awesome-awesomeness/terminal/msr

                                                        Awesome Empirical Software Engineering !Awesome (https://awesome.re/badge.svg) (https://awesome.re)
A curated repository of data sets and tools that can be used for conducting evidence-based, data-driven research on software systems.
This research approach is often termed experimental, or empirical software engineering (https://en.wikipedia.org/wiki/Experimental_software_engineering).
Many of the data sets can also be useful in research using search-based software engineering (https://en.wikipedia.org/wiki/Search-based_software_engineering) methods.
The repository is named after the Mining Software Repositories (MSR) (https://www.msrconf.org/) conference series.
For examples of such work see the MSR conference's Hall of Fame (http://2016.msrconf.org/#/hall-of-fame).


- This list requires your input for its continuous improvement.
  Read the contribution guide (contributing.md) for instructions on how
  you can contribute.
  Alternatively, you can send me an email (mailto:dds@aueb.gr)
  if you find the process too cumbersome or confusing.
- For more awesome lists, see awesome (https://github.com/sindresorhus/awesome).

Contents
- Repositories (#repositories)
- Data Sets (#data-sets)
- Tools (#tools)
- Research Outlets (#research-outlets)

Repositories

- SIR (http://sir.unl.edu/portal/index.php) - Software-artifact infrastructure repository; Java, C, C++, and C# software together with test suites and fault data.
- PROMISE (http://promise.site.uottawa.ca/SERepository/datasets-page.html) - About 20 datasets related to software engineering research.
- FLOSSmole (https://flossmole.org/collection_details) - Collaborative collection and analysis of free/libre/open source project data.
- Zenodo (http://zenodo.org/) - Software data collections in CERN's open-access repository.
  - Software Engineering Artifacts Can Really Assist Future Tasks (http://zenodo.org/communities/seacraft)
  - Empirical Software Engineering (https://zenodo.org/communities/empirical-software-engineering/)
  - Mining Software Repositories (https://zenodo.org/communities/msr/)

