Kairós: using context histories for predictions and recommendations in projects time management Online publication date: Fri, 15-Jul-2022
by Felipe Chaves Rodrigues; Alexsandro Souza Filippetto; Robson Kerschner De Lima; Wesllei Felipe Heckler; Jorge Luis Victória Barbosa
International Journal of Agile Systems and Management (IJASM), Vol. 15, No. 1, 2022
Abstract: Time management is an important part of a project. Cost and quality are directly affected by any changes in deadlines. Therefore, this paper presents Kairós, a computational model for prediction and recommendation in project schedules. We made a systematic mapping study on the research topics, and the gaps found were the base for the creation of the model. The model makes recommendations to the manager proactively according to best practices in project management, learning with the approval or rejection of each recommendation. We performed an evaluation through a prototype using simulated use cases with real data from a software development company. The results showed that the model was able to predict with a precision of 94% whether a task would be completed with delay, with 86% accuracy. The results demonstrated that the use of context histories contributes to project management.
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