Directed Test Program Generation for JIT Compiler Bug Localization
HeuiChan Lim, Saumya Debray

TL;DR
This paper introduces a novel method for automatically generating test programs to improve bug localization in JIT compilers by creating inputs that are both similar and dissimilar to seed programs, enhancing bug detection accuracy.
Contribution
It presents a new technique for test program generation that considers both passing and failing inputs, tailored for JIT compiler bug localization, outperforming existing methods.
Findings
Generated test inputs significantly improve bug localization accuracy.
The approach effectively distinguishes between bug-triggering and non-triggering inputs.
Prototype experiments demonstrate superior performance over current techniques.
Abstract
Bug localization techniques for Just-in-Time (JIT) compilers are based on analyzing the execution behaviors of the target JIT compiler on a set of test programs generated for this purpose; characteristics of these test inputs can significantly impact the accuracy of bug localization. However, current approaches for automatic test program generation do not work well for bug localization in JIT compilers. This paper proposes a novel technique for automatic test program generation for JIT compiler bug localization that is based on two key insights: (1) the generated test programs should contain both passing inputs (which do not trigger the bug) and failing inputs (which trigger the bug); and (2) the passing inputs should be as similar as possible to the initial seed input, while the failing programs should be as different as possible from it. We use a structural analysis of the seed…
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Taxonomy
TopicsSoftware Testing and Debugging Techniques · Software System Performance and Reliability · Software Reliability and Analysis Research
