@ test_that("community_label_propagation_impl basic", {
   withr::local_seed(20250909)
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
-  expect_snapshot(community_label_propagation_impl(g))
+  expect_snapshot(community_label_propagation_impl(
+    g,
+    lpa.variant = "dominance"
+  ))
   expect_snapshot(community_label_propagation_impl(
     g,
     mode = "in",
     weights = c(1, 2),
     initial = 1:3,
-    fixed = c(TRUE, FALSE, TRUE)
+    fixed = c(TRUE, FALSE, TRUE),
+    lpa.variant = "retention"
   ))
 })
 
@@ -3527,7 +3347,7 @@ test_that("community_leiden_impl basic", {
   expect_snapshot(community_leiden_impl(
     g,
     weights = c(1, 2),
-    vertex.weights = c(1, 2, 3),
+    vertex.out.weights = c(1, 2, 3),
     resolution = 0.5,
     beta = 0.1,
     start = TRUE,
@@ -3565,8 +3385,8 @@ test_that("community_infomap_impl basic", {
   expect_snapshot(community_infomap_impl(g))
   expect_snapshot(community_infomap_impl(
     g,
-    e.weights = c(1, 2),
-    v.weights = c(1, 2, 3),
+    edge.weights = c(1, 2),
+    vertex.weights = c(1, 2, 3),
     nb.trials = 2
   ))
 })
@@ -4116,12 +3936,12 @@ test_that("local_scan_neighborhood_ecount_impl basic", {
   g <- path_graph_impl(4)
   expect_snapshot(local_scan_neighborhood_ecount_impl(
     g,
-    neighborhoods = list(1:2, 2:3, 2:4, 2)
+    neighborhoods = list(1:2 - 1, 2:3 - 1, 2:4 - 1, 2 - 1)
   ))
   expect_snapshot(local_scan_neighborhood_ecount_impl(
     g,
     weights = c(1, 2, 3),
-    neighborhoods = list(1:2, 1:3, 2:4, 1)
+    neighborhoods = list(1:2 - 1, 1:3 - 1, 2:4 - 1, 1 - 1)
   ))
 })
 
@@ -4715,7 +4535,7 @@ test_that("canonical_permutation_impl basic", {
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
   expect_snapshot(canonical_permutation_impl(g))
-  expect_snapshot(canonical_permutation_impl(g, colors = c(1, 2, 3), sh = "fl"))
+  expect_snapshot(canonical_permutation_impl(g, colors = c(1, 2, 3)))
 })
 
 test_that("canonical_permutation_impl errors", {
@@ -4769,7 +4589,7 @@ test_that("count_automorphisms_impl basic", {
   local_igraph_options(print.id = FALSE)
   g <- path_graph_impl(3)
   expect_snapshot(count_automorphisms_impl(g))
-  expect_snapshot(count_automorphisms_impl(g, colors = c(1, 2, 3), sh = "fl"))
+  expect_snapshot(count_automorphisms_impl(g, colors = c(1, 2, 3)))
 })
 
 test_that("count_automorphisms_impl errors", {
@@ -4787,9 +4607,7 @@ test_that("automorphism_group_impl basic", {
   expect_snapshot(automorphism_group_impl(g))
   expect_snapshot(automorphism_group_impl(
     g,
-    colors = c(1, 2, 3),
-    sh = "fl",
-    details = TRUE
+    colors = c(1, 2, 3)
   ))
 })
 
@@ -4992,20 +4810,6 @@ test_that("sir_impl errors", {
   expect_snapshot_igraph_error(sir_impl(NULL, beta = 0.1, gamma = 0.1))
 })
 
-# 304. convex_hull_2d_impl
-
-test_that("convex_hull_2d_impl basic", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot(convex_hull_2d_impl(matrix(1:6, ncol = 2)))
-})
-
-test_that("convex_hull_2d_impl errors", {
-  withr::local_seed(20250909)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(convex_hull_2d_impl("a"))
-})
-
 # 305. dim_select_impl
 
 test_that("dim_select_impl basic", {
@@ -5359,138 +5163,6 @@ test_that("is_edge_coloring_impl errors", {
   expect_snapshot_igraph_error(is_edge_coloring_impl(NULL, types = c(1, 2)))
 })
 