Data Sets

- AndroidTimeMachine (https://androidtimemachine.github.io) - Graph-based dataset of commit history of 8,431 real-world Android apps.
- AndroZoo (https://androzoo.uni.lu/) - Collection of Android Applications.
- Bug Prediction Dataset (http://bug.inf.usi.ch/index.php) - Collection of models and metrics from Eclipse JDT Core, PDE UI, Equinox Framework, Lucene, Mylyn, and their histories.
- Code Reviews (http://kin-y.github.io/miningReviewRepo/) - Code reviews of OpenStack, LibreOffice, AOSP, Qt, Eclipse.
- CoREBench (http://www.comp.nus.edu.sg/%7Erelease/corebench/) - Collection of 70 realistically Complex Regression Errors that were systematically extracted from the repositories and bug reports of four 
open-source software projects: Make, Grep, Findutils, and Coreutils.
- Cryptocurrency GitHub Activity and Market Cap Dataset (https://rvantonder.github.io/CryptOSS/) - Activity such as commits, stars, prices, and market cap of over 200 cryptocurrency projects on GitHub over time.
Raw, historic data is also available (https://zenodo.org/record/2595588#.XRuzuBNKhSM).
- Defects4J (https://github.com/rjust/defects4j) - Collection of 395 reproducible bugs collected with the goal of advancing software testing research.
- Eclipse AERI stacktraces (http://download.eclipse.org/scava/datasets/aeri_stacktraces/aeri_stacktraces.html) - Collection of stacktraces of Exceptions encountered by users of the Eclipse IDE, as retrieved by 
the AERI reporting system.
- Enron Spreadsheets and Emails (https://figshare.com/articles/Enron_Spreadsheets_and_Emails/1221767) - All the spreadsheets and emails used in the paper 'Enron's Spreadsheets and Related Emails: A Dataset and 
Analysis'.
- Findbugs-maven (https://github.com/istlab/maven_bug_catalog) - Set of FindBugs reports for the Java projects of the Maven repository (https://maven.apache.org).
- GHTorrent (http://ghtorrent.org/) - Scalable, queriable, offline mirror of data offered through the GitHub REST API.
- GitHub Bug Dataset (http://www.inf.u-szeged.hu/~ferenc/papers/GitHubBugDataSet/) - Bug Dataset of 15 Java open-source projects characterized by static source code metrics.
- GitHub on Google BigQuery (https://cloud.google.com/bigquery/public-data/github) - GitHub data accessible through Google's BigQuery platform.
- Grammar Zoo (http://slebok.github.io/zoo/) - Collection of grammars of DSLs and GPLs, some extracted from metamodels and document schemata.
- KaVE (http://www.kave.cc/datasets) - Developer tool interaction data.
- Linux Kernel 4.21 Call Graphs (https://zenodo.org/record/2652487#.XRnvomUzb0o) - The Linux Kernel 4.21 Call Graphs produced using CScout (https://github.com/dspinellis/cscout/). 
- Maven metrics (https://github.com/bkarak/data_msr2015) - Collection of software complexity & sizing metrics for the Maven Repository (https://maven.apache.org).
- Maven Dependency Graph (https://zenodo.org/record/1489120) - Snapshot of the whole Maven Central taken on September 6, 2018, stored in a graph database.
- mzdata (https://github.com/jxshin/mzdata) - Multi-extract and multi-level dataset of Mozilla issue tracking history.
- npm-miner (https://github.com/AuthEceSoftEng/msr-2018-npm-miner) - The dataset contains the analysis results of 5 open source software quality tools eslint, escomplex, nsp, jsinspect and sonarjs for 2000 
popular (in terms of stars and downloads) npm packages.
- OCL Expressions on GitHub (https://github.com/tue-mdse/ocl-dataset) - Data set of 9188 OCL expressions originating from 504 EMF meta-models in 245 systematically selected GitHub repositories.
- RepoReapers Data Set (https://reporeapers.github.io) - Data set containing a collection of _engineered software projects_ from GHTorrent.
- Software Heritage Graph Dataset (https://doi.org/10.5281/zenodo.2583978) - Graph of the development history and file metadata of >80 million software projects from various forges (GitHub, Gitlab, Debian, PyPI,
Google Code, etc) in a deduplicated and unified representation (paper here (https://dl.acm.org/citation.cfm?id=3341907)).
- STAMINA (http://stamina.chefbe.net/download) - (STAte Machine INference Approaches) data are used to benchmark techniques for learning deterministic finite state machines (FSMs).
- Stack Exchange (https://archive.org/details/stackexchange) - Anonymized dump of all user-contributed content on the Stack Exchange network.
- TravisTorrent (http://travistorrent.testroots.org) - Provides free and easy-to-use Traivs CI build analyses.
- Ultimate Debian Database (UDD) (https://wiki.debian.org/UltimateDebianDatabase) - Data about various aspects of Debian (e.g. packages, bugs, mainteners) in the same SQL database.
- Unified Bug Dataset (http://www.inf.u-szeged.hu/~ferenc/papers/UnifiedBugDataSet/) - Static source code based datasets which includes the Bugcatchers Bug Dataset, the Bug Prediction Dataset 
(http://bug.inf.usi.ch/index.php), the Eclipse Bug Dataset (https://www.st.cs.uni-saarland.de/softevo/bug-data/eclipse/), the GitHub Bug Dataset (http://www.inf.u-szeged.hu/~ferenc/papers/GitHubBugDataSet/), 
some datasets from the PROMISE (http://promise.site.uottawa.ca/SERepository/datasets-page.html) repository.
- Unix history (https://github.com/dspinellis/unix-history-repo) - Git repository with 46 years of Unix history evolution.

