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A Systematic Literature Review of Machine Learning Applications in Software Engineering

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Book cover Proceedings of the 5th International Conference on Big Data and Internet of Things (BDIoT 2021)

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Abstract

Machine Learning (ML) has been a concern in Software Engineering (SE) over the past years. However, how to use ML and what it can offer for SE is still subject to debate among researchers. This paper investigates the application of ML in SE. The goal is to identify the used algorithms, the addressed topics and the main findings. It performs a Systematic Literature Review (SLR) of peer-reviewed studies published between 1995 and 2020. Data extracted from the studies show that ML algorithms are of great practical value in the different activities of software development process, especially “Software specification” and “Software validation” since “Software bug prediction” and “Software quality improvement” are the most recurring research topics.

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Authors and Affiliations

  1. ENSIAS, Mohammed V University of Rabat, Rabat, Morocco

    Houda Mezouar & Abdellatif El Afia

Authors
  1. Houda Mezouar
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  2. Abdellatif El Afia
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Correspondence to Houda Mezouar .

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Editors and Affiliations

  1. ENSIAS, Mohammed V University, Rabat, Morocco

    Mohamed Lazaar

  2. UNILEHAVRE, UNIROUEN, Normandie Université, Le Havre, France

    Claude Duvallet

  3. Vrije Universiteit Brussel, Brussels, Belgium

    Abdellah Touhafi

  4. ENSA, Abdelmalek Essaâdi University, Tetuan, Morocco

    Mohammed Al Achhab

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Mezouar, H., Afia, A.E. (2022). A Systematic Literature Review of Machine Learning Applications in Software Engineering. In: Lazaar, M., Duvallet, C., Touhafi, A., Al Achhab, M. (eds) Proceedings of the 5th International Conference on Big Data and Internet of Things. BDIoT 2021. Lecture Notes in Networks and Systems, vol 489. Springer, Cham. https://doi.org/10.1007/978-3-031-07969-6_24

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