Denotational semantics are a great way to capture the meaning of a programming language. If your language provides a denotational semantics it's a nice exercise to implement them in a functional language. For instance, here's my implementation of R5RS Scheme in Haskell following the spec's semantics.[0]
A lot of toy Scheme implementations omit call/cc for instance because it can be hard to reason about and do correctly, whereas following the spec made it really easy.
"Denotational semantics are a great way to capture the meaning of a programming language" - big claim - what is the meaning of a programming language?
For example, if you able to capture what the meaning of a programming language is, then could you please demonstrate by communicating what "the meaning of the programming language" C is, for instance? This appears to be a nonsensical combination of words, as I do not recognise a programming language as having an intrinsic meaning?
I think you're thinking of the wrong definition for "meaning." OP is talking about what code in a language means, i.e. when I see the code say `1 + 2` does that mean that the numbers signed or unsigned? Are they arbitrary precision or a certain size? What errors can result from the addition? Etc. It's essentially saying that you can look at a piece of code and formally define what it means to the computer
This seems pretty good from a brief flick through; the author. Graham Hutton, is pretty well known in the CS community.
Some other resources for people who find that this piques their interest and that they want to go deeper:
* Formal Reasoning About Programs ("FRAP") by Adam Chlipala - available for free here: http://adam.chlipala.net/frap/. Forms the basis for 6.822 at MIT, and comes with an accompanying Coq formalisation (as well as psets in Coq).
* The Formal Semantics of Programming Languages: An Introduction by Glynn Winskel.
* Essentials of Programming Languages by Friedman and Wand http://eopl3.com/
It's quite accessible and has an emphasis on executable implementations. Covers quite a wide variety of paradigms, FP, FP with mutation, type checking, type inference, and objects and classes.
* Concrete Semantics by Nipkow and Klein http://concrete-semantics.org/, which is also an introduction to the Isabelle/HOL proof assistant and formalizes all of the PL content in Isabelle
There's also:
* Semantics with Applications: An Appetizer by Nielson and Nielson https://www.springer.com/gp/book/9781846286919, apparently a newer edition of an older book I liked and which used to be available as a free PDF, but the link from my browser history is now broken
This is timely, I'm reviewing this deck just after working a grueling day on my language and tuning the language runtime for performance.
What's interesting is how many things we can now intuitively take for granted, but for each idea someone had to suffer and make it real. Their primary barrier was people via communication and getting traction.
A lot of toy Scheme implementations omit call/cc for instance because it can be hard to reason about and do correctly, whereas following the spec made it really easy.
[0] https://github.com/siraben/r5rs-denot