Add NEWS.md documenting v5.0.0 breaking changes

- Document breaking change in DAE initialization behavior
- Provide clear migration guide for affected users
- Explain available initialization algorithms
- Include rationale for the breaking change
- Add information about new ODE/SDE initialization support

Author: ChrisRackauckas

NEWS.md

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+# Sundials.jl NEWS
+
+## v5.0.0
+
+### Breaking Changes
+
+#### DAE Initialization Algorithm Changes
+
+The default initialization behavior for DAE problems has changed significantly. This is a **breaking change** that may affect existing code using IDA.
+
+**Previous behavior:**
+- IDA would automatically attempt to compute consistent initial conditions by default
+- This automatic initialization could sometimes produce incorrect results without warning
+
+**New behavior:**
+- The default is now validation-only mode that checks if provided initial conditions are consistent
+- If initial conditions are inconsistent, an error is raised with a clear message
+- Automatic initialization must be explicitly requested
+
+**Migration Guide:**
+
+If you have existing code that relies on automatic DAE initialization:
+
+```julia
+# Old code (v4.x) - automatic initialization was implicit
+prob = DAEProblem(f, du0, u0, tspan, differential_vars = differential_vars)
+sol = solve(prob, IDA())
+```
+
+You now have several options:
+
+1. **Use automatic initialization explicitly (recommended for most users):**
+```julia
+using DiffEqBase: BrownFullBasicInit
+prob = DAEProblem(f, du0, u0, tspan, differential_vars = differential_vars)
+sol = solve(prob, IDA(), initializealg = BrownFullBasicInit())
+```
+
+2. **Provide consistent initial conditions:**
+```julia
+# Ensure du0 and u0 satisfy f(du0, u0, p, t0) = 0
+prob = DAEProblem(f, du0, u0, tspan, differential_vars = differential_vars)
+sol = solve(prob, IDA())  # Will validate and proceed if consistent
+```
+
+3. **For problems without differential_vars information:**
+```julia
+using DiffEqBase: ShampineCollocationInit
+prob = DAEProblem(f, du0, u0, tspan)  # No differential_vars
+sol = solve(prob, IDA(), initializealg = ShampineCollocationInit())
+```
+
+**Available initialization algorithms:**
+- `DefaultInit()` - Intelligently chooses initialization based on problem type (new default)
+- `BrownFullBasicInit()` - Brown's algorithm for index-1 DAEs (requires differential_vars)
+- `ShampineCollocationInit()` - Shampine's collocation method (works without differential_vars)
+- `CheckInit()` - Only validates initial conditions without modification
+
+**Why this change was made:**
+- **Safety**: Silent automatic initialization could produce incorrect results
+- **Clarity**: Users now explicitly choose their initialization strategy
+- **Debugging**: Clearer error messages when initial conditions are inconsistent
+- **Performance**: Avoid unnecessary initialization computations when not needed
+
+#### ODE/SDE Initialization Support
+
+CVODE and ARKODE now support the `initializealg` parameter for parameter initialization compatibility with ModelingToolkit. This enables proper handling of problems with initialization requirements.
+
+```julia
+# Now supported for ODE problems with initialization needs
+sol = solve(prob, CVODE_BDF(), initializealg = DefaultInit())
+```
+
+### Features
+
+- Added support for DiffEqBase initialization algorithms across all Sundials solvers
+- Improved callback handling to use callback-specific initialization algorithms
+- Enhanced error messages for DAE initialization failures
+
+### Dependency Updates
+
+- Minimum DiffEqBase version: 6.190.2
+- Added NonlinearSolveBase dependency for improved nonlinear solving
+- Added LinearSolve dependency for initialization support
+- Updated minimum SciMLBase version to 2.119.0
+
+## Previous Versions
+
+For changes in previous versions, see the git history and release notes on GitHub.