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OOPSLA '04 Companion to the 19th annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
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From daikon to agitator: lessons and challenges in building a commercial tool for developer testing
Proceedings of the 2006 international symposium on Software testing and analysis
DSD-Crasher: a hybrid analysis tool for bug finding
Proceedings of the 2006 international symposium on Software testing and analysis
Bogor/Kiasan: A k-bounded Symbolic Execution for Checking Strong Heap Properties of Open Systems
ASE '06 Proceedings of the 21st IEEE/ACM International Conference on Automated Software Engineering
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EXE: automatically generating inputs of death
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Lightweight extraction of syntactic specifications
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Compositional dynamic test generation
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Variably interprocedural program analysis for runtime error detection
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TAICPART-MUTATION '07 Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION
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Information and Software Technology
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Testing container classes: random or systematic?
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Information and Software Technology
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Test-case generation and bug-finding through symbolic execution
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Test input generation using dynamic programming
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Detecting missing method calls as violations of the majority rule
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Dynamically validating static memory leak warnings
Proceedings of the 2013 International Symposium on Software Testing and Analysis
A comparative evaluation of static analysis actionable alert identification techniques
Proceedings of the 9th International Conference on Predictive Models in Software Engineering
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DSD-Crasher is a bug finding tool that follows a three-step approach to program analysis: D. Capture the program's intended execution behavior with dynamic invariant detection. The derived invariants exclude many unwanted values from the program's input domain. S. Statically analyze the program within the restricted input domain to explore many paths. D. Automatically generate test cases that focus on reproducing the predictions of the static analysis. Thereby confirmed results are feasible. This three-step approach yields benefits compared to past two-step combinations in the literature. In our evaluation with third-party applications, we demonstrate higher precision over tools that lack a dynamic step and higher efficiency over tools that lack a static step.