A Guided Genetic Algorithm for Automated Crash Reproduction

@article{Soltani2017AGG,
  title={A Guided Genetic Algorithm for Automated Crash Reproduction},
  author={Mozhan Soltani and Annibale Panichella and Arie van Deursen},
  journal={2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)},
  year={2017},
  pages={209-220},
  url={https://api.semanticscholar.org/CorpusID:199514177}
}
EvoCrash is presented, a post-failure approach which uses a novel Guided Genetic Algorithm (GGA) to cope with the large search space characterizing real-world software programs and outperforming the state-of-the-art in crash replication.
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40 References

Evolutionary Testing for Crash Reproduction

This paper proposes a new solution for automatic crash reproduction based on evolutionary unit test generation techniques that can successfully reproduce crashes which are not reproducible by two other state-of-art techniques.

Crash reproduction via test case mutation: let existing test cases help

This paper proposes an approach to automatic crash reproduction via test case mutation, which updates existing test cases to trigger crashes rather than creating new test cases from scratch, and increases the chance of executing the specific path.

1600 faults in 100 projects: automatically finding faults while achieving high coverage with EvoSuite

An empirical study applying EvoSuite on 100 randomly selected open source software projects reveals that SBST has the unique advantage of being well suited to perform both traditional goals at the same timeโ€”efficiently triggering faults, while producing representative test sets for any chosen coverage criterion.

JCHARMING: A bug reproduction approach using crash traces and directed model checking

A novel crash reproduction approach, called JCHARMING (Java CrasH Automatic Reproduction by directed Model checkING), which takes advantage of the completeness provided by model checking while ignoring unneeded system states by means of information found in crash traces combined with static slices.

STAR: Stack Trace Based Automatic Crash Reproduction via Symbolic Execution

This paper proposes an automatic crash reproduction framework using collected crash stack traces that combines an efficient backward symbolic execution and a novel method sequence composition approach to generate unit test cases that can reproduce the original crashes without incurring additional runtime overhead.

Whole Test Suite Generation

This work proposes a novel paradigm in which whole test suites are evolved with the aim of covering all coverage goals at the same time while keeping the total size as small as possible, and implemented this novel approach in the EvoSuite tool.

Instance Generator and Problem Representation to Improve Object Oriented Code Coverage

This work presents a new automated search-based software test-data generation approach that achieves high code coverage for unit-class testing and implements it in a tool, JTExpert, that gives better results in terms of search time and code coverage than the state of the art, EvoSuite.

Reconstructing Core Dumps

Applied on seven non-trivial Java bugs, RECORE reconstructs the exact failure in five cases without any runtime overhead in production code.

Pex-White Box Test Generation for .NET

Pex automatically produces a small test suite with high code coverage for a .NET program. To this end, Pex performs a systematic program analysis (using dynamic symbolic execution, similar toโ€ฆ

A bug reproduction approach based on directed model checking and crash traces

This paper proposes a novel crash reproduction approach that combines directed model checking and backward slicing to identify the program statements needed to reproduce a crash and shows that JCHARMING is efficient in reproducing bugs from 10 different open source systems.