How Good Is Genetic Programming at Predicting Changes and Defects?

One of the main problems practitioners have to deal with is the identification of change and defect proneness of source code entities (e.g., Classes). During the last years a lot of techniques have been employed for predicting change and defect proneness of classes. In this paper we study the capabi...

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Veröffentlicht in:2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing S. 544 - 548
1. Verfasser: Marinescu, Cristina
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.09.2014
Schlagworte:
changes
Data mining
defects
empirical software engineering
Genetic programming
Java
Measurement
metrics
Predictive models
Software
Software engineering
software repositories
source code
ISBN:9781479984473, 1479984477
Online-Zugang:Volltext
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Zusammenfassung:One of the main problems practitioners have to deal with is the identification of change and defect proneness of source code entities (e.g., Classes). During the last years a lot of techniques have been employed for predicting change and defect proneness of classes. In this paper we study the capabilities of Genetic Programming for performing the addressed problem by measuring the precision and recall of the obtained predictions.
ISBN:9781479984473
1479984477
DOI:10.1109/SYNASC.2014.78