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Authors: Anıl Aydın and Ayça Tarhan

Affiliation: Hacettepe University, Turkey

Keyword(s): Defect Prediction, Iterative Software Development, Rayleigh Model, Linear Regression Model, Lessons Learned.

Related Ontology Subjects/Areas/Topics: Service-Oriented Software Engineering and Management ; Software Engineering ; Software Quality Management

Abstract: One of the biggest problems that software organizations encounter is specifying the resources required and the duration of projects. Organizations that record the number of defects and the effort spent on fixing these defects are able to correctly predict the latent defects in the product and the effort required to remove these latent defects. The use of reliability models reported in the literature is typical to achieve this prediction, but the number of studies that report defect prediction models for iterative software development is scarce. In this article we present a case study which predicts the defectiveness of new releases in an iterative, civil project where defect arrival phase data is not recorded. We investigated Linear Regression Model and Rayleigh Model one of the statistical reliability model that contain time information, to predict the module level and project level defectiveness of the new releases of an iterative project through the iterations. The models were created by using 29 successive releases for the project level and 15 successive releases for the module level defect density data. This article explains the procedures that were applied to generate the defectiveness models and the lessons learned from the studies. (More)

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Paper citation in several formats:
Aydın, A. and Tarhan, A. (2014). Investigating Defect Prediction Models for Iterative Software Development When Phase Data is Not Recorded - Lessons Learned. In Proceedings of the 9th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE; ISBN 978-989-758-030-7; ISSN 2184-4895, SciTePress, pages 48-58. DOI: 10.5220/0004888300480058

@conference{enase14,
author={Anıl Aydın. and Ay\c{C}a Tarhan.},
title={Investigating Defect Prediction Models for Iterative Software Development When Phase Data is Not Recorded - Lessons Learned},
booktitle={Proceedings of the 9th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE},
year={2014},
pages={48-58},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004888300480058},
isbn={978-989-758-030-7},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - Investigating Defect Prediction Models for Iterative Software Development When Phase Data is Not Recorded - Lessons Learned
SN - 978-989-758-030-7
IS - 2184-4895
AU - Aydın, A.
AU - Tarhan, A.
PY - 2014
SP - 48
EP - 58
DO - 10.5220/0004888300480058
PB - SciTePress