The last-minute Brexit deal essentially extends the transition period status for a few months with regards to data protection issues.

Gcovr 4.2 is out, and provides a broad array of new features! With the ability to use config files, new output formats like JSON and SonarQube XML, and the ability to combine coverage data from multiple runs, this release should make it easier to create coverage report in more complex scenarios.

Gcovr is a command line tool that uses gcov to produce code coverage reports in various formats, such as text summaries, detailed HTML reports, and various machine-readable formats. It works with the GCC and Clang compilers.

You can pip install gcovr from PyPI, read the overview on GitHub, or read the full documentation.

Today's ruling by the ECJ on the Google v CNIL case seems to limit the territorial scope of the GDPR.

But that misses the main point of the ruling. First, the analysis is specific to the Right to Erasure. Second, it's more about the territorial scope of EU data protection authorities: they have no direct right to mandate changes to non-EU activity unless the authority first balances data subject rights against the freedom of information to show that such changes are necessary and proportional.

MongoDB announced that they are withdrawing the SSPL license from the OSI license-review process.

This reduces confusion about what is Open Source and what is not, but leaves a crucial question unsolved: how can we ensure sustainable development for Open Source projects?

Virtual method calls are simple: you just look up the method slot in a vtable and call the function pointer. Easy! Well, not quite: interfaces present a kind of multiple inheritance, and things quickly become complicated.

This post discusses interface method calls in C++ (GCC), Java (OpenJDK/HotSpot), C# (CLR), Go, and Rust.

It is an expanded version of my answer on Software Engineering Stack Exchange on Implementation of pure abstract classes and interfaces.

After a lot of refactoring and cleanup, gcovr 4.0 is out!

This release represents four months of work. The focus was on internal changes, but there are lots of enhancements as well: better filters, improved Python 3 support, GCC 8 support, better encoding support via --source-encoding, parallel gcov invocations with -j, and HTML customizations with --html-title, --html-medium-threshold, and --html-high-threshold.

Gcovr is a command line tool that uses gcov to produce code coverage reports as text summaries, detailed HTML reports, or Cobertura-compatible XML. I works with the GCC and Clang compilers.

You can pip install gcovr from PyPI, read the overview on GitHub, or read the user guide.

I've assembled a list of a few programming and tech blogs which I particularly enjoy.

So you've got a Perl $variable. Can we use it as an array or hash reference? If you do an online search for possible solutions, you'll find a number of suggestions, most of them wrong.

TL;DR: checking if ref $variable eq 'ARRAY' is almost always a bug. Depending on your use case, you want:

• reftype $variable eq 'ARRAY' from Scalar::Util as a check for physical array references, or
• _::is_array_ref $variable from my module Util::Underscore as a check for logical array references.

With Dist::Zilla (dzil), testing Perl projects on Travis CI can be a bit tricky. Here's my approach.

When does it make sense to keep integration tests separate from your unit tests, and when is it OK to make no distinction?

Well, it's all about getting fast feedback.

This article explains the difference between dynamic dispatch (late binding) and static dispatch (early binding). We'll also touch on the differences in language support for virtual and static methods, and how virtual methods can be circumvented.

I'm currently refactoring a huge method into smaller parts. It is stock full of nested loops, maintains a complex state machine with more variables than I have fingers, and is the kind of code where I have to ask myself how I could ever think this would have been a good idea. So obviously, I'm splitting that function into smaller, independent chunks with the Extract Method refactoring technique.¹ Since the control flow is now simplified, the code has also become easier to test – as long as I'm comfortable with testing private methods. Why?

The number of test cases needed for full path coverage corresponds directly to the McCabe complexity of the code under test. Since many simple functions often have lower total complexity than one convoluted function, the overall required testing effort is reduced. As this reduction can be substantial, there is a strong incentive to test the extracted methods directly, instead of testing only through the public interface.

Global dependencies make it difficult to properly test a piece of code. By extracting all dependencies into a single manageable object, we can easily mock the necessary services and avoid a large-scale refactor.

There are many exciting parser technologies out there, and one of the most promising is Marpa. This post discusses how Marpa improves over commonly used parsers.

Object-oriented programming and functional programming imply each other. While encoding closures as objects is a well-known technique (see the command pattern, and e.g. Functors in C++), using closures to implement objects is a bit more unusual.

In this post, I will explore creating a simple object system in JavaScript, using only the functional parts.

A Stack Overflow question asked how to translate a VB-like conditional into a C-like ternary. The other answers suggested regexes or treating it as Perl code *shudder*. But transpiling code to another language can be done correctly.

This post aims to cover:

• parsing with Marpa::R2,
• AST manipulation,
• optimization passes,
• compilation, and
• Perl OO.

In the end, we'll be able to do all that in only 200 lines of code!

Since this post is already rather long, we will not discuss parsing theory. You are expected to be familiar with EBNF grammar notation.