Wherein I attempt to give a 10,000-foot overview of semantics of programming languages.

First off, I am a mathematician, not a programming language theorist. Please comment below if I say anything that’s completely off-base or even just a bit misleading: I’ll be happy to make the necessary corrections.

*Clears throat*

## Operational and Logical Semantics

You can study a programming language by its operational semantics or by its logical semantics, which both try to answer the question “when are two programs equivalent?”.

Two programs are logically equivalent only when they are the same in all possible interpretations of the primitive language symbols. As a result, not a lot of programs are logically equivalent. In contrast, two programs are operationally equivalent when they produce the same result for all possible inputs, whether or not they have logically-equivalent source code.

Edit: My descriptions of both operational semantics and logical semantics need a lot of work! I’ll fix them after I’ve done adequate reading, but in the mean time, see the discussion on Twitter [4].

## Denotational Semantics

Operational semantics ignores side effects, looking only at the inputs (say, from stdin) and the outputs (say, to stdout). Denotational semantics is kinda part-way between logical semantics and operational semantics. In denotational semantics, you define a mapping between your programming language and some mathematical model (e.g. a finite-state machine or an abstract algebra or a category). In that way, each program written in your language is identified with some mathematical entity in the model. The particular mathematical entity that a given program maps to is considered to be the intended interpretation of that program.

Two programs are denotationally equivalent relative to a given model if they both map to the same mathematical entity in that model. In other words, two programs are denotationally equivalent if they are the same entity in the intended interpretation. Contrast that to logical equivalence, which requires the programs be the same for all possible interpretations.

## The “M” Word

Moggi pointed out that if your denotational model is a certain kind of category (a cartesian-closed category), then you could use monads in the model category (not in the programming language itself) to promote certain classes of side effects to first-class mathematical entities in that model [1]. This allows you to formally model and study side effects and develop a notion of equivalence of side-effectual programs that is more fine-grained than operational semantics while being less restrictive than logical semantics.

It wasn’t long before a couple of zealots took Moggi’s ideas about using monads in the meta-language a step further by using monads in the formal language, adding them as first-class features of their “too cute for its own good” toy PL, Haskell [2, 3].

## A Simple Language

Here’s a simple language:

A program written in this language is a sequence of statements, one per line. Here’s a very simple one:

input gets the first eight bytes of stdin and reads them as a 64-bit unsigned int, ignoring any extra bytes. It is read at program start and is immutable thereafter. If at program start there are fewer than eight bytes in stdin, then the missing bytes are treated as 00000000.

time gets the current system time, in millis since epoch, each time it is used.

store n mutates an eight-byte stored value by reading its value as a 64-bit unsigned int and then adding n to it (overflows are allowed and silent, no data consistency requirements here). This is the language’s only abstraction for memory: a single eight-byte chunk. At the start of any program, the store is initialized with zeros.

sleep n causes the program to wait for n milliseconds before continuing.

output prints the currently-stored eight bytes of stdout.

rm -rf / does the unthinkable.

Since operational equivalence requires that program outputs be the same whenever the inputs are the same, the following program

is not operationally equivalent to itself, since we can cause it to produce a different output while feeding it the same input simply by running the program at different times.

Perhaps more importantly, the two programs

and

are operationally equivalent (since deleting everything does not put bytes on stdout), even though we’d probably prefer they not be.

## A Simple Denotational Semantics

We’ll give a denotational semantics for our language, writing the model in Haskell.

Now we can define a mapping from programs written in our simple language to values of type Program in our Haskell model. This allows us to treat two programs as denotationally equivalent (relative to our model) if they both get mapped to the same Program value.

A few things to note:

First, since there’s no way to define an Eq instance for functions, Haskell won’t be able to automatically prove denotational equivalence of parsed programs for us. However, since we now at least have a sensible definition of program equivalence, we could still prove the equivalence of two programs (relative to our model) on paper ourselves, if we had to. Or if there’s no time for that, we could always use QuickCheck.

Second, I keep saying cryptic things like “relative to our model.” This is to emphasize that the Haskell model we wrote is by no means the only valid model for our simple language. In fact, while it is an improvement over the operational semantics (now we can prove that a program doesn’t pave the root directory), it’s still flawed. For instance, our model treats all operations besides sleep as though they take no time to complete. While this is perhaps reasonable for our purposes, keep in mind that a given denotational model is not necessarily the only reasonable model of a programming language.

## References

1. E. Moggi, Notions of computation and monads. Information and Computation, July 1991. http://www.sciencedirect.com/science/article/pii/0890540191900524.

2. S. Peyton Jones, P. Wadler, Imperative functional programming. ACM Symposium on Principles Of Programming Languages (POPL), Jan 1993. http://www.microsoft.com/en-us/research/wp-content/uploads/1993/01/imperative.pdf.