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Automating Software Changes Via Recommendation Systems, Xiaoyu Liu

Computer Science and Engineering Theses and Dissertations

As the complexity of software systems is growing tremendously, it came with increasingly sophisticated data provided during development. The systematic and large-scale accumulation of software engineering data opened up new opportunities that infer information appropriately can be helpful to software development in a given context. This type of intelligent software development tools came to be known as recommendation systems.

Recommendation Systems in Software Change (RSSCs) share commonalities with conventional recommendation systems: mainly in their usage model, the usual reliance on data mining, and in the predictive nature of their functionality. So a major challenge for designing RSSCs is to automatically …