Detection of Seed Methods for Quantification of Feature Confinement

Andrzej Olszak, Eric Bouwers, Bo Nørregaard Jørgensen, Joost Visser

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

143 Downloads (Pure)

Abstract

The way features are implemented in source code has a significant influence on multiple quality aspects of a software system. Hence, it is important to regularly evaluate the quality of feature confinement. Unfortunately, existing approaches to such measurement rely on expert judgement for tracing links between features and source code which hinders the ability to perform cost-efficient and consistent evaluations over time or on a large portfolio of systems.
In this paper, we propose an approach to automating measurement of feature confinement by detecting the methods which play a central role in implementations of features, the so-called seed methods, and using them as starting points for a static slicing algorithm. We show that this approach achieves the same level of performance compared to the use of manually identified seed methods. Furthermore we illustrate the scalability of the approach by tracking the evolution of feature scattering and tangling in an open-source project over a period of ten years.
Original languageEnglish
Title of host publicationTOOL Europe 2012
EditorsCarlo A. Furia, Sebastian Nanz
Number of pages17
VolumeLNCS 7304
PublisherSpringer
Publication date2012
Pages252–268
ISBN (Print)978-3-642-30560-3
Publication statusPublished - 2012

Fingerprint

Dive into the research topics of 'Detection of Seed Methods for Quantification of Feature Confinement'. Together they form a unique fingerprint.

Cite this