OOP Is Dead, Long Live Data-oriented Design

by Stoyan Nikolov

For decades C++ developers have built software around OOP concepts that ultimately failed us - we didn’t see the promises of code reuse, maintenance or simplicity fulfilled, and performance suffers significantly. Data-oriented design can be a better paradigm in fields where C++ is most important - game development, high-performance computing, and real-time systems.

The talk will briefly introduce data-oriented design and focus on practical real-world examples of applying DoD where previously OOP constructs were widely employed.

Examples will be shown from modern web browsers. They are overwhelmingly written in C++ with OOP - that’s why most of them are slow memory hogs. In the talk I’ll draw parallels between the design of systems in Chrome and their counterparts in the HTML renderer Hummingbird. As we’ll see, Hummingbird is multiple times faster because it ditches OOP for good in all performance-critical areas.

We will see how real-world C++ OOP systems can be re-designed in a C++ data-oriented way for better performance, scalability, maintainability and testability.

“C++17 Standard Library Quick Reference” Now Available

by Marc Gregoire

Together with Peter Van Weert, we finished our new book titled “C++17 Standard Library Quick Reference”. It’s published by Apress...

Making C++ Pipes Compatible with STL Algorithms

by Jonathan Boccara

As we saw in the previous post, the Smart output iterators are now called Pipes...

Remember the Vasa! or, plus ça change, plus c’est la même chose

by Ben Deane

I’ve been programming in C++ for almost a quarter of a century now. I grew up, professionally, with C++, and in many ways, it grew up along with me...

Overload 152 is now available

Reactive or Proactive.
Reactive systems are all the rage. Frances Buontempo compares them with a proactive approach.

A Low-Latency Logging Framework.
Logging can be a bottleneck in systems. Wesley Maness and Richard Reich demonstrate a low-latency logging framework that avoids common problems.

Empty Scoped Enums as Strong Aliases for Integral Types.
Scoped enums have many advantages. Lukas Böger demonstrates their use as strong types of numbers.

C++ Reflection for Python Binding.
There are various approaches to generating Python bindings in C++. Russell Standish shows how Classdesc can be used to achieve this.

Trip Report: Italian C++ 2019.
Milan held Italy’s largest C++ conference. Hans Vredeveld reports back.

Afterwood.
Many people are risk-averse. Chris Oldwood considers this position – in verse.

2019 Poster Program Announced

by Bob Steagall

We’re pleased to announce that the 2019 Poster Program is now available!  We have twelve outstanding entries this year, and encourage you to stop by and read all of them...

Lightning Talks and Lightning Challenge

by Phil Nash

Whilst many of the main conference talks go deep, Lightning Talks are, well, lighter. That doesn’t mean you won’t gain deep insights from some. Many, however, are humorous, entertaining – and often high-energy...

C++ Core Guidelines: Non-Rules and Myths

by Rainer Grimm

Of course, you already know many non-rules and myths to C++. Non-rules and myths which we have to argument against when we use modern C++. The supporting section of the C++ core guidelines addresses the most resistant once but also provides alternatives...

Presenter Interviews: Stephan T. Lavavej

by Kevin Carpenter

In this week’s presenter interview, Kevin Carpenter welcomes Stephan T. Lavavej (STL) for a preview of his upcoming talk, Floating-Point charconv: Making Your Code 10x Faster With C++17’s Final Boss. Stephan discusses achieving a 3x to 10x speed up with charconv in C++17.

Combining Ranges and Smart Output Iterators

by Jonathan Boccara

In our current stage of development of smart output iterators, we have:

• some iterators, such as filter, transform, unzip or demux,
• the possibility to combine them: filter(pred) >>= transform(f) >>= unzip(back_inserter(output1), back_inserter(output2))
• their usage as the output iterator of an STL algorithm:

std::copy(begin(inputs), end(inputs), transform(f) >>= back_inserter(outputs));

What we’re going to work on today is removing the call to std::copy to have a pipeline made of output iterators only. And once we get such a pipeline, we will plug it to ranges, in order to benefit from the expressiveness of both ranges and smart output iterators, in the same expression...