- Verification results processing, visualization and assessment:
- Improving calculation and visualization of code coverage for particular verification tasks.
- Calculation and visualization of code coverage split by correctness rule specifications for verification jobs or sub-jobs as a whole.
- Switching to new functions for converting and comparing error traces by default as well as removing the outdated ones.
- Fixes of processing, visualization and comparison of error traces for data races.
- Verification back-ends:
- Support for configuring verification back-ends.
- Updating verification back-ends used by default.
- Integration of Ultimate Automizer as an alternative verification back-end.
- Verification tasks generation:
- Ability to generate verification tasks consisting of several C source files.
- Parallel generation of verification tasks and processing of verification results.
- Reusing intermediate results obtained during verification tasks generation.
- Support for installation and updates within OpenStack clouds.
After more than 2 years of very intensive development we are glad to announce that the first version of Klever was released. Klever 0.1 includes extremely many awesome features to mention all of them explicitly. We just would like to thank all developers and contributors who made this possible.
Starting from Klever 0.1 we will make new releases each several months and, if this will have sense for some users, create stable branches for previous releases to backport fixes of the most critical issues.
Ilja Zakharov has finished works on Google Summer of Code 2016 project "Environment model specifications for more bugs to reveal" for The Linux Foundation.
During the project Ilja has ported all environment model specifications and tests to a new process calculus based environment model generator and implemented new environment model specifications to improve precision of environment models generated during static verification of Linux kernel modules. Moreover, a lot of work has been done to fix bugs in the environment model generator and to implement new features in it. For instance, Ilja has implemented a feature to generate simplified models for huge drivers to get a chance to a verification tool to finish analysis within a reasonable time.
As a result of this work, overall verification false positive rate has been decreased to 75% and a number of missing target bugs has been decreased to 40% from 60% (number of missed confirmed bugs that should be able to detect with our verification system).
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