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MeSRAM - A method for assessing robustness of measurement programs in large software development organizations and its industrial evaluation

Journal article
Authors Miroslaw Staron
Wilhelm Meding
Published in Journal of Systems and Software
Volume 113
Issue March
Pages 76-100
ISSN 0164-1212
Publication year 2016
Published at Institutionen för data- och informationsteknik, Software Engineering (GU)
Pages 76-100
Language en
Keywords Measurement program, Software engineering, Metrics, Case study, fault prediction, measurement systems, metrics, agile, quality, collaboration, performance, complexity, framework, Computer Science, ACTICE, PT 11st International Conference on Design, User Experience, and Usability (DUXU)/14th, OCEEDINGS25th International Conference on Software Engineering (ICSE 2003), MAY 03-10, 2003, rtland, or, p564, OGRAMMING, XP 201314th International Conference on Agile Processes in Software Engineering and, VELOPMENT5th International Conference on Software Quality Days (SWQD), JAN 15-17, 2013, Vienna, OCESS AND PRODUCT MEASUREMENT (IWSM-MENSURA)Joint Conference of the 23rd International, actice, v23, p89, RUM (ISESS 97) - EMERGING INTERNATIONAL STANDARDS, PROCEEDINGS3rd IEEE International, rtland, or, p641
Subject categories Computer and Information Science


Measurement programs in large software development organizations contain a large number of indicators, base and derived measures to monitor products, processes and projects. The diversity and the number of these measures causes the measurement programs to become large, combining multiple needs, measurement tools and organizational goals. For the measurement program to effectively support organization's goals, it should be scalable, automated, standardized and flexible - i.e. robust. In this paper we present a method for assessing the robustness of measurement programs. The method is based on the robustness model which has been developed in collaboration between seven companies and a university. The purpose of the method is to support the companies to optimize the value obtained from the measurement programs and their cost. We evaluated the method at the seven companies and the results from applying the method to each company quantified the robustness of their programs, reflecting the real-world status of the programs and pinpointed strengths and improvements of the programs. (C) 2015 Elsevier Inc. All rights reserved.

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