11 citations · 60 across the 17 of their papers we have counts for
17 papers
Integrating Crash Report Mining and LLMs for Bug Localization and Repair: An Industrial Report
Marcos Medeiros, Uirá Kulesza, Christoph Treude +5
Analyzing crash-report bugs in large-scale industrial software systems requires substantial maintenance effort, particularly in production environments where developers must handle…
Effective Code Membership Inference for Code Completion Models via Adversarial Prompts
Yuan Jiang, Zehao Li, Shan Huang +3
Membership inference attacks (MIAs) on code completion models offer an effective way to assess privacy risks by inferring whether a given code snippet was part of the training data…
How Developers Interact with AI: A Taxonomy of Human-AI Collaboration in Software Engineering
Christoph Treude, Marco A. Gerosa
Artificial intelligence (AI), including large language models and generative AI, is emerging as a significant force in software development, offering developers powerful tools that…
Bot-Driven Development: From Simple Automation to Autonomous Software Development Bots
Christoph Treude, Christopher M. Poskitt
As software development increasingly adopts automation, bot-driven development (BotDD) represents a transformative shift where bots assume proactive roles in coding, testing, and p…
StagedVulBERT: Multi-Granular Vulnerability Detection with a Novel Pre-trained Code Model
Yuan Jiang, Yujian Zhang, Xiaohong Su +2
The emergence of pre-trained model-based vulnerability detection methods has significantly advanced the field of automated vulnerability detection. However, these methods still fac…
An Empirical Study of API Misuses of Data-Centric Libraries
Akalanka Galappaththi, Sarah Nadi, Christoph Treude
Developers rely on third-party library Application Programming Interfaces (APIs) when developing software. However, libraries typically come with assumptions and API usage constrai…
Can LLMs Replace Manual Annotation of Software Engineering Artifacts?
Toufique Ahmed, Premkumar Devanbu, Christoph Treude +1
Experimental evaluations of software engineering innovations, e.g., tools and processes, often include human-subject studies as a component of a multi-pronged strategy to obtain gr…
An Empirical Study of Static Analysis Tools for Secure Code Review
Wachiraphan Charoenwet, Patanamon Thongtanunam, Van-Thuan Pham +1
Early identification of security issues in software development is vital to minimize their unanticipated impacts. Code review is a widely used manual analysis method that aims to u…
Documenting Ethical Considerations in Open Source AI Models
Haoyu Gao, Mansooreh Zahedi, Christoph Treude +2
Background: The development of AI-enabled software heavily depends on AI model documentation, such as model cards, due to different domain expertise between software engineers and…
Prioritising GitHub Priority Labels
James Caddy, Christoph Treude
Communities on GitHub often use issue labels as a way of triaging issues by assigning them priority ratings based on how urgently they should be addressed. The labels used are dete…
LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead
Junda He, Christoph Treude, David Lo
Integrating Large Language Models (LLMs) into autonomous agents marks a significant shift in the research landscape by offering cognitive abilities that are competitive with human…
Creative and Correct: Requesting Diverse Code Solutions from AI Foundation Models
Scott Blyth, Markus Wagner, Christoph Treude
AI foundation models have the capability to produce a wide array of responses to a single prompt, a feature that is highly beneficial in software engineering to generate diverse co…
The Impact Of Bug Localization Based on Crash Report Mining: A Developers' Perspective
Marcos Medeiros, Uirá Kulesza, Roberta Coelho +3
Developers often use crash reports to understand the root cause of bugs. However, locating the buggy source code snippet from such information is a challenging task, mainly when th…
Enhancing Source Code Representations for Deep Learning with Static Analysis
Xueting Guan, Christoph Treude
Deep learning techniques applied to program analysis tasks such as code classification, summarization, and bug detection have seen widespread interest. Traditional approaches, howe…
Improving Automated Code Reviews: Learning from Experience
Hong Yi Lin, Patanamon Thongtanunam, Christoph Treude +1
Modern code review is a critical quality assurance process that is widely adopted in both industry and open source software environments. This process can help newcomers learn from…
Encoding Version History Context for Better Code Representation
Huy Nguyen, Christoph Treude, Patanamon Thongtanunam
With the exponential growth of AI tools that generate source code, understanding software has become crucial. When developers comprehend a program, they may refer to additional con…
Application of Collaborative Learning Paradigms within Software Engineering Education: A Systematic Mapping Study
Rita Garcia, Christoph Treude, Andrew Valentine
Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE e…