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Extracting Common and Variable Code using the LCS Algorithm for Migration to SPLE

  • Taeyoung Kim*
  • , Jihyun Lee
  • , Sungwon Kang
  • *Corresponding author for this work
  • Jeonbuk National University
  • Korea Advanced Institute of Science and Technology

Research output: Contribution to conferenceConference paperpeer-review

Abstract

The LCS (Longest Common Subsequence) algorithm is a well-known algorithm that finds the longest subsequence from two different strings while preserving the relative order between the characters that make up the strings. When migrating from source code to Software Product Line Engineering (SPLE), the process of identifying commonality and variability is a crucial step and many studies have applied the LCS algorithm for this process, but this algorithm can be applied only to two sources although the cases of three or more sources are common. This study proposes a method that extracts common and variable code lines from three or more sources. The proposed method consists of the preprocessing phase that divides sources into sections by reflecting the characteristics of their programming languages, and the phase for applying the LCS algorithm. To evaluate the proposed method, we applied it to ArgoUML-SPL and compared the result with the original platform of ArgoUML-SPL, which confirmed that common and variable code lines were effectively identified.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 47th Annual Computers, Software, and Applications Conference, COMPSAC 2023
EditorsHossain Shahriar, Yuuichi Teranishi, Alfredo Cuzzocrea, Moushumi Sharmin, Dave Towey, AKM Jahangir Alam Majumder, Hiroki Kashiwazaki, Ji-Jiang Yang, Michiharu Takemoto, Nazmus Sakib, Ryohei Banno, Sheikh Iqbal Ahamed
PublisherIEEE Computer Society
Pages1004-1005
Number of pages2
ISBN (Electronic)9798350326970
DOIs
StatePublished - 2023
Event47th Annual IEEE Computers, Software, and Applications Conference, COMPSAC 2023 - Hybrid, Torino, Italy
Duration: 2023.06.262023.06.30

Publication series

NameProceedings - International Computer Software and Applications Conference
Volume2023-June
ISSN (Print)0730-3157

Conference

Conference47th Annual IEEE Computers, Software, and Applications Conference, COMPSAC 2023
Country/TerritoryItaly
CityHybrid, Torino
Period23.06.2623.06.30

Keywords

  • commonality and variability extraction
  • extractive approach
  • LCS algorithm
  • software product line
  • SPL migration

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems
  • Data Science

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