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ORIGINAL RESEARCH article

Front. Artif. Intell.
Sec. AI in Business
Volume 7 - 2024 | doi: 10.3389/frai.2024.1443956
This article is part of the Research Topic Business Transformation through AI-enabled Technologies View all 3 articles

The use of artificial intelligence for automatic analysis and reporting of software defects

Provisionally accepted
Mark Esposito Mark Esposito 1,2*Saman Sarbazvatan Saman Sarbazvatan 3Terence Tse Terence Tse 2Gabriel Silva-Atencio Gabriel Silva-Atencio 4
  • 1 Harvard University, Cambridge, United States
  • 2 Hult International Business School, Cambridge, Massachusetts, United States
  • 3 École des ponts ParisTech (ENPC), Marne-la-Vallée, Île-de-France, France
  • 4 Latin American University of Science and Technology, San José, San Jose, Costa Rica

The final, formatted version of the article will be published soon.

    The COVID-19 pandemic marked a before and after in the business world, causing a growing demand for the use of applications, reducing delivery times, budgets and improving the quality of products, where Artificial Intelligence (AI) is taking a relevant role in the improvement of these processes, since it incorporates mathematical models that allow analyzing the logical structure of the systems, to detect and reduce errors or failures in real-time. The objective of this study was to determine the most relevant aspects to be considered for detecting software defects using

    Keywords: artificial intelligence, Software Development, Automation testing, Software defect, Software failure

    Received: 04 Jun 2024; Accepted: 18 Nov 2024.

    Copyright: © 2024 Esposito, Sarbazvatan, Tse and Silva-Atencio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Mark Esposito, Harvard University, Cambridge, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.