Bridging the Gap Between Academia and Industry in Machine Learning Software Defect Prediction: Thirteen Considerations
S Stradowski, L Madeyski - 2023 38th IEEE/ACM International …, 2023 - ieeexplore.ieee.org
This experience paper describes thirteen considerations for implementing machine learning
software defect prediction (ML SDP) in vivo. Specifically, we provide the following report on …
software defect prediction (ML SDP) in vivo. Specifically, we provide the following report on …
Costs and Benefits of Machine Learning Software Defect Prediction: Industrial Case Study
S Stradowski, L Madeyski - Companion Proceedings of the 32nd ACM …, 2024 - dl.acm.org
Context: Our research is set in the industrial context of Nokia 5G and the introduction of
Machine Learning Software Defect Prediction (ML SDP) to the existing quality assurance …
Machine Learning Software Defect Prediction (ML SDP) to the existing quality assurance …
Integration of AI in the Realm of Software Development
J Bhuvana, V Ranjan… - … Conference on Advances …, 2023 - ieeexplore.ieee.org
Software engineering has increasingly utilized" Artificial Intelligence"(AI) to improve self-
organizing IT solutions. This research aims to fill the existing void in the thorough …
organizing IT solutions. This research aims to fill the existing void in the thorough …