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..
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data
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datasets
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input
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lib
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resources
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scripts
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vis
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A graph(ical) approach towards Bounded Contexts.ipynb
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Architecture Governance Example.ipynb
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Building Higher-Level Abstractions of Source Code.ipynb
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Calculating Indentation-based Complexity.ipynb
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Calculating the Structural Similarity of Test Cases.ipynb
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Checking the modularization based on changes (3D Version).ipynb
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Checking the modularization of software systems by analyzing co-changing source code files.ipynb
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Code Maat Python.ipynb
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Committer Distribution.ipynb
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Creating a fun dataset.ipynb
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Defect Analysis using pandas.ipynb
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Developers' Habits (IntelliJ Edition).ipynb
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Developers' Habits (Linux Edition).ipynb
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Effective interactive data visualization with pandas and pygal.ipynb
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Finding tested code with jQAssistant.ipynb
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Fitness Function for Detecting Cyclic Package Dependencies.ipynb
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Fitness Function for Detecting Race Conditions.ipynb
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Fixing code that is actually used with Tablesaw.ipynb
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Generate fake data for Spring PetClinic with Pandas and Faker.ipynb
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Generating Synthetic Data based on a Git Log.ipynb
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Grouping co-changing code - fossology.ipynb
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Grouping co-changing code.ipynb
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Identifying lost knowledge in the Linux kernel source code.ipynb
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Impact Analysis with jQAssistant and Neo4j.ipynb
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Indentation Complexity.ipynb
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Java Type Dependency Analysis.ipynb
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Joint Sources - Using Pandas as ETL tool.ipynb
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Knowledge Islands.ipynb
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Mini-Tutorial Git Log Analyse mit Python und Pandas.ipynb
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Mini-Tutorial Git Log Analysis with Python and Pandas.ipynb
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Mining SonarQube.ipynb
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Mining performance HotSpots with JProfiler, jQAssistant, Neo4j and Pandas.ipynb
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No-Go-Areas.ipynb
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Production Coverage Demo Notebook.ipynb
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Production Coverage Demo with Tablesaw and BeakerX.ipynb
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Proof of Concept - Adding comments to classes in jQAssistant.ipynb
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Quantifying the Java Development Kit.ipynb
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Race Condition Demo Notebook.ipynb
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Read in semi-structured data with pandas.ipynb
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Read in semi-structured data.ipynb
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Reading a Git log file output with Pandas.ipynb
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Reading a Git repo's commit history with Pandas efficiently.ipynb
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SWOT analysis for spotting worthless code.ipynb
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Similarity visualizations PCA AHC.ipynb
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Spotting co-changing files.ipynb
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Spotting performance issues with vmstat.ipynb
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Storing Git commit information into Pandas' DataFrame.ipynb
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Structural Test Case Similarity.ipynb
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Tracking Reengineerings under the Hood.ipynb
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Travis CI Build Breaker Analysis.ipynb
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Visualize Developer Contributions with Stream Graphs.ipynb
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Visualizing Production Coverage with JaCoCo, Pandas and D3.ipynb
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Visualizing and Clustering of the Structural Similarities of Test Cases.ipynb
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Word Cloud Computing.ipynb
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Word count distribution of commit messages.ipynb
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demo_pandas_jqassistant.ipynb
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Getting Started with Python Pandas.md
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README.md
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