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Gergő Balogh

Publications and source records attributed to Gergő Balogh.

3 recordsLinked to original sources

What Does It Mean and Why Should I Bother? Motivating Students to Write Better Commit Messages

This paper reports on a locally motivated mixed-methods case study addressing a teaching-related suspicion held by software engineering instructors: that commit messages written by students frequently fail to serve their intended communicative role. To examine this suspicion empirically, we analyzed commit messages from student and industrial case-study projects using a partial replication of an established commit-message quality taxonomy. The results confirm that communication and quality issues occur recurrently in both contexts, substantiating the instructors' initial concern. Motivated by this finding, we devised What Do You Mean? (WDYM), a lightweight, role-based educational game intended to surface and address commit-message communication breakdowns within the constraints of university coursework. Analysis of gameplay observations and participant surveys shows that WDYM is effective in raising awareness and fostering reflection on commit-message communication issues, although it provides limited evidence of immediate or sustained improvement in commit-message writing practices. Taken together, the study presents WDYM as a useful, though imperfect, context-bound intervention for addressing a locally observed instructional problem, without claiming general applicability beyond the studied setting.

cs.SE↗

Show Your Title! A Scoping Review on Verbalization in Software Engineering with LLM-Assisted Screening

Understanding how software developers think, make decisions, and behave remains a key challenge in software engineering (SE). Verbalization techniques (methods that capture spoken or written thought processes) offer a lightweight and accessible way to study these cognitive aspects. This paper presents a scoping review of research at the intersection of SE and psychology (PSY), focusing on the use of verbal data. To make large-scale interdisciplinary reviews feasible, we employed a large language model (LLM)-assisted screening pipeline using GPT to assess the relevance of over 9,000 papers based solely on titles. We addressed two questions: what themes emerge from verbalization-related work in SE, and how effective are LLMs in supporting interdisciplinary review processes? We validated GPT's outputs against human reviewers and found high consistency, with a 13\% disagreement rate. Prominent themes mainly were tied to the craft of SE, while more human-centered topics were underrepresented. The data also suggests that SE frequently draws on PSY methods, whereas the reverse is rare.

cs.SE↗

On the Integration of Spectrum-Based Fault Localization Tools into IDEs

Spectrum-Based Fault Localization (SBFL) is a technique to be used during debugging, the premise of which is that, based on the test case outcomes and code coverage, faulty code elements can be automatically detected. SBFL is popular among researchers because it is lightweight and easy to implement, and there is a lot of potential in it when it comes to research that aims to improve its effectiveness. Despite this, the technique cannot be found in contemporary development and debugging tools, only a handful of research prototypes are available. Reasons for this can be multiple, including the algortihms' sub-optimal effectiveness and other technical weaknesses. But, also the lack of clear functional and non-functional requirements for such a tool, either standalone or integrated into IDEs. In this paper, we attempt to provide such a list in form of recommendations, based on surveying the most popular SBFL tools and on our own researchers' and tool builders' experience.

cs.SE↗