OOPSLA '04 Companion to the 19th annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
Check 'n' crash: combining static checking and testing
Proceedings of the 27th international conference on Software engineering
DART: directed automated random testing
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
CUTE: a concolic unit testing engine for C
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Effective typestate verification in the presence of aliasing
Proceedings of the 2006 international symposium on Software testing and analysis
Pex: white box test generation for .NET
TAP'08 Proceedings of the 2nd international conference on Tests and proofs
Practical verification for the working programmer with codecontracts and abstract interpretation
VMCAI'11 Proceedings of the 12th international conference on Verification, model checking, and abstract interpretation
Program slicing enhances a verification technique combining static and dynamic analysis
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Verifying systems rules using rule-directed symbolic execution
Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems
Dynamically validating static memory leak warnings
Proceedings of the 2013 International Symposium on Software Testing and Analysis
Behind the scenes in SANTE: a combination of static and dynamic analyses
Automated Software Engineering
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Software-defect detection is an increasingly important research topic in software engineering. To detect defects in a program, static verification and dynamic test generation are two important proposed techniques. However, both of these techniques face their respective issues. Static verification produces false positives, and on the other hand, dynamic test generation is often time consuming. To address the limitations of static verification and dynamic test generation, we present an automated defect-detection tool, called DyTa, that combines both static verification and dynamic test generation. DyTa consists of a static phase and a dynamic phase. The static phase detects potential defects with a static checker; the dynamic phase generates test inputs through dynamic symbolic execution to confirm these potential defects. DyTa reduces the number of false positives compared to static verification and performs more efficiently compared to dynamic test generation.