An Empirical Analysis of Git Commit Logs for Potential Inconsistency in Code Clones
This program is tentative and subject to change.
Code clones are code snippets that are identical or similar to other snippets within the same or different files. They are often created through copy-and-paste practices and modified during development and maintenance activities.
Since a pair of code clones, known as a clone pair, has a possible logical coupling between them, it is expected that changes to each snippet are made simultaneously (co-changed) and consistently.
There is extensive research on code clones, including studies related to the co-change of clones; however, detailed analysis of commit logs for code clone pairs has been limited.
In this paper, we investigate the commit logs of code snippets from clone pairs, using the git-log command to extract changes to cloned code snippets. We analyzed 45 repositories owned by the Apache Software Foundation on GitHub and addressed three research questions regarding commit frequency, co-change ratio, and commit patterns.
Our findings indicate that (1) on average, clone snippets are changed infrequently, typically only two or three times throughout their lifetime, (2) the ratio of co-changes is about half of all clone changes, with 10-20% of co-changed commits being concerning (potentially inconsistent), and (3) 35-65% of all clone pairs being classified as concerning clone pairs (potentially inconsistent clone pairs). These results suggest the need for a consistent management system through the commit timeline of clones.
An Empirical Analysis of Git Commit Logs for Potential Inconsistency in Code Clones (SCAM2024_Clone_Commit_Analysis_Camera_Ready (5).pdf) | 356KiB |
This program is tentative and subject to change.
Mon 7 OctDisplayed time zone: Mountain Time (US & Canada) change
13:30 - 15:00 | |||
13:30 22mTalk | An Empirical Analysis of Git Commit Logs for Potential Inconsistency in Code Clones Research Track File Attached | ||
13:52 22mTalk | 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 | ||
14:15 22mTalk | Toward Interactive Optimization of Source Code Differences: An Empirical Study of Its Performance Research Track | ||
14:37 22mResearch paper | Catching Smells in the Act: A GitHub Actions Workflow Investigation Research Track Ali Khatami Delft University of Technology, Cédric Willekens Delft University of Technology, Andy Zaidman Delft University of Technology Pre-print |