Investigating the Significance of Bellwether Effect to improve Software Effort Estimation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Detail(s)

Original languageEnglish
Title of host publication2017 IEEE International Conference on Software Quality, Reliability and Security (QRS)
PublisherIEEE
Pages340-351
ISBN (Electronic)978-1-5386-0592-9
Publication statusPublished - Aug 2017

Publication series

NameIEEE International Conference on Software Quality, Reliability and Security (QRS)
PublisherIEEE

Conference

TitleThe 2017 IEEE International Conference on Software Quality, Reliability, and Security
Location Faculty of Information Technology, Czech Technical University
PlaceCzech Republic
CityPrague
Period25 - 29 July 2017

Abstract

Bellwether effect refers to the existence of exemplary projects (called the Bellwether) within a historical dataset to be used for improved prediction performance. Recent studies have shown an implicit assumption of using recently completed projects (referred to as moving window) for improved prediction accuracy. In this paper, we investigate the Bellwether effect on software effort estimation accuracy using moving windows. The existence of the Bellwether was empirically proven based on six postulations. We apply statistical stratification and Markov chain methodology to select the Bellwether moving window. The resulting Bellwether moving window is used to predict the software effort of a new project. Empirical results show that Bellwether effect exist in chronological datasets with a set of exemplary and recently completed projects representing the Bellwether moving window. Result from this study has shown that the use of Bellwether moving window with the Gaussian weighting function significantly improve the prediction accuracy.

Research Area(s)

  • Bellwether Effect, Bellwether moving window, Chronological dataset, Markov chains

Citation Format(s)

Investigating the Significance of Bellwether Effect to improve Software Effort Estimation. / Mensah, Solomon; Keung, Jacky; MacDonell, Stephen G.; Bosu, Michael F.; Bennin, Kwabena E.

2017 IEEE International Conference on Software Quality, Reliability and Security (QRS). IEEE, 2017. p. 340-351 8009938 (IEEE International Conference on Software Quality, Reliability and Security (QRS)).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)