Abstract
Random testing has proven to be an effective technique for compiler
validation. However, the debugging of bugs identified through random
testing presents a significant challenge due to the frequent occurrence of duplicate test programs that expose identical compiler bugs. The process
to identify duplicates is a practical research problem known as bug deduplication. Prior methodologies for compiler bug deduplication
primarily rely on program analysis to extract bug-related features for duplicate identification, which can result in substantial computational overhead and limited generalizability. This paper investigates the
feasibility of employing bisection, a standard debugging procedure largely overlooked in prior research on compiler bug deduplication, for this
purpose. Our study demonstrates that the utilization of bisection to
locate failure-inducing commits provides a valuable criterion for deduplication, albeit one that requires supplementary techniques for more accurate identification. Building on these results, we introduce BugLens,
a novel deduplication method that primarily uses bisection, enhanced by
the identification of bug-triggering optimizations to minimize false
negatives. Empirical evaluations conducted on four real-world datasets demonstrate that BugLens significantly outperforms the state-of-the-art analysis-based methodologies Tamer and D3 by saving an average of 26.98%
and 9.64% human effort to identify the same number of distinct bugs. Given
the inherent simplicity and generalizability of bisection, it presents a
highly practical solution for compiler bug deduplication in real-world applications.
https://arxiv.org/abs/2506.23281
Regards,
John Levine,
[email protected], Taughannock Networks, Trumansburg NY
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