The Art and Science of Analyzing Software Data

is a researcher in the empirical software engineering group at Microsoft Research. He is primarily interested in the relationship between software design, social dynamics, and processes in large development projects. He has studied software development teams at Microsoft, IBM, and in the Open Source realm, examining the effects of distributed development, ownership policies, and the ways in which teams complete software tasks. He has published in the top Software Engineering venues and is the recipient of the ACM SIGSOFT distinguished paper award. Tim Menzies, Full Professor, CS, NC State and a former software research chair at NASA. He has published 200+ publications, many in the area of software analytics. He is an editorial board member (1) IEEE Trans on SE; (2) Automated Software Engineering journal; (3) Empirical Software Engineering Journal. His research includes artificial intelligence, data mining and search-based software engineering. He is best known for his work on the PROMISE open source repository of data for reusable software engineering experiments. is a researcher in the Research in Software Engineering (RiSE) group at Microsoft Research, adjunct assistant professor at the University of Calgary, and affiliate faculty at University of Washington. He is best known for his work on systematic mining of version archives and bug databases to conduct empirical studies and to build tools to support developers and managers. He received two ACM SIGSOFT Distinguished Paper Awards for his work published at the ICSE '07 and FSE '08 conferences.

• Past, Present, and Future of Analyzing Software DataPart 1 TUTORIAL-TECHNIQUESMining Patterns and Violations Using Concept AnalysisAnalyzing Text in Software ProjectsSynthesizing Knowledge from Software Development ArtifactsA Practical Guide to Analyzing IDE Usage DataLatent Dirichlet Allocation: Extracting Topics from Software Engineering DataTools and Techniques for Analyzing Product and Process DataPART 2 DATA/PROBLEM FOCUSSEDAnalyzing Security DataA Mixed Methods Approach to Mining Code Review Data: Examples and a Study of Multicommit Reviews and Pull RequestsMining Android Apps for AnomaliesChange Coupling Between Software Artifacts: Learning from Past ChangesPART 3 STORIES FROM THE TRENCHESApplying Software Data Analysis in Industry Contexts: When Research Meets RealityUsing Data to Make Decisions in Software Engineering:Providing a Method to our MadnessCommunity Data for OSS Adoption Risk ManagementAssessing the State of Software in a Large Enterprise: A 12-Year RetrospectiveLessons Learned from Software Analytics in PracticePART 4 ADVANCED TOPICSCode Comment Analysis for Improving Software QualityMining Software Logs for Goal-Driven Root Cause AnalysisAnalytical Product Release PlanningPART 5 DATA ANALYSIS AT SCALE (BIG DATA)Boa: An Enabling Language and Infrastructure for Ultra-Large-Scale MSR StudiesScalable Parallelization of Specification Mining Using Distributed Computing