This changelog lists only the most important changes. Smaller (bug)fixes as well as non-mature features are not part of the changelog.
This changelog lists only the most important changes. Smaller (bug)fixes as well as non-mature features are not part of the changelog.
The releases of major and minor versions contain an overview of changes since the last major/minor update.
The releases of major and minor versions contain an overview of changes since the last major/minor update.
Version 1.4.x
Version 1.5.x
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## Version 1.4.2 (under development)
## Version 1.5.0 (2020/03)
- Added portfolio engine which picks a good engine (among other settings) based on features of the symbolic input.
- Added portfolio engine which picks a good engine (among other settings) based on features of the symbolic input.
- Abort of Storm (via timeout or CTRL+C for example) is now gracefully handled. After an abort signal the program waits some seconds to output the result computed so far and terminates afterwards. A second signal immediately terminates the program.
- Abort of Storm (via timeout or CTRL+C for example) is now gracefully handled. After an abort signal the program waits some seconds to output the result computed so far and terminates afterwards. A second signal immediately terminates the program.
- Setting `--engine dd-to-sparse --bisimulation` now triggers extracting the sparse bisimulation quotient.
- Setting `--engine dd-to-sparse --bisimulation` now triggers extracting the sparse bisimulation quotient.
@ -25,6 +26,11 @@ Version 1.4.x
- `storm-pomdp`: Only accept POMDPs that are canonical.
- `storm-pomdp`: Only accept POMDPs that are canonical.
- `storm-pomdp`: Prism language extended with observable expressions.
- `storm-pomdp`: Prism language extended with observable expressions.
- `storm-pomdp`: Various fixes that prevented usage.
- `storm-pomdp`: Various fixes that prevented usage.
- Several bug fixes.
Version 1.4.x
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### Version 1.4.1 (2019/12)
### Version 1.4.1 (2019/12)
- Implemented long run average (LRA) computation for DTMCs/CTMCs via value iteration and via gain/bias equations.
- Implemented long run average (LRA) computation for DTMCs/CTMCs via value iteration and via gain/bias equations.