CompAS: A new approach to commonality and variability analysis with applications in computer assisted orthopaedic surgery

Douta, Gisèle; Talib, Haydar; Nierstrasz, Oscar; Langlotz, Frank (2009). CompAS: A new approach to commonality and variability analysis with applications in computer assisted orthopaedic surgery. Information and software technology, 51(2), pp. 448-459. London: Butterworth 10.1016/j.infsof.2008.05.017

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In rapidly evolving domains such as Computer Assisted Orthopaedic Surgery (CAOS) emphasis is often put first on innovation and new functionality, rather than in developing the common infrastructure needed to support integration and reuse of these innovations. In fact, developing such an infrastructure is often considered to be a high-risk venture given the volatility of such a domain. We present CompAS, a method that exploits the very evolution of innovations in the domain to carry out the necessary quantitative and qualitative commonality and variability analysis, especially in the case of scarce system documentation. We show how our technique applies to the CAOS domain by using conference proceedings as a key source of information about the evolution of features in CAOS systems over a period of several years. We detect and classify evolution patterns to determine functional commonality and variability. We also identify non-functional requirements to help capture domain variability. We have validated our approach by evaluating the degree to which representative test systems can be covered by the common and variable features produced by our analysis.

Item Type: Journal Article (Original Article)
Division/Institute: 08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor: Nierstrasz, Oscar Marius
ISSN: 0950-5849
Publisher: Butterworth
Language: English
Submitter: Factscience Import
Date Deposited: 04 Oct 2013 15:22
Last Modified: 17 Mar 2015 22:49
Publisher DOI: 10.1016/j.infsof.2008.05.017
Web of Science ID: 000261919900016
URI: http://boris.unibe.ch/id/eprint/37164 (FactScience: 207112)

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