Briand, Lionel

Software documentation: how much is enough?

Briand, L. C. (2003) · Seventh European Conference onSoftware Maintenance and Reengineering, 2003. Proceedings.

Software Engineering ResearchModel-Driven Software Engineering Techniques

Cited by 69

Impact of log parsing on deep learning-based anomaly detection

Khan, Z. A., Shin, D., Bianculli, D., & Briand, L. C. (2024) · Empirical Software Engineering

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 49

Automating image segmentation verification and validation by learning test oracles

Frounchi, K., Briand, L. C., Grady, L., Labiche, Y., & Subramanyan, R. (2011) · Information and Software Technology

Medical Image Segmentation TechniquesSoftware Testing and Debugging Techniques

Cited by 31

Simulator-based Explanation and Debugging of Hazard-triggering Events in DNN-based Safety-critical Systems

Fahmy, H., Pastore, F., Briand, L., & Stifter, T. (2023) · ACM Transactions on Software Engineering and Methodology

Software Testing and Debugging TechniquesSafety Systems Engineering in Autonomy

Cited by 17

LLM meets ML: Data-efficient Anomaly Detection on Unstable Logs

Hadadi, F., Xu, Q., Bianculli, D., & Briand, L. (2024) · arXiv

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 7

SWE-ABS: Adversarial Benchmark Strengthening Exposes Inflated Success Rates on Test-based Benchmark

Yu, B., Cao, Y., Zhang, Y., Lin, L., Xu, J., Zhong, Z., Xu, Q., Wang, G., Cao, J., Cheung, S.-C., et al. (2026) · arXiv

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 2

A Structured Approach to Safety Case Construction for AI Systems

Lee, S. U., Zhu, L., Shamsujjoha, M., Dong, L., Lu, Q., Chen, J., & Briand, L. (2026) · arXiv

Safety Systems Engineering in AutonomyEthics and Social Impacts of AI

Cited by 0