Journal of Software: Evolution and Process

Cover image for Vol. 24 Issue 4

June 2012

Volume 24, Issue 4

Pages 375–454

  1. Research Articles

    1. Top of page
    2. Research Articles
    1. Formalizing interactive staged feature model configuration (pages 375–400)

      Ebrahim Bagheri, Tommaso Di Noia, Dragan Gasevic and Azzurra Ragone

      Version of Record online: 15 FEB 2011 | DOI: 10.1002/smr.534

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      We have developed a maximal covering specialization algorithm that creates a sound and complete specialization of a software product line feature model based on stakeholders' hard constraints, which is complemented by the maximal covering configuration algorithm that orders and creates a configuration given the soft constraints of the stakeholders. The focus of these techniques is to achieve maximum desirability for the developed feature model configuration for the stakeholders. Copyright © 2011 John Wiley & Sons, Ltd.

    2. Process attribute rating and sensitivity analysis in process assessment (pages 401–419)

      Ho-Won Jung

      Version of Record online: 1 JUN 2011 | DOI: 10.1002/smr.545

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      The ISO/IEC 15504 standards do notprovide an aggregation method of a set of practiceachievements into the process attribute (PA) rating that are utilized to determine capability level. This study addresses a simple additive weighting methodbased on the performance value and weights of practices implemented. Then, sensitivity analysis is conducted to evaluate how much achange in the weight or performance value of an implemented practice will affect and alter the current PArating.

    3. Integration test effort in sap r/3 systems (pages 421–435)

      P. A. van de Griend and R. J. Kusters

      Version of Record online: 8 JUN 2011 | DOI: 10.1002/smr.546

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      We study change characteristics across test systems and production systems. The magnitude of a solitary change, in terms of touched objects, is not correlated to integration test effort. Clustering a set of solitary changes produces a positive correlation between cluster size and integration test effort.

    4. A review of methods for evaluation of maturity models for process improvement (pages 436–454)

      Yeni Yuqin Li Helgesson, Martin Höst and Kim Weyns

      Version of Record online: 25 AUG 2011 | DOI: 10.1002/smr.560

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      In this paper, a mapping study of the literature on the evaluation of maturity models is presented. The identified papers are mapped to a proposed framework for maturity models and classified according to six categories (the maturity model under evaluation, type of evaluation, relation of the evaluators/authors to the maturity model, objectivity, main purpose and size). The result of this mapping study is a clear overview of how the evaluation of maturity models has been carried out. Further, the evaluation of the maturity models in the Capability Maturity Model family is discussed in more detail.