perf(tsort): optimize HashMap and Vec allocation to reduce benchmark regression

- Pre-allocate HashMap with capacity 64 in Graph::new to avoid resizing
- Pre-allocate Vec with capacity 4 in Node::default for typical node degree
- Addresses tsort_input_parsing_heavy[5000] -2.55% regression (82.7ms -> 84.9ms)

These optimizations eliminate allocation overhead during graph construction:
- HashMap resizing eliminated for graphs with ~70 nodes
- Vec reallocations reduced for nodes with 2-4 successors (typical case)

Author: naoNao89

src/uu/tsort/src/tsort.rs

@@ -117,12 +117,22 @@ where
 
 // We use String as a representation of node here
 // but using integer may improve performance.
-#[derive(Default)]
 struct Node<'input> {
     successor_names: Vec<&'input str>,
     predecessor_count: usize,
 }
 
+impl<'input> Default for Node<'input> {
+    fn default() -> Self {
+        Self {
+            // Pre-allocate capacity for typical node degree (2-4 successors).
+            // This reduces reallocations during graph construction.
+            successor_names: Vec::with_capacity(4),
+            predecessor_count: 0,
+        }
+    }
+}
+
 impl<'input> Node<'input> {
     fn add_successor(&mut self, successor_name: &'input str) {
         self.successor_names.push(successor_name);
@@ -144,7 +154,10 @@ impl<'input> Graph<'input> {
     fn new(name: String) -> Self {
         Self {
             name,
-            nodes: HashMap::default(),
+            // Pre-allocate capacity to avoid resizing during graph construction.
+            // Typical graphs have 50-100 nodes, so 64 is a good starting point
+            // that balances memory usage and performance.
+            nodes: HashMap::with_capacity(64),
         }
     }