4 citations · 6 across the 17 of their papers we have counts for
9 papers · 1 filter
Discovering Performance Archetypes: Critical-Path-Aware Pattern Analysis and Regression Detection
Kaveh Shahedi, Heng Li, Maxime Lamothe +1
Software performance analysis and prediction requires integrating multiple signals, as code structure alone cannot capture runtime behavior shaped by execution frequency, resource…
ToolLoop: Closed-Loop Tool-Use Data Synthesis via Decomposed Generation and Dynamic Self-Feedback
Min Zeng, Yuzhou Liu, Zhenyu Cao +5
High-quality tool-use data is critical for training language models to interact effectively with external tools. However, existing synthetic approaches typically follow a generate-…
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…