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Data mining for validation in software engineering: An example
KTH, Superseded Departments, Computer and Systems Sciences, DSV.ORCID iD: 0000-0002-1780-0683
2004 (English)In: International journal of software engineering and knowledge engineering, ISSN 0218-1940, Vol. 14, no 4, 407-427 p.Article in journal (Refereed) Published
Abstract [en]

Consider two independently done software engineering studies that used different approaches to cover some of the same subject area, such as software maintenance. Although done differently and for different purposes, to what extent can each study serve as a validation of the other? Within the scope of the subject area overlap, data mining can be applied to provide a quantitative assessment. This paper reports on the data mining that attempted to cross validate two independently done and published software engineering studies of software maintenance, one on a corrective maintenance maturity model, and the other on an objective classification of software maintenance activities. The data mining established that each of the two independently done studies effectively and very strongly validates the other.

Place, publisher, year, edition, pages
2004. Vol. 14, no 4, 407-427 p.
Keyword [en]
software maintenance activities, problem management, corrective maintenance, maintenance typology, empirical measurement, software engineering validation, maintenance
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:kth:diva-23737DOI: 10.1142/S0218194004001725ISI: 000223985000004OAI: oai:DiVA.org:kth-23737DiVA: diva2:342436
Note
QC 20100525 QC 20110926. 15th International Conference on Software Engineering and Knowledge Engineering. San Francisco, CA. JUL 01-03, 2003Available from: 2010-08-10 Created: 2010-08-10 Last updated: 2017-12-12Bibliographically approved

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Kajko-Mattsson, Mira Miroslawa

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