On the applicability of search-based algorithms for software change prediction

作     者：Malhotra, Ruchika Khanna, Megha 

作者机构：Delhi Technol Univ Dept Software Engn Delhi India Univ Delhi Sri Guru Gobind Singh Coll Commerce Delhi India 

出 版 物：《INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT》 (国际系统保证工程与管理杂志)

年 卷 期：2023年第14卷第1期

页      面：55-73页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 1202[管理学-工商管理] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0837[工学-安全科学与工程] 0823[工学-交通运输工程] 

主　　题：Change proneness Search based algorithms Software quality Object-oriented software 

摘      要：Numerous research studies have claimed that search-based algorithms have the potential to be effectively used in various software engineering domains. An important task in software organizations is to efficiently recognize change prone classes of a software, as it is crucial to plan efficient resource utilization and to take precautionary design measures as early as possible in the software product lifecycle. This assures development of good quality software products at lower costs. The current study attempts to evaluate the capability of search-based algorithms while developing prediction models for identification of the change prone classes in a software. Though previous literature has evaluated the use of statistical category and machine learning category of algorithms in this domain, the suitability of search-based algorithms needs extensive investigation in this area. Furthermore, the study compares the performance of search-based classifiers with statistical and machine learning classifiers, by empirically validating the results on fourteen open source data sets. The results indicate comparable and in some cases even better performance of search based algorithms in comparison to other evaluated categories of algorithms.