SE 5520 Software Analytics 3.0 Credits
Software repositories archive valuable software engineering data, such as source code, execution traces, historical code changes, mailing lists, bug reports, and chats. This data contains a wealth of information about a project’s status and history. By doing data science on software repositories, researchers can gain an understanding of software development practices, and practitioners can better manage, maintain, and evolve complex software projects. Software analytics techniques may be applied to various tasks such as code summarization, code comment generation, question-answer extraction, sentiment analysis, etc. This course provides students with an understanding of and hands-on experience with ML and NLP techniques that represent knowledge and solve existing SE problems.
Repeat Status: Not repeatable for credit
Prerequisites: CS 5010 [Min Grade: D] or CS 501 [Min Grade: D]