4 citations · 6 across the 17 of their papers we have counts for
18 papers · 1 filter
Understanding the Energy Impact of Software Refactoring: A Workload-Aware Study of Controlled Examples and Real-World Commits
Haibo Wang, Heng Li, Shin Hwei Tan
Refactoring improves software maintainability while preserving functional behavior, yet behavior preservation does not imply energy neutrality. Existing studies primarily examine i…
LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs
Forough Majidi, Mohammad Mehdi Morovati, Foutse Khomh +1
Large Language Models (LLMs) are integrated into software systems and AI services, making efficient LLM serving a concern for software engineering. Serving LLMs is challenging beca…
Ethics Testing: Proactive Identification of Generative AI System Harms
Shin Hwei Tan, Haibo Wang, Heng Li
Generative Artificial Intelligence (GAI) systems that can automatically generate content in the form of source code or other contents (e.g., images) has seen increasing popularity…
Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code
Yang Liu, Da Song, Armstrong Foundjem +2
Chain-of-Thought (CoT) prompting is widely used to elicit explicit reasoning from large language models for code (LLM4Code). However, its impact on robustness and the stability of…
Empirical Characterization of Logging Smells in Machine Learning Code
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
Logging plays a central role in ensuring reproducibility, observability, and reliability in machine learning (ML) systems. While logging is generally considered a good engineering…
Improving the Robustness of Large Language Models for Code Tasks via Fine-tuning with Perturbed Data
Yang Liu, Armstrong Foundjem, Xingfang Wu +2
Context: In the fast-paced evolution of software development, Large Language Models (LLMs) have become indispensable tools for tasks such as code generation, completion, analysis,…
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…
LogLSHD: Fast Log Parsing with Locality-Sensitive Hashing and Dynamic Time Warping
Shu-Wei Huang, Xingfang Wu, Heng Li
Large-scale software systems generate vast volumes of system logs that are essential for monitoring, diagnosing, and performance optimization. However, the unstructured nature and…
An Efficient Model Maintenance Approach for MLOps
Forough Majidi, Foutse Khomh, Heng Li +1
In recent years, many industries have utilized machine learning (ML) models in their systems. Ideally, ML models should be trained on and applied to data from the same distribution…
Tracing Optimization for Performance Modeling and Regression Detection
Kaveh Shahedi, Heng Li, Maxime Lamothe +1
Software performance modeling plays a crucial role in developing and maintaining software systems. A performance model analytically describes the relationship between the performan…
What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach
Xingfang Wu, Heng Li, Foutse Khomh
Log data are generated from logging statements in the source code, providing insights into the execution processes of software applications and systems. State-of-the-art log-based…
Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection
Xingfang Wu, Heng Li, Nobukazu Yoshioka +2
One goal of technical online communities is to help developers find the right answer in one place. A single question can be asked in different ways with different wordings, leading…
Characterizing and Classifying Developer Forum Posts with their Intentions
Xingfang Wu, Eric Laufer, Heng Li +3
With the rapid growth of the developer community, the amount of posts on online technical forums has been growing rapidly, which poses difficulties for users to filter useful posts…