Introducing Marks

In my previous two posts (here and here), I described how and why programming languages can’t talk about many issues that affect programmers–important issues like product requirements, design constraints, intellectual property, and more. I also inventoried the mechanisms that extend the semantics of languages today, and explored why those mechanisms have limited value. If you haven’t read those posts, please do; what I say next won’t make a lot of sense without that foundation.

In the intent programming language that I’m creating, the solution to this problem is called “marks” (a name which alludes to linguistic markedness). Marks play a role somewhat analogous to adjectives and adverbs in human language; they are crucial enrichers. They resemble decorators or annotations in other languages, though their power is much, much greater.

Without further ado, let me provide a blueprint for this bridge across the semantic gap that I’ve been lamenting–the design guidelines for “marks.” Then I’m going to show you an example of how easy it could be to use marks, and how much power they give you.

image credit: Curious Expeditions (Flickr)


  1. Code and its compiler(s) must have a compile-time API specified by the language.
    It’s not okay if Clang generates one type of AST, GCC a second, and MSVC a third; all compilers that support the language must expose a spec-compatible, programmable API for all language constructs. For example, I need to be able to find out what parameters and local variables are declared in a function, and what their data types and other characteristics are. This is similar to what reflection offers, but reflection doesn’t help at all, because I need this before run-time. (Kudos to D, which provides compile-time reflection very similar to what I’m describing…) As I mentioned in my post about making a codebase const-correct, the lack of this feature is really a serious design flaw. Why should code, of all things programmers deal with, be impossible to code against?

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How to make a const-correct codebase in 4300 easy steps

One of the codebases that I work on is theoretically C++, but if you peer under the hood, it looks more like 1990-vintage C. It’s 500 KLOC of almost purely procedural code, with lots of structs and few true objects. More dusty and brittle than I’d like.

Image credit: Tim Gillin (Flickr)

I am not a C++ bigot; I first began to do serious, professional coding in C, not long after this codebase got its start. I understand the C-isms pretty well. And although I think Linus got carried away in his rant about the ugliness of C++, I can appreciate the ways that lean C sometimes makes its descendant look ugly and inefficient. (Though C++11 and 14 are making this less true…)

This means that I don’t consider the C-like style of this particular codebase a fatal flaw, in and of itself.

However, since my early coding adventures I’ve been converted to the advantages of OOP for complex projects and large teams, and I’ve also accumulated a lot of battlescars around multithreading. Our codebase needs OOP to solve some encapsulation antipatterns, and it needs RAII and C++11-style mutexing in the worst way. Its old, single-threaded mindset makes far too many things far too slow and error-prone.

A few months ago, we decided to make an investment to solve these problems.

To do it right, I had the team add a story to our scrum backlog about making the codebase const-correct. And therein lies a tale worth recounting…

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