When you come across my blog, you may be thinking “What is this guy doing”? There are some weird analyses that have somehow to do with software development. But why all this?
Data Analysis in Software Development
jQAssistant: Cypher Query Examples
Here are some queries that I use regulary at meetups and conferences for showing some features of jQAssistant and Neo4j.
Video: Linux Git Log Analysis
Here is a short video that demonstrates how you can get some insights from the history of a Git repository using Jupyter Notebook, Python, pandas and matplotlib: We take a look at exporting the necessary data reading in the dataset
Calculating Indentation-based Complexity
In this blog post, I want to show you a nice complexity metric that works for most major programming languages that we use for our software systems – the indentation-based complexity metric.
Mini-Tutorial Git Log Analysis with Python and Pandas
This notebook is a simple mini-tutorial to introduce you to basic functions of Jupyter, Python, Pandas and matplotlib with the aim of analyzing software data. Therefore, the example is chosen in such a way that we come across the typical methods in a data analysis.
Mini-Tutorial: Git-Log-Analyse mit Python und Pandas (German)
Dieses Notebook ist ein einfach gehaltenes Mini-Tutorial zur Vorstellung grundlegender Funktionen von Jupyter, Python, Pandas und matplotlib, um ein Gefühl für die Analyse von Softwaredaten mit diesen Bibliotheken zu bekommen. Daher ist das gewählte Beispiel so gewählt, dass wir typische Aufgaben während einer Datenanalyse bearbeiten…
My talk at JAX 2018
Thanks for the active participation and great feedback! Here you can find the slides of my talk “Software Analytics for Practitioners” at JAX 2018 (mostly in German) as well as a place for further discussions and feedback…
SWOT analysis for spotting worthless code
In this short blog post, I want to show you an idea where you take some very detailed datasets from a software project and transform it into a representation where management can reason about…
Identifying lost knowledge in the Linux kernel source code
Knowing all about the software system we are developing is valuable, but too often a rare situation we are facing today. In times of software development experts shortages and stressful software projects, high turnover in teams leads quickly to lost knowledge about the source code…
Visualizing and Clustering of the Structural Similarities of Test Cases
In this blog post, I show how we can partly automate the process of identifying groups of similar test cases as well as how we can visualize those groups. The aim is to find test cases that test the same production code but shouldn’t do it…