Debugging in Parallel

Abstract

The presence of multiple faults in a program can inhibit the ability of fault-localization techniques to locate the faults. This problem occurs for two reasons: when a program fails, the number of faults is, in general, unknown; and certain faults may mask or obfuscate other faults. This paper presents our approach to solving this problem that leverages the well-known advantages of parallel work flows to reduce the time-to-release of a program. Our approach consists of a technique that enables more effective debugging in the presence of multiple faults and a methodology that enables multiple developers to simultaneously debug multiple faults. The paper also presents an empirical study that demonstrates that our parallel-debugging technique and methodology can yield a dramatic decrease in total debugging time compared to a one-fault-at-a-time, or conventionally sequential, approach.


Related research categories:
(1) Debugging
(2) Testing
(3) Empirical Studies
(4) Machine Learning

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