Teralizer: Semantics-Based Test Generalization from Conventional Unit Tests to Property-Based Tests
- URL: http://arxiv.org/abs/2512.14475v1
- Date: Tue, 16 Dec 2025 15:08:00 GMT
- Title: Teralizer: Semantics-Based Test Generalization from Conventional Unit Tests to Property-Based Tests
- Authors: Johann Glock, Clemens Bauer, Martin Pinzger,
- Abstract summary: Teralizer is a prototype for Java that transforms JUnit tests into property-based jqwik tests.<n>We demonstrate this approach through Teralizer, a prototype for Java that transforms JUnit tests into property-based jqwik tests.<n>Generalization of mature developer-written tests from Apache Commons utilities showed only 0.05-0.07 percentage points improvement.
- Score: 5.266171160963615
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Conventional unit tests validate single input-output pairs, leaving most inputs of an execution path untested. Property-based testing addresses this shortcoming by generating multiple inputs satisfying properties but requires significant manual effort to define properties and their constraints. We propose a semantics-based approach that automatically transforms unit tests into property-based tests by extracting specifications from implementations via single-path symbolic analysis. We demonstrate this approach through Teralizer, a prototype for Java that transforms JUnit tests into property-based jqwik tests. Unlike prior work that generalizes from input-output examples, Teralizer derives specifications from program semantics. We evaluated Teralizer on three progressively challenging datasets. On EvoSuite-generated tests for EqBench and Apache Commons utilities, Teralizer improved mutation scores by 1-4 percentage points. Generalization of mature developer-written tests from Apache Commons utilities showed only 0.05-0.07 percentage points improvement. Analysis of 632 real-world Java projects from RepoReapers highlights applicability barriers: only 1.7% of projects completed the generalization pipeline, with failures primarily due to type support limitations in symbolic analysis and static analysis limitations in our prototype. Based on the results, we provide a roadmap for future work, identifying research and engineering challenges that need to be tackled to advance the field of test generalization. Artifacts available at: https://doi.org/10.5281/zenodo.17950381
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