computer science

Mining software repositories

Mining software repositories is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Mining software repositories rather than just read about it. In short: Within software engineering, the mining software repositories (MSR) field analyzes the rich data available in software repositories, such as version control repositories, mailing list archives, bug tracking systems, issue tracking systems, etc. to uncover interesting and actionable information about software systems, projects and software engineering. Definition Herzig and Zeller define ”mining software archives” as…

Key takeaways

Mining software repositories belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Mining software repositories to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Mining software repositories from memory before moving on to harder problems.

Reference excerpt

Within software engineering, the mining software repositories (MSR) field analyzes the rich data available in software repositories, such as version control repositories, mailing list archives, bug tracking systems, issue tracking systems, etc. to uncover interesting and actionable information about software systems, projects and software engineering.

Definition Herzig and Zeller define ”mining software archives” as a process to ”obtain lots of initial evidence” by extracting data from software repositories. Further they define ”data sources” as product-based artifacts like source code, requirement artefacts or version archives and claim that these sources are unbiased, but noisy and incomplete.

Techniques

Coupled Change Analysis The idea in coupled change analysis is that developers change code entities (e.g. files) together frequently for fixing defects or introducing new features. These couplings between the entities are often not made explicit in the code or other documents. Especially developers new on the project do not know which entities need to be changed together. Coupled change analysis aims to extract the coupling out of the version control system for a project. By the commits and the timing of changes, we might be able to identify which entities frequently change together. This information could then be presented to developers about to change one of the entities to support them in their further changes.

Commit Analysis There are many different kinds of commits in version control systems, e.g. bug fix commits, new feature commits, documentation commits, etc. To take data-driven decisions based on past commits, one needs to select subsets of commits that meet a given criterion. That can be done based on the commit message. Alternatively, recurrent code change patterns can be automatically identified by analyzing differences between the abstract syntax trees of file revisions within a commit.

Documentation generation It is possible to generate useful documentation from mining software repositories. For instance, Jadeite computes usage statistics and helps newcomers to quickly identify commonly used classes.

Data and tools The primary mining data comes from version control systems. Early mining experiments were done on CVS repositories. Then, researchers had extensively analyzed SVN repositories. Now, Git repositories are dominant. Depending on the nature of the data required (size, domain, processing), one can either download data from one of these sources. However, data governance and data collection for the sake of building large language models have come to change the rules of the game, by integrating the use of web crawlers to obtain data from multiple sources and domains.

See also Software evolution Software analytics Software maintenance Software archaeology

References

Worked examples

Example 1 — a first encounter with Mining software repositories

Start with the simplest possible case. Write down what Mining software repositories claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Mining software repositories before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Mining software repositories ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Mining software repositories

In research: Mining software repositories appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Mining software repositories in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Mining software repositories is common in secondary-school and first-year university syllabi. It links to neighbouring topics Software engineering, so understanding it makes those chapters shorter.
In everyday life: Look for Mining software repositories outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Mining software repositories in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Mining software repositories means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Mining software repositories out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Mining software repositories in simple terms?

Why does Mining software repositories matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Mining software repositories?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Mining software repositories.