An empirical analysis of flaky tests

By Q. Luo, Farah Hariri, Lamyaa Eloussi, Darko Marinov. SIGSOFT FSE, 2014

498 citations recorded by the source corpus.

Subfields: Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/363c9c645dc8c303c3d7ad995f60beae32ce10fa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Naman Jain
2. Leandro Von Werra

In Software

1. Naman Jain

Citations in the corpus

• BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions (2024, methodology): “…quality, we implement a three-fold human curation process: Examination We first perform a rigorous manual examination of the benchmarks, guided by a set of detailed guidelines (Appendix G.3) to add more test cases and resolve a list of runtime issues due to the LLM-generated flaky tests [37].”
• CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval (2025, unknown): “These challenges underscore the urgent need for retrieval systems that go beyond surface-level functional matching to explicitly account for code quality, leading to a central research question: Can code retrievers be designed based on not only relevance but also quality?”