SCAM 2024
Mon 7 - Tue 8 October 2024
co-located with ICSME 2024
Mon 7 Oct 2024 13:47 - 14:03 at Fremont - Code Smells Chair(s): Tushar Sharma

A source code difference (diff) indicates changes made by comparing new and old source codes, and it can be utilized in code reviews to help developers understand the changes made to the code. Although many diff generation methods have been proposed, existing automatic methods may generate nonoptimal diffs, hindering reviewers from understanding the changes. In this paper, we propose an interactive approach to optimize diffs. Users can provide feedback for the points of a diff that should not be matched but are or parts that should be matched but are not. The edit graph is updated based on this feedback, enabling users to obtain a more optimal diff. We simulated our proposed method by applying a search algorithm to empirically assess the number of feedback instances required and the amount of diff optimization resulting from the feedback to investigate the potential of this approach. The results of 23 GitHub projects confirm that 92% of nonoptimal diffs can be addressed with less than four feedback actions in the ideal case.

Mon 7 Oct

Displayed time zone: Arizona change

13:30 - 15:00
Code SmellsResearch Track at Fremont
Chair(s): Tushar Sharma Dalhousie University
13:30
16m
Research paper
Catching Smells in the Act: A GitHub Actions Workflow InvestigationVideo Presentation
Research Track
Ali Khatami Delft University of Technology, Cédric Willekens Delft University of Technology, Andy Zaidman Delft University of Technology
Pre-print
13:47
16m
Research paper
Toward Interactive Optimization of Source Code Differences: An Empirical Study of Its Performance
Research Track
Tsukasa Yagi Tokyo Institute of Technology, Shinpei Hayashi Tokyo Institute of Technology
DOI Pre-print
14:04
16m
Research paper
On the Prevalence, Evolution, and Impact of Code Smells in Simulation Modelling Software
Research Track
Riasat Mahbub Dalhousie University, Masud Rahman Dalhousie University, Muhammad Ahsanul Habib Dalhousie University
14:21
16m
Research paper
An Empirical Analysis of Git Commit Logs for Potential Inconsistency in Code Clones
Research Track
Reishi Yokomori Nanzan University, Katsuro Inoue Nanzan University
Pre-print File Attached
14:40
20m
Live Q&A
Discussion (Code Smells)
Research Track