[documentation] Fix the table of AD backends

Author: amontoison

docs/src/backend.md

@@ -8,14 +8,14 @@ The backend information is in a structure [`ADNLPModels.ADModelBackend`](@ref) i
 The functions used internally to define the NLPModel API and the possible backends are defined in the following table:
 
 | Functions | FowardDiff backends | ReverseDiff backends | Zygote backends | Enzyme backend | Sparse backend |
-| ----------- | ----------- | ----------- | ----------- |  ----------- |  ----------- |  ----------- |
+| --------- | ------------------- | -------------------- | --------------- | -------------- | -------------- |
 | `gradient` and `gradient!` | `ForwardDiffADGradient`/`GenericForwardDiffADGradient` | `ReverseDiffADGradient`/`GenericReverseDiffADGradient` | `ZygoteADGradient` | `EnzymeADGradient` | -- |
 | `jacobian` | `ForwardDiffADJacobian` | `ReverseDiffADJacobian` | `ZygoteADJacobian` | -- | `SparseADJacobian` |
 | `hessian` | `ForwardDiffADHessian` | `ReverseDiffADHessian` | `ZygoteADHessian` | -- | `SparseADHessian` |
-| `Jprod` | `ForwardDiffADJprod`/`GenericForwardDiffADJprod` | `ReverseDiffADJprod`/`GenericReverseDiffADJprod` | `ZygoteADJprod` | -- |
-| `Jtprod` | `ForwardDiffADJtprod`/`GenericForwardDiffADJtprod` | `ReverseDiffADJtprod`/`GenericReverseDiffADJtprod` | `ZygoteADJtprod` | -- |
-| `Hvprod` | `ForwardDiffADHvprod`/`GenericForwardDiffADHvprod` | `ReverseDiffADHvprod`/`GenericReverseDiffADHvprod` | -- |
-| `directional_second_derivative` | `ForwardDiffADGHjvprod` | -- | -- | -- | -- | 
+| `Jprod` | `ForwardDiffADJprod`/`GenericForwardDiffADJprod` | `ReverseDiffADJprod`/`GenericReverseDiffADJprod` | `ZygoteADJprod` | -- | -- |
+| `Jtprod` | `ForwardDiffADJtprod`/`GenericForwardDiffADJtprod` | `ReverseDiffADJtprod`/`GenericReverseDiffADJtprod` | `ZygoteADJtprod` | -- | -- |
+| `Hvprod` | `ForwardDiffADHvprod`/`GenericForwardDiffADHvprod` | `ReverseDiffADHvprod`/`GenericReverseDiffADHvprod` | -- | -- | -- |
+| `directional_second_derivative` | `ForwardDiffADGHjvprod` | -- | -- | -- | -- |
 
 The functions `hess_structure!`, `hess_coord!`, `jac_structure!` and `jac_coord!` defined in `ad.jl` are generic to all the backends for now.
 

docs/src/predefined.md

@@ -75,5 +75,6 @@ jac(nlp, x)
 ```
 
 The package [`SparseConnectivityTracer.jl`](https://github.com/adrhill/SparseConnectivityTracer.jl) is used to compute the sparsity pattern of Jacobians and Hessians.
-The evaluation of the number of directional derivatives and the seeds needed to evaluate the compressed Jacobians and Hessians is done by [`ColPack.jl`](https://github.com/exanauts/ColPack.jl).
+The evaluation of the number of directional derivatives and the seeds required to compute compressed Jacobians and Hessians is performed using [`SparseMatrixColorings.jl`](https://github.com/gdalle/SparseMatrixColorings.jl).
+As of release v0.8.1, it has replaced [`ColPack.jl`](https://github.com/exanauts/ColPack.jl).
 We acknowledge Guillaume Dalle (@gdalle), Adrian Hill (@adrhill), and Michel Schanen (@michel2323) for the development of these packages.