On the adoption and effects of source code reuse on defect proneness and maintenance effort

• Published in: Empirical software engineering : an international journal 2024-02, Vol.29 (1), p.20, Article 20
• Main Authors: Giordano, Giammaria, Festa, Gerardo, Catolino, Gemma, Palomba, Fabio, Ferrucci, Filomena, Gravino, Carmine
• Format: Article
• Language: English
• Subjects: Code reuse; Compilers; Computer Science; Design defects; Evolution; Impact analysis; Inheritances; Interpreters; Maintenance; Object oriented programming; Programming Languages; Software Engineering/Programming and Operating Systems; Software reuse; Source code; Special Issue on Registered Reports
• ISSN: 1382-3256; 1573-7616
• DOI: 10.1007/s10664-023-10408-6

Software reusability mechanisms, like inheritance and delegation in Object-Oriented programming, are widely recognized as key instruments of software design that reduce the risks of source code being affected by defects, other than to reduce the effort required to maintain and evolve source code. Previous work has traditionally employed source code reuse metrics for prediction purposes, e.g., in the context of defect prediction. However, our research identifies two noticeable limitations of the current literature. First, still little is known about the extent to which developers actually employ code reuse mechanisms over time. Second, it is still unclear how these mechanisms may contribute to explaining defect-proneness and mainten0ance effort during software evolution. We aim at bridging this gap of knowledge, as an improved understanding of these aspects might provide insights into the actual support provided by these mechanisms, e.g., by suggesting whether and how to use them for prediction purposes. We propose an exploratory study, conducted on 12 Java projects–over 44,900 commits–of the Defects4J dataset, aiming at (1) assessing how developers use inheritance and delegation during software evolution; and (2) statistically analyzing the impact of inheritance and delegation on fault proneness and maintenance effort. Our results let emerge various usage patterns that describe the way inheritance and delegation vary over time. In addition, we find out that inheritance and delegation are statistically significant factors that influence both source code defect-proneness and maintenance effort.