Demo Data from EDBT 2026 / reviewers in the wild / expert
Yagnik Suchak
dblp:202/8430
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 87% Software maintenance and evolution · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering › mining software repositories › commit analysis
commit classification |
0.3 | 1 | 2017 | GitcProc: a tool for processing and classifying GitHub commits · ISSTA 2017 |
Empirical software engineering
mining software repositories |
0.3 | 1 | 2017 | GitcProc: a tool for processing and classifying GitHub commits · ISSTA 2017 |
Methods — techniques the papers use, named apart from their topics
regular expression matching · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | GitcProc: a tool for processing and classifying GitHub commitsabstractSites such as GitHub have created a vast collection of software artifacts that researchers interested in understanding and improving software systems can use. Current tools for processing such GitHub data tend to target project metadata and avoid source code processing, or process source code in a manner that requires significant effort for each language supported. This paper presents GitcProc, a lightweight tool based on regular expressions and source code blocks, which downloads projects and extracts their project history, including fine-grained source code information and development time bug fixes. GitcProc can track changes to both single-line and block source code structures and associate these changes to the surrounding function context with minimal set up required from users. We demonstrate GitcProc's ability to capture changes in multiple languages by evaluating it on C, C++, Java, and Python projects, and show it finds bug fixes and the context of source code changes effectively with few false positives. Casey Casalnuovo, Yagnik Suchak, Baishakhi Ray, Cindy Rubio-González |
ISSTA | 2 |