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ARISE: A framework for automated risk identification in Scrum using memory-based recommendation
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DOI：10.1016/j.jss.2026.112987.png)
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Abstract
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• A knowledge-based framework is proposed to recommend relevant risks in agile software projects. • Project profiles and standardized risk descriptions enable reuse across similar Scrum initiatives. • The k-NN-based recommendation system achieved 63% precision, 80% recall, and 68% F1-score. • Integration with the Scrum lifecycle fosters early risk identification and continuous control. • A TAM-based user study with 24 practitioners indicated high acceptance and perceived usefulness (91.67%).
Keywords:
Agile software development
Risk management
Risk recommendation system
Knowledge reuse
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