-# 327. deterministic_optimal_imitation_impl
-
-test_that("deterministic_optimal_imitation_impl basic", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(deterministic_optimal_imitation_impl(
-    g,
-    1,
-    quantities = c(1, 2, 3),
-    strategies = c(1, 2, 3)
-  ))
-  expect_snapshot(deterministic_optimal_imitation_impl(
-    g,
-    1,
-    optimality = "minimum",
-    quantities = c(1, 2, 3),
-    strategies = c(1, 2, 3),
-    mode = "in"
-  ))
-})
-
-test_that("deterministic_optimal_imitation_impl errors", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(
-    deterministic_optimal_imitation_impl(
-      NULL,
-      1,
-      quantities = c(1, 2, 3),
-      strategies = c(1, 2, 3)
-    )
-  )
-})
-
-# 328. moran_process_impl
-
-test_that("moran_process_impl basic", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(moran_process_impl(
-    g,
-    weights = c(1, 1),
-    quantities = c(1, 2, 3),
-    strategies = c(1, 2, 3),
-    mode = "in"
-  ))
-})
-
-test_that("moran_process_impl errors", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(
-    moran_process_impl(NULL, quantities = c(1, 2, 3), strategies = c(1, 2, 3))
-  )
-})
-
-# 329. roulette_wheel_imitation_impl
-
-test_that("roulette_wheel_imitation_impl basic", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(roulette_wheel_imitation_impl(
-    g,
-    1,
-    TRUE,
-    quantities = c(1, 2, 3),
-    strategies = c(1, 2, 3)
-  ))
-  expect_snapshot(roulette_wheel_imitation_impl(
-    g,
-    1,
-    FALSE,
-    quantities = c(1, 2, 3),
-    strategies = c(1, 2, 3),
-    mode = "in"
-  ))
-})
-
-test_that("roulette_wheel_imitation_impl errors", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(
-    roulette_wheel_imitation_impl(
-      NULL,
-      1,
-      TRUE,
-      quantities = c(1, 2, 3),
-      strategies = c(1, 2, 3)
-    )
-  )
-})
-
-# 330. stochastic_imitation_impl
-
-test_that("stochastic_imitation_impl basic", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(stochastic_imitation_impl(
-    g,
-    1,
-    algo = 1,
-    quantities = c(1, 2, 3),
-    strategies = c(1, 2, 3)
-  ))
-  expect_snapshot(stochastic_imitation_impl(
-    g,
-    1,
-    algo = 2,
-    quantities = c(1, 2, 3),
-    strategies = c(1, 2, 3),
-    mode = "in"
-  ))
-})
-
-test_that("stochastic_imitation_impl errors", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(
-    stochastic_imitation_impl(
-      NULL,
-      1,
-      algo = 1,
-      quantities = c(1, 2, 3),
-      strategies = c(1, 2, 3)
-    )
-  )
-})
-
 # 331. invalidate_cache_impl
 
 test_that("invalidate_cache_impl basic", {
@@ -5506,33 +5178,6 @@ test_that("invalidate_cache_impl errors", {
   expect_snapshot_igraph_error(invalidate_cache_impl(NULL))
 })
 
-# 332. vertex_path_from_edge_path_impl
-
-test_that("vertex_path_from_edge_path_impl basic", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  g <- path_graph_impl(3)
-  expect_snapshot(vertex_path_from_edge_path_impl(
-    g,
-    start = 1,
-    edge.path = c(1, 2)
-  ))
-  expect_snapshot(vertex_path_from_edge_path_impl(
-    g,
-    start = 1,
-    edge.path = c(1),
-    mode = "in"
-  ))
-})
-
-test_that("vertex_path_from_edge_path_impl errors", {
-  withr::local_seed(12345)
-  local_igraph_options(print.id = FALSE)
-  expect_snapshot_igraph_error(
-    vertex_path_from_edge_path_impl(NULL, start = 1, edge.path = c(1, 2))
-  )
-})
-
 # 333. version_impl
 
 test_that("version_impl basic", {
diff --git a/tests/testthat/test-centrality.R b/tests/testthat/test-centrality.R
index 367e88e0248..f78a23d8fd8 100644
--- a/tests/testthat/test-centrality.R
+++ b/tests/testthat/test-centrality.R
@@ -590,7 +590,8 @@ test_that("eigen_centrality() works", {
 
