Abstract

The quality and reliability of software systems, in terms of their functional correctness, critically relies on the effectiveness of the testing tools and techniques to detect errors in the system before deployment. A lack of testing tools for concurrent programs that systematically control thread scheduling choices has not allowed concurrent software development to keep abreast with hardware trends of multi-core and multi-processor technologies. This motivates a need for the development of systematic testing techniques that detect errors in concurrent programs. The work in this dissertation presents a potentially scalable technique that can be used to detect concurrency errors in production code. The technique is a viable solution for software engineers and testers to detect errors in multi-threaded programs before deployment. We present a guided testing technique that combines static analysis techniques, systematic verification techniques, and heuristics to efficiently detect errors in concurrent programs. An abstraction-refinement technique lies at the heart of the guided test technique. The abstraction-refinement technique uses as input potential errors in the program generated by imprecise, but scalable, static analysis tools. The abstraction further leverages static analyses to generate a set of program locations relevant in verifying the reachability of the potential error. Program execution is guided along these points by ranking both thread and data non-determinism. The set of relevant locations is refined when program execution is unable to make progress. The dissertation also discusses various heuristics for effectively guiding program execution. We implemented the guided test technique to detect errors in Java programs. Guided test successfully detects errors caused by thread schedules and data input values in Java benchmarks and the JDK concurrent libraries for which other state of the art analysis and testing tools for concurrent programs are unable to find an error.

Degree

PhD

College and Department

Physical and Mathematical Sciences; Computer Science

Rights

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