Predicting software reuse using machine learning techniques-A case study on open-source Java software systems.

ABSTRACT: Software reuse is an essential practice to increase efficiency and reduce costs in software production. Software reuse practices range from reusing artifacts, libraries, components, packages, and APIs. Identifying suitable software for reuse requires pinpointing potential candidates. However, there are no objective methods in place to measure software reuse. This makes it challenging to identify highly reusable software. Software reuse research mainly addresses two hurdles: 1) identifying reusable candidates effectively and efficiently, and 2) selecting high-quality software components that improve maintainability and extensibility. This paper proposes automating software reuse prediction by leveraging machine learning (ML) algorithms, enabling future research and practitioners to better i

SUBMITTER: Yeow MYH 

PROVIDER: S-EPMC11824963 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature