Love, Joy, Anger, Sadness, Fear, and Surprise: SE Needs Special Kinds of AI: A Case Study on Text Mining and SE
arXiv:2004.11005v18 citations
AI Analysis
This addresses the challenge of improving team productivity and code quality in software engineering by leveraging emotional analysis, though it appears incremental as it applies existing text mining methods to a new domain.
The paper tackles the problem of monitoring developer emotions in software engineering to identify when a codebase needs help, using text mining to analyze what code makes developers happiest or angriest.
Do you like your code? What kind of code makes developers happiest? What makes them angriest? Is it possible to monitor the mood of a large team of coders to determine when and where a codebase needs additional help?