A Useful Resource for Defect Prediction Models

Ragneala, Roxana

アイテム詳細

登録内容を編集ファイル形式で保存

一時保存へ追加

タグ情報を表示リリース履歴を表示詳細要約

公開

学位論文

A Useful Resource for Defect Prediction Models

MPS-Authors

/persons/resource/persons45239

Ragneala, Roxana
International Max Planck Research School, MPI for Informatics, Max Planck Society;

External Resource

There are no locators available

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

フルテキスト (公開)

公開されているフルテキストはありません

付随資料 (公開)

There is no public supplementary material available

引用

Ragneala, R. (2009). A Useful Resource for Defect Prediction Models. Master Thesis, Universität des Saarlandes, Saarbrücken.

引用: https://hdl.handle.net/11858/00-001M-0000-0027-BA8D-E

要旨

Predicting likely software defects in the future is valuable for project managers when planning resource allocation for software testing. But building prediction models using only code metrics may not be suffice for accurate results. In this work, we investigate the value of code history metrics that can be collected from the project's version archives for the purpose of defect prediction. Our results suggest that prediction models built using code history metrics outperform those using traditional code metrics only.