Tools
- astminer (https://github.com/JetBrains-Research/astminer) - Library and tool for mining of path-based representations of code and other data derived from ASTs.
- Boa (http://boa.cs.iastate.edu/) - Domain-specific language and infrastructure that eases mining software repositories.
- buckwheat (https://github.com/JetBrains-Research/buckwheat) - Multi-language tokenizer for extracting identifiers from source code.
- ckjm (http://www.spinellis.gr/sw/ckjm/) - Chidamber and Kemerer Java Metrics.
- Coming (https://github.com/SpoonLabs/coming/) - A Java framework for analyzing code changes and mining instances of change patterns from Git repositories.
- CryptOSS (https://github.com/rvantonder/CryptOSS) - Mine GitHub activity and market cap data for cryptocurrency projects.
- DbDeo (https://github.com/tushartushar/DbDeo) - Extract embedded SQL statements and detect database schema smells.
- Designite (http://www.designite-tools.com) - Compute source code metrics and detect a variety of implementation, design, and architecture smells for C#.
- DesigniteJava (https://github.com/tushartushar/DesigniteJava) - Compute source code metrics and detect a variety of implementation and design smells for Java.
- Diggit (https://github.com/jrfaller/diggit) - Agile Ruby Tool to analyze Git repositories.
- GrimoireLab (http://grimoirelab.github.io/) - Free/Libre/Open Source tools for Software Development Analytics.
- MetricMiner (http://www.github.com/mauricioaniche/metricminer2) - Lean Java DSL to mine and extract data (e.g. commits, developers, modifications, diffs) from Git and SVN repositories.
- Maven-miner (https://github.com/diverse-project/maven-miner) - Java tools and infrastructure to resolve the whole Maven dependency graph, hosted in Maven Central, in the form of a Neo4j (https://neo4j.com/) 
Graph.
- Perceval (https://github.com/chaoss/grimoirelab-perceval) - Fetch repository data from tens of back-ends.
- Puppeteer (https://github.com/tushartushar/Puppeteer) - Detect configuration smells in Puppet code.
- PyDriller (https://github.com/ishepard/pydriller) - Python Framework to analyse Git repositories.
- qmcalc (https://github.com/dspinellis/cqmetrics) - Calculate quality metrics from C source code.
- reaper (https://github.com/RepoReapers/reaper) - Python tool to compute a score for a repository from GHTorrent. The score quantifies the extent to which the project contained within the repository is 
_engineered_.
- RefactoringMiner (https://github.com/tsantalis/RefactoringMiner) - Library/API for detection of refactorings in changes of Java code.
- VulData7 (https://github.com/electricalwind/data7) - Java framework enabling the automated collection of commits fixing vulnerabilities that are reported in NVD (links NVD with Git).

Research Outlets
- Outlets exclusively devoted to empirical software engineering research
  - Empirical Software Engineering journal (https://link.springer.com/journal/10664)
  - MSR: Mining Software Repositories conference (https://www.msrconf.org/)
  - PROMISE: Predictive Models and Data Analytics in Software Engineering conference (http://promise.site.uottawa.ca/SERepository/)
- Outlets that publish empirical software engineering research
  - ACM Transactions on Software Engineering and Methodology (TOSEM) (https://dl.acm.org/citation.cfm?id=J790)
  - ESEC/FSE: ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (https://www.esec-fse.org/)
  - ICSE: International Conference on Software Engineering (http://www.icse-conferences.org/)
  - IEEE Software magazine (https://publications.computer.org/software-magazine/)
  - IEEE Transactions on Software Engineering (https://www.computer.org/csdl/journal/ts)
  - Journal of Systems and Software (https://www.journals.elsevier.com/journal-of-systems-and-software)
  - SANER: IEEE International Conference on Software Analysis, Evolution and Reengineering (https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000695)


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To the extent possible under law, Diomidis Spinellis (http://www.spinellis.gr) has waived all copyright and related or neighboring rights to this work.