Merge pull request #1467 from visr/typo

docs: fix a few typos

Author: YingboMa

docs/src/basics/AbstractSystem.md

@@ -62,7 +62,7 @@ Optionally, a system could have:
 - `get_noiseeqs(sys)`: Noise equations of the current-level system.
 
 Note that if you know a system is an `AbstractTimeDependentSystem` you could use `get_iv` to get the 
-unique independent variable directly, rather than using `independenent_variables(sys)[1]`, which is clunky and may cause problems if `sys` is an `AbstractMultivariateSystem` because there may be more than one independent variable. `AbstractTimeIndependentSystem`s do not have a method `get_iv`, and `independent_variables(sys)` will return a size-zero result for such. For an `AbstractMultivariateSystem`, `get_ivs` is equivalent.
+unique independent variable directly, rather than using `independent_variables(sys)[1]`, which is clunky and may cause problems if `sys` is an `AbstractMultivariateSystem` because there may be more than one independent variable. `AbstractTimeIndependentSystem`s do not have a method `get_iv`, and `independent_variables(sys)` will return a size-zero result for such. For an `AbstractMultivariateSystem`, `get_ivs` is equivalent.
 
 A system could also have caches:
 

docs/src/basics/Composition.md

@@ -129,7 +129,7 @@ will be lazily reconstructed on demand.
 
 In some scenarios, it could be useful for model parameters to be expressed
 in terms of other parameters, or shared between common subsystems.
-To fascilitate this, ModelingToolkit supports sybmolic expressions
+To facilitate this, ModelingToolkit supports symbolic expressions
 in default values, and scoped variables.
 
 With symbolic parameters, it is possible to set the default value of a parameter or initial condition to an expression of other variables.
@@ -256,7 +256,7 @@ solving. In summary: these problems are structurally modified, but could be
 more efficient and more stable.
 
 ## Components with discontinuous dynamics
-When modeling, e.g., impacts, saturations or Coulomb friction, the dynamic equations are discontinuous in either the state or one of its derivatives. This causes the solver to take very small steps around the discontinuity, and sometimes leads to early stopping due to `dt <= dt_min`. The correct way to handle such dynamics is to tell the solver about the discontinuity be means of a root-finding equation. [`ODEsystem`](@ref)s accept a keyword argument `continuous_events`
+When modeling, e.g., impacts, saturations or Coulomb friction, the dynamic equations are discontinuous in either the state or one of its derivatives. This causes the solver to take very small steps around the discontinuity, and sometimes leads to early stopping due to `dt <= dt_min`. The correct way to handle such dynamics is to tell the solver about the discontinuity by means of a root-finding equation. [`ODEsystem`](@ref)s accept a keyword argument `continuous_events`
 ```
 ODESystem(eqs, ...; continuous_events::Vector{Equation})
 ODESystem(eqs, ...; continuous_events::Pair{Vector{Equation}, Vector{Equation}})

docs/src/basics/FAQ.md

@@ -27,7 +27,7 @@ pnew = varmap_to_vars([β=>3.0, c=>10.0, γ=>2.0],parameters(sys))
 For statements that are in the `if then else` form, use `IfElse.ifelse` from the
 [IfElse.jl](https://github.com/SciML/IfElse.jl) package to represent the code in a
 functional form. For handling direct `if` statements, you can use equivalent boolean
-mathematical expressions. For example `if x > 0 ...` can be implementated as just
+mathematical expressions. For example `if x > 0 ...` can be implemented as just
 `(x > 0) * `, where if `x <= 0` then the boolean will evaluate to `0` and thus the
 term will be excluded from the model.
 

docs/src/comparison.md

@@ -84,7 +84,7 @@
 
 - Modia.jl uses Julia's expression objects for representing its equations.
   ModelingToolkit.jl uses [Symbolics.jl](https://symbolics.juliasymbolics.org/dev/),
-  and thus the Julia expressions follow Julia symantics and can be manipulated
+  and thus the Julia expressions follow Julia semantics and can be manipulated
   using a computer algebra system (CAS).
 - Modia's compilation pipeline is similar to the
   [Dymola symbolic processing pipeline](https://www.claytex.com/tech-blog/model-translation-and-symbolic-manipulation/)

docs/src/tutorials/spring_mass.md

@@ -217,7 +217,7 @@ observed(sys)
  spring₊x(t) ~ sqrt(abs2(mass₊pos[1](t)) + abs2(mass₊pos[2](t)))
 ```
 
-These are explicit algebraic equations which can be used to reconstruct the required variables on the fly. This leads to dramatic computational savings since implicitly solving an ODE scales as O(n^3), so fewer states are signficantly better!
+These are explicit algebraic equations which can be used to reconstruct the required variables on the fly. This leads to dramatic computational savings since implicitly solving an ODE scales as O(n^3), so fewer states are significantly better!
 
 We can access these variables using the solution object. For example, let's retrieve the x-position of the mass over time:
 

src/structural_transformation/bareiss.jl

@@ -1,4 +1,4 @@
-# Keeps compatibility with bariess code movoed to Base/stdlib on older releases
+# Keeps compatibility with bariess code moved to Base/stdlib on older releases
 
 using LinearAlgebra
 using SparseArrays

src/systems/abstractsystem.jl

@@ -994,7 +994,7 @@ end
 """
 $(TYPEDSIGNATURES)
 
-entend the `basesys` with `sys`, the resulting system would inherit `sys`'s name
+extend the `basesys` with `sys`, the resulting system would inherit `sys`'s name
 by default.
 """
 function extend(sys::AbstractSystem, basesys::AbstractSystem; name::Symbol=nameof(sys))