APSEC 2022
Tue 6 - Fri 9 December 2022
Fri 9 Dec 2022 13:35 - 13:55 at Room1 - Source Code Analysis 2 Chair(s): Yoshiki Higo

It is generally accepted in Software Engineering that code clones – often the result of copy-and-paste of existing code – result in poorer maintainability of software systems. Consequently, a variety of techniques have been devised to detect cloned code in software systems and alert developers of duplicated code. Most techniques operate at the source-code level and require some combination of pretty-printing, tokenization and abstraction in order to improve the comparison of code fragments over purely string-based techniques. Avoiding some of the issues of source-code based approaches, we are investigating the effectiveness of using various similarity measures on Bytecode to identify code clones in Java-based systems in this work. The results of our evaluation on selected Java systems indicate that instruction sequences can be used to effectively detect identical code clones. Especially, we achieved the best performance when using the normalized edit distance among applied similarity measures.

Fri 9 Dec

Displayed time zone: Osaka, Sapporo, Tokyo change

13:00 - 14:00
Source Code Analysis 2Technical Track / ERA - Early Research Achievements at Room1
Chair(s): Yoshiki Higo Osaka University
13:00
20m
Paper
Diff Feature Matching Network in Refactoring DetectionBest Paper Award
Technical Track
Tan Liang , Christoph Bockisch Philipps-Universität Marburg
13:20
15m
Paper
Reusing My Own Code: Preliminary Results for Competitive Coding in Jupyter Notebooks
ERA - Early Research Achievements
Natanon Ritta Mahidol University, Tasha Settewong Mahidol University, Raula Gaikovina Kula Nara Institute of Science and Technology, Chaiyong Rakhitwetsagul Mahidol University, Thailand, Thanwadee Sunetnanta Mahidol University, Kenichi Matsumoto Nara Institute of Science and Technology
13:35
20m
Paper
An Experimental Comparison of Clone Detection Techniques using Java Bytecode
Technical Track
Jean-Guy Schneider Monash University, Sung Une (Sunny) Lee CSIRO's Data61