1 citations · 2 across the 5 of their papers we have counts for
9 papers
Empirical Characterization of Logging Smells in Machine Learning Code
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
\underline{Context:} Logging is a fundamental yet complex practice in software engineering, essential for monitoring, debugging, and auditing software systems. With the increasing…
Logging Requirement for Continuous Auditing of Responsible Machine Learning-based Applications
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
Machine learning (ML) is increasingly applied across industries to automate decision-making, but concerns about ethical and legal compliance remain due to limited transparency, fai…
An Empirical Study on Method-Level Performance Evolution in Open-Source Java Projects
Kaveh Shahedi, Nana Gyambrah, Heng Li +2
Performance is a critical quality attribute in software development, yet the impact of method-level code changes on performance evolution remains poorly understood. While developer…
From Technical Excellence to Practical Adoption: Lessons Learned Building an ML-Enhanced Trace Analysis Tool
Kaveh Shahedi, Matthew Khouzam, Heng Li +2
System tracing has become essential for understanding complex software behavior in modern systems, yet sophisticated trace analysis tools face significant adoption gaps in industri…
Adversarial Attack Classification and Robustness Testing for Large Language Models for Code
Yang Liu, Armstrong Foundjem, Foutse Khomh +1
Large Language Models (LLMs) have become vital tools in software development tasks such as code generation, completion, and analysis. As their integration into workflows deepens, e…
SDLog: A Deep Learning Framework for Detecting Sensitive Information in Software Logs
Roozbeh Aghili, Xingfang Wu, Foutse Khomh +1
Software logs are messages recorded during the execution of a software system that provide crucial run-time information about events and activities. Although software logs have a c…