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Validating software...
Validating software measures using action research a method and industrial experiences
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- Antinyan, Vard (författare)
- Department of Computer Science and Engineering, Chalmers, University of Gothenburg, Gothenburg, Sweden
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- Staron, Miroslaw (författare)
- Department of Computer Science and Engineering, Chalmers, University of Gothenburg, Gothenburg, Sweden
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- Sandberg, Anna (författare)
- Ericsson, Gothenburg, Sweden
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- Hansson, Jörgen, 1970- (författare)
- Högskolan i Skövde,Institutionen för informationsteknologi,Forskningscentrum för Informationsteknologi
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(creator_code:org_t)
- 2016-06
- 2016
- Engelska.
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Ingår i: EASE '16. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450336918
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Validating software measures for using them in practice is a challenging task. Usually more than one complementary validation methods are applied for rigorously validating software measures: Theoretical methods help with defining the measures with expected properties and empirical methods help with evaluating the predictive power of measures. Despite the variety of these methods there still remain cases when the validation of measures is difficult. Particularly when the response variables of interest are not accurately measurable and the practical context cannot be reduced to an experimental setup the abovementioned methods are not effective. In this paper we present a complementary empirical method for validating measures. The method relies on action research principles and is meant to be used in combination with theoretical validation methods. The industrial experiences documented in this paper show that in many practical cases the method is effective. © 2016 ACM.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Software Engineering (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Action research
- Software measure
- Validation
- Software engineering
- Empirical method
- Industrial experience
- Predictive power
- Software measures
- Theoretical methods
- Theoretical validations
- Industrial research
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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EASE '16
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