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Using Machine Intelligence to Prioritise Code Review Requests
Ericsson, SWE.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering. Ericsson /Blekinge Institute of Technology.ORCID iD: 0000-0002-7220-9570
2021 (English)In: Proceedings of the 2021 International Conference on Software Engineering (ICSE'21), IEEE Computer Society, 2021, p. 11-20Conference paper, Published paper (Refereed)
Abstract [en]

Modern Code Review (MCR) is the process of reviewing new code changes that need to be merged with an existing codebase. As a developer, one may receive many code review requests every day, i.e., the review requests need to be prioritised. Manually prioritising review requests is a challenging and time-consuming process. To address the above problem, we conductedan industrial case study at Ericsson aiming at developing a toolcalled Pineapple, which uses a Bayesian Network to prioritise code review requests. To validate our approach/tool, we deployed it in a live software development project at Ericsson, wherein more than 150 developers develop a telecommunication product.We focused on evaluating the predictive performance, feasibility, and usefulness of our approach. The results indicate that Pineapple has competent predictive performance (RMSE = 0.21 and MAE = 0.15). Furthermore, around 82.6% of Pineapple’s users believe the tool can support code review request prioritisation by providing reliable results, and around 56.5% of the users believe it helps reducing code review lead time. As future work, we plan to evaluate Pineapple’s predictive performance, usefulness, and feasibility through a longitudinal investigation. Index Terms—Modern Code Review, Prioritisation,

Place, publisher, year, edition, pages
IEEE Computer Society, 2021. p. 11-20
Series
2021 IEEE/ACM 43RD INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN PRACTICE (ICSE-SEIP 2021)
Keywords [en]
Modern Code Review, Prioritisation, Bayesian Networks, Machine Intelligence, Machine Learning, Machine Reasoning
National Category
Computer Sciences Computer Systems
Identifiers
URN: urn:nbn:se:bth-21043DOI: 10.1109/ICSE-SEIP52600.2021.00010ISI: 000684234800002Scopus ID: 2-s2.0-85115709756ISBN: 978-0-7381-4669-0 (print)OAI: oai:DiVA.org:bth-21043DiVA, id: diva2:1526947
Conference
43rd IEEE/ACM International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP) / May 20-30, Madrid, Spain
Note

open access

Available from: 2021-02-09 Created: 2021-02-09 Last updated: 2021-10-10Bibliographically approved

Open Access in DiVA

Pineapple_ICSE_2021(861 kB)140 downloads
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Type fulltextMimetype application/pdf

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Britto, Ricardo

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