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In this workshop, we’ll analyze software systems and surrounding processes as well as teams to uncover weaknesses in development and operation—solely based on data. As a foundation, we’ll use best practices and methodologies from the area of data science.
We’ll use open-source tools for our analyses. With this approach, you can continue to use the same tools free of charge after the workshop. Due to the large community behind them, you’ll have a wealth of tips and further knowledge at your disposal for your very own analyses!
Learning Goals
We’ll offer you an introduction to the following topics:
- Use standard tools from the fields of data science for the analysis of software data.
- Identify problems in software development in a data-driven, systematic and structured way.
- Derive actionable conclusions from analysis results.
- Communicate analyses and insights that are also understandable to non-technical people.
Contents
- Introduction to Software Analytics (0,5h)
- Data sources for analyses in software development
- Challenges while analyzing software data
- Introduction to Reproducible Data Science (0,5h)
- Data analysis with Jupyter, Python, pandas & Co.
- Outlook on graph-based software analysis and machine learning on code
- Interactive, hands-on projects and katas (4h)
Example of Use
The video below shows an example of an analysis of a larger software project. The analysis demonstrates advanced export functions from the version control system Git, techniques for reading semi-structured data, and visualizing data with the data analysis tool pandas.
Target Audience
Software developers, software architects, and anyone who ever wanted to analyze data and has at least basic experience with software development.
You should have a basic understanding of a programming language (variables, methods, loops, assignments, etc.).
Organization
- Duration: 2 half days, each 2,5h + 0,5h break
- Max. participants: 12
- Online tools used: Zoom, Miro, Browser
Why you should attend
- Make more informed decisions in the future! Provide information that is not pulled out of thin air but based on actual figures, data, and facts.
- Systematically keep track of your systems! Being able to analyze software comprehensively and automated is essential for today’s system landscapes' sustainable evolution.
- Apply your acquired knowledge also outside of software development! Move your company forward with your data-oriented analyses in other areas as well.