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Guest editorial: special issue on predictive models for software quality

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journal contribution
posted on 2018-05-03, 15:18 authored by Leandro L. Minku, Ayşe B. Bener, Burak Turhan
[First paragraph] Software systems are increasingly large and complex, making activities related to ensuring software quality increasingly difficult. In this context, techniques able to automatically retrieve knowledge from software data in order to improve software quality are highly desirable. Predictive modelling has been showing promising results in this area. For instance, it can be used to learn the relationship between features retrieved from software processes, software usage or software itself and certain properties of interest, e.g., the presence of bugs, the likelihood of changes leading to crashes and the presence of code smells. Such knowledge can be particularly useful to improve the quality of large and complex systems.

History

Citation

Software Quality Journal, 2018, pp. 1-3

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Informatics

Version

  • AM (Accepted Manuscript)

Published in

Software Quality Journal

Publisher

Springer Verlag (Germany)

issn

0963-9314

eissn

1573-1367

Copyright date

2018

Available date

2019-04-16

Publisher version

https://link.springer.com/article/10.1007/s11219-018-9409-7

Notes

The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.;There was no peer review for this article, as it is the description of a special issue organised by the author et al. So, the pre-review is the same as the final article.

Language

en

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