Locating bugs without looking back
- Submitting institution
-
The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1459769
- Type
- D - Journal article
- DOI
-
10.1007/s10515-017-0226-1
- Title of journal
- Automated Software Engineering
- Article number
- -
- First page
- 383
- Volume
- 25
- Issue
- 3
- ISSN
- 0928-8910
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper in a top software engineering journal presents a state-of-the-art algorithm to suggest where to fix a bug. It requires less data than other approaches and yet outperforms them. A pilot trial in a company (project lead contact available) showed a reduction of 30% in the average time to fix a bug. Huawei will fund a project (2021-2024; PI: Yu; Project manager, Huawei, details on request) to further develop this approach, which is also a key component of the EPSRC STRIDE project (2020-2023), to test how automated tools and humans best work together.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
