Software practitioners make technical and business decisions based on their understanding of software projects. This understanding is grounded in their own experiences, but can be augmented by studying various kinds of software development artifacts, including source code, bug reports, version control meta-data, test cases, usage logs, etc. Unfortunately, the software development knowledge contained in these artifacts is typically not organized in the way that is immediately accessible from and useful to developers and stakeholders' decision making needs. To make easy handing the large amount of data faced when accessing development knowledge, software analytics - use of analysis, data, and systematic reasoning for making decisions - have been recently emerged as an emerging field of modern data analysis.

The third International Workshop on Software Analytics (SWAN 2017) will provide an informal interactive forum for researchers and participants to exchange ideas and experiences, streamline research on software analytics, identify some common ground of their work, share lessons and challenges, thereby articulating a vision for the future of software analytics.