Input Range Generation for Compiler-Induced Numerical Inconsistencies

Compiler-induced numerical inconsistencies present a significant challenge when testing and verifying numerical software—they can arise in a variety of situations, such as when porting code to a new platform or when using a different compiler or optimization flag. While existing tools can identify the source code location that induce an inconsistency for a specific input, no techniques are available to find input ranges where inputs that trigger these inconsistencies exist. In this paper, we propose a multi-phase approach to detect unknown input ranges that induce such inconsistencies; we call them inconsistency-inducing inputs. Our approach combines input-partitioned and coverage-based input sampling, input clustering, and optimization algorithms. We implement our approach in the tool CIGEN, which finds inputs that trigger high compiler-induced inconsistencies in numerical programs and outputs a list of input ranges containing such inconsistency-inducing inputs. Our experimental evaluation show 53.4% improvement over the state of the art in finding inputs that trigger compiler-induced inconsistencies in 175 GNU Scientific Library (GSL) functions. We further examine a subset of the inconsistencies and discuss their characteristics and possible root causes.

See the code on GitHub: github.com/LLNL/CIGEN

Recommended citation: Dolores Miao, Ignacio Laguna, and Cindy Rubio-González. 2024. Input Range Generation for Compiler-Induced Numerical Inconsistencies. In Proceedings of the 38th ACM International Conference on Supercomputing. Association for Computing Machinery, New York, NY, USA, 201–212.
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