Software Analytics with Data Science on Software Data

Data Science has demonstrated its value in extracting insights from business data, raising the question: Why not apply these principles to our software systems’ data? In this talk, I’ll introduce you to the world of Software Analytics. We’ll explore how to extract valuable insights from software data by using tools and techniques from data science to get rid of big, systemic problems in our software systems.

You’ll learn how to leverage scientific thinking, manage the analysis process, and apply literate statistical programming to analyze software systems in an understandable way. Or to put it in the words of software developers: We automate the analysis of large software systems using open-source tools like Jupyter Notebook, Python, pandas, jQAssistant, and Neo4j. I’ll also demonstrate through live-coding how we can gain new insights from data sources like Git repositories, performance measurements, or source code.

Join me in this session to acquire your starter kit for uncovering deeply hidden issues and change the way of improving systems with data-driven software analysis!

Markus Harrer

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Markus Harrer is a software engineer who’s passionate about improving the way we do software development. He specializes in the analysis of software data such as source code, application performance data or version control repositories to show the underlying problems of the symptoms we face on the surface. He is an active contributor in communities on the topics of Software Analytics, software architecture, software modernization and Wardley Maps. He is also an accredited trainer for the iSAQB Foundation Level and the Advanced Level Module IMPROVE.

Slides

harrer.pdf