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Empirical Software Engineering
Erschienen in: Empirical Software Engineering 2/2020

28.01.2020

Cross-version defect prediction: use historical data, cross-project data, or both?

verfasst von: Sousuke Amasaki

Erschienen in: Empirical Software Engineering | Ausgabe 2/2020

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Abstract

Context

Although a long-running project has experienced many releases, removing defects from a product is still a challenge. Cross-version defect prediction (CVDP) regards project data of prior releases as a useful source for predicting fault-prone modules based on defect prediction techniques. Recent studies have explored cross-project defect prediction (CPDP) that uses the project data from outside a project for defect prediction. While CPDP techniques and CPDP data can be diverted to CVDP, its effectiveness has not been investigated.

Objective

To investigate whether CPDP approaches and CPDP data are useful for CVDP. The investigation also compared the usage of prior release data.

Method

We chose a style of replication of a previous comparative study on CPDP approaches.

Results

Some CPDP approaches could improve the performance of CVDP. The use of the latest prior release was the best choice. If one has no CVDP data, the use of CPDP data for CVDP was found to be effective.

Conclusions

1) Some CPDP approaches could improve CVDP, 2), if one can access project data from the latest release, project data from older releases would not bring clear benefit, and 3) even if one has no CVDP data, appropriate CPDP approaches would be able to deliver quality prediction with CPDP data.
Vorheriger Artikel Code Localization in Programming Screencasts
Nächster Artikel Deriving a usage-independent software quality metric

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Fußnoten
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Metadaten
Titel
Cross-version defect prediction: use historical data, cross-project data, or both?
verfasst von
Sousuke Amasaki
Publikationsdatum
28.01.2020
Verlag
Springer US
Erschienen in
Empirical Software Engineering / Ausgabe 2/2020
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI
https://doi.org/10.1007/s10664-019-09777-8

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