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Team-related Features in Code Review Prediction Models
In this paper, we propose the use of team-related features to improve the performance of predictions that are helpful to build code reviewer recommenders, with our target predictions being the identification of reviewers that would participate in a review and the provided amount of feedback.
Explaining reputation assessments
Reputation is crucial to enabling human or software agents to select among alternative providers.
Quantitatively Assessing the Benefits of Model-driven Development in Agent-based Modeling and Simulation
The agent-based modeling and simulation (ABMS) paradigm has been used to analyze, reproduce, and predict phenomena related to many application areas.
A systematic review and taxonomy of explanations in decision support and recommender systems
With the recent advances in the field of artificial intelligence, an increasing number of decision-making tasks are delegated to software systems.
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