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AI in Software Engineering: A Survey on Project Management Applications

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arxiv 2307.15224 v1 pith:SHHJ2T6H submitted 2023-07-27 cs.SE

Talia Crawford , Scott Duong , Richard Fueston , Ayorinde Lawani , Samuel Owoade , Abel Uzoka , Reza M. Parizi , Abbas Yazdinejad This is my paper · ORCID
classification cs.SE
keywords engineeringsoftwareintelligencemanagementpossibleprojectsurveythen
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Artificial Intelligence (AI) refers to the intelligence demonstrated by machines, and within the realm of AI, Machine Learning (ML) stands as a notable subset. ML employs algorithms that undergo training on data sets, enabling them to carry out specific tasks autonomously. Notably, AI holds immense potential in the field of software engineering, particularly in project management and planning. In this literature survey, we explore the use of AI in Software Engineering and summarize previous works in this area. We first review eleven different publications related to this subject, then compare the surveyed works. We then comment on the possible challenges present in the utilization of AI in software engineering and suggest possible further research avenues and the ways in which AI could evolve with software engineering in the future.

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Cited by 2 Pith papers

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  1. GenAI-Enabled Backlog Grooming in Agile Software Projects: An Empirical Study

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    A human-in-the-loop GenAI Jira tool found duplicate backlog items with 100 percent precision and roughly 45 percent less time per duplicate in a five-person study.

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    A laser SLAM framework that models each object as a Gaussian-process contour, updated recursively and inferred jointly with the robot pose in a Bayesian framework.

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