Remembering the Future

1.1 Modeling Meaning
So we want to study semantics. But how? To study meaning, we need a language for describing meaning. Human language is, however, notoriously slippery, and as such is a poor means for communicating what are very precise concepts. But what else can we use? Computer scientists use a variety of techniques for capturing the meaning of a program, all of which rely on the following premise: the most precise language we have is that of mathematics (and logic). Traditionally, three mathematical techniques have been especially popular: denotational, operational and axiomatic semantics. Each of these is a rich and fascinating field of study in its own right, but these techniques are either too cumbersome or too advanced for our use. (We will only briefly gloss over these topics, in section 23.) We will instead use a method that is a first cousin of operational semantics, which some people call interpreter semantics.

The idea behind an interpreter semantics is simple: to explain a language, write an interpreter for it. The act of writing an interpreter forces us to understand the language, just as the act of writing a mathematical description of it does. But when we’re done writing, the mathematics only resides on paper, whereas we can run the interpreter to study its effect on sample programs. We might incrementally modify the interpreter if it makes a mistake. When we finally have what we think is the correct representation of a language’s meaning, we can then use the interpreter to explore what the language does on interesting programs. We can even convert an interpreter into a compiler, thus leading to an efficient implementation that arises directly from the language’s definition.

A careful reader should, however, be either confused or enraged (or both). We’re going to describe the meaning of a language through an interpreter, which is a program. That program is written in some language. How do we know what that language means? Without establishing that first, our interpreters would appear to be mere scrawls in an undefined notation. What have we gained? This is an important philosophical point, but it’s not one we’re going to worry about much in practice.

Topics: Meaning | Modeling | Representation | Programming