   for (i in 1:1000) {
     G <- sample_gnm(10, sample(1:20, 1))
-    ev <- eigen_centrality(G)
+    # FIXME: Find a way to avoid warnings
+    suppressWarnings(ev <- eigen_centrality(G))
     expect_good(
       as_adjacency_matrix(G, sparse = FALSE),
       ev$vector,
diff --git a/tests/testthat/test-interface.R b/tests/testthat/test-interface.R
index d1f5b10ecc1..a40b91f2ea4 100644
--- a/tests/testthat/test-interface.R
+++ b/tests/testthat/test-interface.R
@@ -222,3 +222,10 @@ test_that("get_edge_id() errors correctly for wrong matrices", {
   mat <- matrix(c(1, 2, 1, 3, 1, 4), nrow = 2, ncol = 3)
   lifecycle::expect_deprecated(get_edge_ids(g, mat))
 })
+
+test_that("incident() works", {
+  local_igraph_options(print.id = FALSE)
+  g <- make_graph("Zachary")
+  expect_snapshot(incident(g, 1))
+  expect_snapshot(incident(g, 34))
+})
diff --git a/tests/testthat/test-simple.R b/tests/testthat/test-simple.R
new file mode 100644
index 00000000000..aff0bea5c1e
--- /dev/null
+++ b/tests/testthat/test-simple.R
@@ -0,0 +1,5 @@
+test_that("is_simple() works", {
+  g <- graph_from_literal(1 +-+ 2 -+ 3)
+  expect_true(is_simple(g))
+  expect_false(is_simple(g, directed = FALSE))
+})
diff --git a/tests/testthat/test-structural-properties.R b/tests/testthat/test-structural-properties.R
index f938d495dd0..0c92d2299b9 100644
--- a/tests/testthat/test-structural-properties.R
+++ b/tests/testthat/test-structural-properties.R
@@ -65,9 +65,9 @@ test_that("max_degree() works", {
   g <- make_graph(c(1, 2, 2, 2, 2, 3), directed = TRUE)
   expect_equal(max_degree(g), 4)
   expect_equal(max_degree(g, mode = "out"), 2)
-  expect_equal(max_degree(g, loops = FALSE), 2)
-  expect_equal(max_degree(g, mode = "out", loops = FALSE), 1)
-  expect_equal(max_degree(g, mode = "in", loops = FALSE), 1)
+  expect_equal(max_degree(g, loops = "none"), 2)
+  expect_equal(max_degree(g, mode = "out", loops = "none"), 1)
+  expect_equal(max_degree(g, mode = "in", loops = "none"), 1)
   expect_equal(max_degree(g, v = c()), 0)
   expect_equal(max_degree(make_empty_graph()), 0)
 })
@@ -905,7 +905,7 @@ test_that("edge_density works", {
   expect_equal(gd, gd2)
 })
 
-test_that("knn works", {
+test_that("knn works -- trivial examples", {
   withr::local_seed(42)
 
   ## Some trivial ones
@@ -917,23 +917,28 @@ test_that("knn works", {
     knn(g2),
     list(knn = c(1, rep(9, 9)), knnk = c(9, rep(NaN, 7), 1))
   )
+})
 
-  ## A scale-free one, try to plot 'knnk'
+test_that("knn works -- scale-free one", {
+  withr::local_seed(42)
   g3 <- simplify(sample_pa(1000, m = 5))
   r3 <- knn(g3)
   expect_equal(r3$knn[43], 46)
   expect_equal(r3$knn[1000], 192.4)
   expect_equal(r3$knnk[100], 18.78)
   expect_equal(length(r3$knnk), 359)
+})
 
-  ## A random graph
+test_that("knn works -- random graph", {
+  withr::local_seed(42)
   g4 <- sample_gnp(1000, p = 5 / 1000)
   r4 <- knn(g4)
-  expect_equal(r4$knn[1000], 20 / 3)
+  expect_equal(r4$knn[1000], 5)
   expect_equal(length(r4$knnk), 15)
-  expect_equal(r4$knnk[12], 19 / 3)
+  expect_equal(r4$knnk[12], 5.6389, tolerance = 1e-5)
+})
 
-  ## A weighted graph
+test_that("knn works -- weighted graph", {
   g5 <- make_star(10)
   E(g5)$weight <- seq(ecount(g5))
   r5 <- knn(g5)