Asst. Prof. @drexelCCI @drexeluniv | Research on mining software repositories, empirical software engineering | Director of @Soar_Lab
Joined February 2014
- Tweets1.3K
- Following520
- Followers1.3K
- Likes7.7K
Preetha Chatterjee retweeted
📝 New article: "Psycholinguistic Analyses in Software Engineering Text: A Systematic Mapping Study" by Amirali Sajadi, Kostadin Damevski, Preetha Chatterjee
👉 Get your copy at doi.org/10.1016/j.infsof.202…
We are disappointed to miss he 40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025) in person this year in Seoul, but our presentation is now available online.
If you are interested in the work, here’s the recording:
youtube.com/watch?v=qvHNUfB3…
LLMs can repair code, but often miss the broader context developers use every day.
We propose a 3-layer knowledge injection framework that incrementally feeds LLMs with bug, repository, and project knowledge.
Preprint of our ASE '25 paper: arxiv.org/pdf/2506.24015
@ASEconf2019
LLMs can repair code, but often miss the broader context developers use every day.
We propose a 3-layer knowledge injection framework that incrementally feeds LLMs with bug, repository, and project knowledge.
Preprint of our ASE '25 paper: arxiv.org/pdf/2506.24015
@ASEconf2019
Evaluated on 314 real-world Python bugs, we observed consistent gains in both #fixed and Pass@k scores for Llama 3.3 and GPT-4o-mini, demonstrating a 23% improvement over prior work.
Preetha Chatterjee retweeted
AI-Powered Commit Explorer (APCE). arxiv.org/abs/2507.16063
Preetha Chatterjee retweeted
Congrats to all the exceptional students, faculty and professional staff who were recognized for their hard work at our annual College Awards Cermony. 👏
View the full album: ow.ly/nJIn50W5Kb7
Headed to @ICSEconf? Don’t miss two exciting talks from our lab!
📌 MSR (Apr 29 | 14–15:30)
"Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution"
arxiv.org/abs/2501.11709
📌 NLBSE (Apr 27 | 11–12:30)
Analyzing Toxicity in OSS
arxiv.org/abs/2412.13133
Sharing the open access link to our recent EMSE paper: link.springer.com/article/10…
LLMs are great at generating code, but are they silently spreading vulnerabilities? TLDR: Yes.
In our latest EMSE paper, we look into: when developers unknowingly share vulnerable code with LLMs, do these models proactively raise security red flags? 🧵
arxiv.org/abs/2502.14202
Preetha Chatterjee retweeted
Benchmarks are our measures of progress. Or are they?
Looking forward to exploring promises & perils of measuring tool capabilities @SBFTworkshop'25! Thanks for the invite!
👩🏭 sbft25.github.io/ (co-located w/ ICSE'25 in Ottawa)
📅 28.04. 11:00 GMT-4 (Also, live on Twitch)
LLMs are great at generating code, but are they silently spreading vulnerabilities? TLDR: Yes.
In our latest EMSE paper, we look into: when developers unknowingly share vulnerable code with LLMs, do these models proactively raise security red flags? 🧵
arxiv.org/abs/2502.14202
As a preliminary solution to this problem, we built a CLI tool prototype that integrates static analysis with LLM prompting, aiming to make AI code suggestions more secure by design.
Delighted to share that our paper, led by my PhD advisee Ramtin Ehsani, “Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution,” has been accepted to the Research Track of MSR 2025.
Preprint: soar-lab.github.io//papers/M…
These gaps—such as missing context or unclear instructions—can significantly hinder the effectiveness of the interaction and slow progress. We identify key textual and code-related heuristics that are associated with successful issue resolution.