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10.1109/ICSM.2015.7332470guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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On the role of developer's scattered changes in bug prediction

Published: 29 September 2015 Publication History

Abstract

The importance of human-related factors in the introduction of bugs has recently been the subject of a number of empirical studies. However, such factors have not been captured yet in bug prediction models which simply exploit product metrics or process metrics based on the number and type of changes or on the number of developers working on a software component. Previous studies have demonstrated that focused developers are less prone to introduce defects than non focused developers. According to this observation, software components changed by focused developers should also be less error prone than software components changed by less focused developers. In this paper we capture this observation by measuring the structural and semantic scattering of changes performed by the developers working on a software component and use these two measures to build a bug prediction model. Such a model has been evaluated on five open source systems and compared with two competitive prediction models: the first exploits the number of developers working on a code component in a given time period as predictor, while the second is based on the concept of code change entropy. The achieved results show the superiority of our model with respect to the two competitive approaches, and the complementarity of the defined scattering measures with respect to standard predictors commonly used in the literature.

Cited By

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  • (2022)Profiling developers to predict vulnerable code changesProceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering10.1145/3558489.3559069(32-41)Online publication date: 7-Nov-2022
  • (2022)Predictive Models in Software Engineering: Challenges and OpportunitiesACM Transactions on Software Engineering and Methodology10.1145/350350931:3(1-72)Online publication date: 9-Apr-2022
  • (2018)Predicting developers' IDE commands with machine learningProceedings of the 15th International Conference on Mining Software Repositories10.1145/3196398.3196459(82-85)Online publication date: 28-May-2018
  • Show More Cited By

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Published In

cover image Guide Proceedings
ICSME '15: Proceedings of the 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME)
September 2015
611 pages
ISBN:9781467375320

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IEEE Computer Society

United States

Publication History

Published: 29 September 2015

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Cited By

View all
  • (2022)Profiling developers to predict vulnerable code changesProceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering10.1145/3558489.3559069(32-41)Online publication date: 7-Nov-2022
  • (2022)Predictive Models in Software Engineering: Challenges and OpportunitiesACM Transactions on Software Engineering and Methodology10.1145/350350931:3(1-72)Online publication date: 9-Apr-2022
  • (2018)Predicting developers' IDE commands with machine learningProceedings of the 15th International Conference on Mining Software Repositories10.1145/3196398.3196459(82-85)Online publication date: 28-May-2018
  • (2017)The impact of using regression models to build defect classifiersProceedings of the 14th International Conference on Mining Software Repositories10.1109/MSR.2017.4(135-145)Online publication date: 20-May-2017

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