1 citations · 1 across the 9 of their papers we have counts for
9 papers
Pattern over Pixels: Measuring Pattern Completion Bias in Multimodal Code Generation
Khai-Nguyen Nguyen, Oscar Chaparro, Antonio Mastropaolo
Multimodal large language models (MLLMs) are increasingly used to translate webpage screenshots into front-end code, but repeated UI patterns may sway them toward visually incorrec…
Rethinking Issue Resolution for AI/ML Systems
Ahmed Adnan, Mushfiqur Rahman, Antu Saha +1
We advocate for AI/ML issue resolution frameworks tailored to maintenance workflows and the nature of modern AI/ML systems. Existing issue resolution frameworks largely emerged for…
On the Reliability of Code Comprehension Proxies
Erfan Arvan, Nadeeshan De Silva, Oscar Chaparro +1
Prior work on code comprehension uses different comprehension proxies---for example, Likert-scale ratings or answers to input-output questions about program snippets, usually colle…
Verifier Warnings Do Not Improve Comprehensibility Prediction
Nadeeshan De Silva, Martin Kellogg, Oscar Chaparro
Proponents of software verification suggest that code simplicity is linked to the effort to verify code, hypothesizing that formal verifiers produce fewer false positive warnings a…
Recovering Fine-Grained Code Change Rationale from Multiple Software Artifacts
Mehedi Sun, Antu Saha, Nadeeshan De Silva +2
Understanding the reasons behind past code changes is critical for refactoring, code review, and debugging. However, code change rationale is often fragmented, inconsistently docum…
Evaluating Language Model Applications for Identifying Solution-Related Content in Issue Report Discussions
Antu Saha, Mehedi Sun, Oscar Chaparro
During issue resolution, software developers rely on issue reports to discuss solutions for defects, feature requests, and other changes. These discussions contain proposed solutio…
From Absolute to Relative Code Comprehensibility Prediction
Nadeeshan De Silva, Martin Kellogg, Oscar Chaparro
Automatically predicting code comprehensibility could support tasks such as refactoring and code review. Existing metrics correlate poorly with human comprehension, motivating ML m…
Decoding the Issue Resolution Process in Practice via Issue Report Analysis: A Case Study of Firefox
Antu Saha, Oscar Chaparro
Effectively managing and resolving software issues is critical for maintaining and evolving software systems. Development teams often rely on issue trackers and issue reports to tr…
Resource-Efficient & Effective Code Summarization
Saima Afrin, Joseph Call, Khai-Nguyen Nguyen +2
Code Language Models (CLMs) have demonstrated high effectiveness in automating software engineering tasks such as bug fixing, code generation, and code documentation. This progress…