Eraser: a dynamic data race detector for multithreaded programs
ACM Transactions on Computer Systems (TOCS)
Proceedings of the 14th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Using Runtime Analysis to Guide Model Checking of Java Programs
Proceedings of the 7th International SPIN Workshop on SPIN Model Checking and Software Verification
Coverage directed test generation for functional verification using bayesian networks
Proceedings of the 40th annual Design Automation Conference
Concurrent Bug Patterns and How to Test Them
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Heuristics for Finding Concurrent Bugs
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
A Classification of Concurrency Failures in Java Components
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Atomizer: a dynamic atomicity checker for multithreaded programs
Proceedings of the 31st ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Probabilistic regression suites for functional verification
Proceedings of the 41st annual Design Automation Conference
Towards a framework and a benchmark for testing tools for multi-threaded programs: Research Articles
Concurrency and Computation: Practice & Experience - Parallel and Distributed Systems: Testing and Debugging (PADTAD)
Noise injection heuristics for concurrency testing
MEMICS'11 Proceedings of the 7th international conference on Mathematical and Engineering Methods in Computer Science
Testing of concurrent programs using genetic algorithms
SSBSE'12 Proceedings of the 4th international conference on Search Based Software Engineering
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A Random test generator generates executable tests together with their expected results. In the form of a noise-maker, it seeds the program with conditional scheduling primitives (such as yield()) that may cause context switches. As a result different interleavings are potentially produced in different executions of the program. Determining a-priori the set of seeded locations required for a bug to manifest itself is rarely possible. This work proposes to reformulate random test generation of concurrent Java programs as a search problem. Hence, it allows applying a set of well known search techniques from the domain of AI to the input space of the test generator. By iteratively refining the input parameters fed to the test generator, the search process creates testing scenarios (i.e. interleavings) that maximizes predefined objective functions. We develop geneticFinder, a noise-maker that uses a genetic algorithm as a search method. We demonstrate our approach by maximizing two objective functions: the high manifestation rate of concurrent bugs and the exporting of a high degree of debugging information to the user. Experimental results show our approach is effective.