Implementing is understanding
I’m gradually reading through the Engineering a Compiler book. I’m enjoying it but after a while I started wondering if I really understood the algorithms and I wanted to make sure of that before going further. So I implemented the algorithms in C++ (C++17, because it’s nice), testing them against the example inputs and grammars from the book. For instance, here is my code to construct, and use, the action and goto tables which define a DFA for a bottom-up table-driven LR(1) parser, along with some test code to use it with a simple expression grammar.
So far I’ve done this for Chapter 2 (Scanners) and Chapter 3 (Parsers) and I’ll try to keep going. It is a useful exercise for me, and maybe it’s useful to someone else reading the book. Please note that the code will probably be meaningless to you if you haven’t read the book or something similar. On the other hand, the code will probably seem childlike if you’ve studied compilers properly.
Trying to get the code to work often showed me that I had had only the illusion of fully understanding. Much of the pseudocode in the book is not very clear, even when you adjust your mind to its vaguely mathematical syntax, and to know what it really means you have to closely read the text descriptions, sometimes finding clues several pages back. For instance it’s not always clear what is meant by a particular symbol, and I found at least one conditional check that appeared in the description but not in the code. I would much rather see descriptions inline in the code.
Pseudocode is vague
I’m not a fan of pseudocode either, though I understand the difficulty in choosing a real programming language for examples. It means putting some readers off. But there could at least be some real code in an appendix. The book has some detailed walkthroughs that show that the authors must have implemented the algorithms somehow, so it’s a shame that I couldn’t just look at that code. I wonder what real programming language might be the most compact for manipulating sets of states when dealing with finite state automata states and grammar symbols.
For the parsers chapter this wasn’t helped by the, presumably traditional, ambiguity of the “FIRST” sets terminology. FIRST(symbol), FIRST(symbols), FIRST(production), and FIRST+(production) are all things.
My code isn’t meant to be efficient. For instance, my LR(1) parser table-building code has some awfully inefficient use of std::set as a key in a std::map. The code is already lengthier than I’d like, so I would prefer not to make it more efficient at the cost of readability. I’ve also probably overdone it with the half-constexpr and vaguely-concepty-generic Grammar classes. But I am tempted by the idea of making these fully constexpr with some kind of constexpr map, and then one day having the compiler build the generated (DFA) tables at compile time, so I wanted to explore that just a little.
But the book is good
Despite my complaints about the presentation of the algorithms, so far I’d still recommend the book. I feel like it’s getting the ideas into my head , it’s not really that bad, and as far as I know there’s nothing better. Of course, given that I haven’t read the alternatives, my recommendation shouldn’t mean much.
Also, these days I always write up my notes as a bigoquiz.com quiz, so here are my quizzable compiler notes so far.