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Extracting corrective actions from code repositories

Published: 17 October 2022 Publication History

Abstract

Simple detection of bugs, defects or anomalies during software development is not enough - it is necessary to apply corrective actions to eliminate them. To find out whether an anomaly exists in any software, we can measure the quality attributes using software metrics. The main goal of this paper was to find out and explain how to meaningfully attribute metrics to useful corrective actions.

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T. Ohno. 1988. Toyota Production System: Beyond Large-Scale Production. Taylor & Francis. https://books.google.ru/books?id=7_-67SshOy8C
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Yogesh Singh, Pradeep Kumar Bhatia, and Omprakash Sangwan. 2007. A review of studies on machine learning techniques. International Journal of Computer Science and Security 1, 1 (2007), 70--84.
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Zhiyuan Wan, Xin Xia, David Lo, and Gail C Murphy. 2019. How does machine learning change software development practices? IEEE Transactions on Software Engineering 47, 9 (2019), 1857--1871.

Cited By

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  • (2024)Towards a mixed human–machine creativityJournal of Cultural Cognitive Science10.1007/s41809-024-00146-68:2(151-165)Online publication date: 19-Jul-2024
  • (2024)Machine Learning in Society: Prospects, Risks, and BenefitsPhilosophy & Technology10.1007/s13347-024-00782-437:3Online publication date: 31-Jul-2024
  • (2023)The Impact of Cognitive Dissonance on the Software Development Process2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS)10.1109/ICSESS58500.2023.10293134(42-46)Online publication date: 17-Oct-2023

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cover image ACM Conferences
MSR '22: Proceedings of the 19th International Conference on Mining Software Repositories
May 2022
815 pages
ISBN:9781450393034
DOI:10.1145/3524842
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 17 October 2022

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Author Tags

  1. anomaly
  2. corrective action
  3. information retrieval
  4. project management
  5. repository
  6. software metrics

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  • Short-paper

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Cited By

View all
  • (2024)Towards a mixed human–machine creativityJournal of Cultural Cognitive Science10.1007/s41809-024-00146-68:2(151-165)Online publication date: 19-Jul-2024
  • (2024)Machine Learning in Society: Prospects, Risks, and BenefitsPhilosophy & Technology10.1007/s13347-024-00782-437:3Online publication date: 31-Jul-2024
  • (2023)The Impact of Cognitive Dissonance on the Software Development Process2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS)10.1109/ICSESS58500.2023.10293134(42-46)Online publication date: 17-Oct-2023
  • (2022)AI and society: a virtue ethics approachAI & SOCIETY10.1007/s00146-022-01545-539:3(1127-1140)Online publication date: 10-Sep-2022

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