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awesome-software-analytics
Curated list of awesome resources and links about Software Analytics
https://github.com/feststelltaste/awesome-software-analytics
- Thomas Zimmermann, Peter Weisgerber, Stephan Diehl, and Andreas Zeller: Mining Version Histories to Guide Software Changes (2004) - A real classic about the idea of using software version control systems to guide software changes (awarded with the ICSE 10 Years Most Influential Paper Award 2014).
- Tim Menzies, Christian Bird, Thomas Zimmermann, Wolfram Schulte, and Ekrem Kocaganeli: The inductive software engineering manifesto: principles for industrial data mining (2011) - Makes you aware of various aspects that you have to consider if you want to implement Software Analytics in the industry.
- Andrew Begel and Thomas Zimmermann: Analyze this! 145 questions for data scientists in software engineering (2013) - a kind of meta-level paper about the questions that arise during software development which may be answered with Software Analytics.
- Ahmed E. Hassan and Tao Xie: Software intelligence: the future of mining software engineering data (2010) - discusses (among other topics) which types of software data can be used with existing data mining techniques.
- Tim Menzies and Thomas Zimmermann. Software Analytics: So What? (2013) - contains a critical discussion on how far has Software Analytics got in the recent years. Includes a short overview of influential papers as well.
- Tamer Mohamed Abdellatif, Luiz Fernando Capretz, Danny Ho: Software Analytics to Software Practice - A Systematic Literature Review (2015) - looks at past papers that applied Software Analytics in practice.
- João Caldeiraa, Fernando Brito e Abreua, Jorge Cardosob, Toacy Oliveira: Software Development Analytics in Practice - A Systematic Literature Review (2020) - provides an aggregate view of Software Development Analytics studies from 2010 to 2019.
- Canadian Summer School on Practical Analyses of Software Engineering Data (2011) - a collection of talks about early adoptions of Software Analytics in practice. _February 2022: unfortunately, this site is gone now. Link leads to archive.org._
- Prof. Dr. Jürgen Döllner: Automated Visual Software Analytics (2015) - Very detailed and precise explanations with focus on the visualization of software analyses.
- Christian Bird, Tim Menzies, Thomas Zimmermann: The Art and Science of Analyzing Software Data. Morgan Kaufmann (2015) - a comprehensive work by some Software Analytics luminaries providing a good fundament for Software Analytics.
- Tim Menzies, Laurie Williams, Thomas Zimmermann: Perspectives on Data Science for Software Engineering. Morgan Kaufmann (2016) - a collection of short articles in the area of Software Analytics. Good and neutral discussion of the advances in the field and the limits of data-driven approaches.
- Adam Tornhill: Software X-Ray. Pragmatic Programmers (2018) - a book full of great software analysis on real code bases.
- Greg Wilson: Using Data Science to Explore Software Development (2017) - discusses the application of Data Science onto software data to answer questions that arise in software development projects.
- Prof. Dr. Rainer Koschke: Software Analytics in komplexen Software-Projekten - introductory article on Software Analytics (written in German).
- Thomas Zimmermann: The productive software engineer (2019) - an interview with Thomas Zimmermann about his current work on software analysis at Microsoft.
- Elmar Juergens: Mining Repository Data to Debug Software Development Teams (2016) - shows how version control systems can reveal communication problems in development teams.
- StephanLaRocca: Dependency Analysis of Legacy Applications with Oracle Graph (2021 - demonstrates the usage of graph technology to analyze legacy systems to find bounded contexts, support effective testing, and identify the most important business processes within an application.
- Dirk Mahler: Yes We Scan! Software Analysis Using jQAssistant (2015) - software analysis of industry software projects using a graph database.
- Nicolas Mervaillie: Fix Your Microservice Architecture Using Graph Analysis (2019) - graph-based software analysis is used to analyze a distributed system.
- Margaret-Anne Storey: Lies, Damned Lies and Software Analytics (2015) - an overview of the history and goals of Software Analytics. I especially like the part where Margaret talks about the risks of Software Analytics like data quality issues, missing trustworthiness of results, and ethical concerns.
- Oliver Tigges, Philipp Haußleiter: Software Dependency Analysis with Graph Databases (2015) - software libraries dependency analysis by using a graph database
- Adam Tornhill: Prioritizing Technical Debt as if Time and Money Matters (2019) - a fresh look at version control data mining to uncover behavioral patterns of development organizations.
- Nicki Watt: Explore your Microservices Architecture with Graph Theory & Network Science (2020) - usage of graph-based algorithms to spot problems in large distrubuted software systems.
- Thomas Zimmermann: Software Productivity Decoded: How Data Science helps to Achieve More (2018) - talk with an introduction to Software Analytics and its application in Microsoft.
- Matt Eland: Visualizing Code in Jupyter Notebooks with Pandas and Plotly (2022) - in this data analytics demo, Matt utilized Jupyter Notebook, Python, Plotly, and Pandas to analyze an open source game project. He also provides the dataset to get your own analysis started.
- Markus Harrer: Software Analytics Workshop (2019) - a repository with a guided tour through first software analysis using Data Science approaches und tools.
- Markus Harrer: Software Analytics Katas (2021) - small challenges designed to train analytical thinking and the use of data-driven software analysis techniques.
- Analysis-Tools.dev - static analysis tools for many programming languages, build tools, config files and more.
- Awesome Open Source - Profilers - tools for in-depth runtime analysis.
- OpenAPM - lists various Application Performance Management tools that can help you to find performance problems.
- Awesome Empirical Software Engineering - a curated repository of software engineering repository mining data sets.
- Awesome Network Analysis - a curated list of awesome network analysis resources. If you want to dig deeper into graph-based analysis of software, you can find plenty of resources in this list.
- Awesome Machine Learning On Source Code - cool links & research papers related to Machine Learning applied to source code (MLonCode).
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