Adam Tornhill. Lisp for the Web. Leanpub. 2015.

A short, practical guide to build a dynamic web site entirely using Common Lisp. Makes extensive use of several libraries, including the intriguingly-named hunchentoot web server (named after a never-staged musical written by Frank Zappa), the CL-WHO HTML generator, and – perhaps most interesting – the Parenscript Lisp to Javascript compiler.

One gain from using Lisp is the ability to wrap-up standard constructions like page templates as macros. Other than this, it’s hard to assess whether the gains are all that significant. One interesting point is that the whole development occurs in Lisp, so there’s no cognitive dissonance between writing the back-end and the front-end: essentially the same argument for using node.js as a back-end framework. While Parenscript isn’t a fully-featured Lisp-in-the-browser it again can benefit from macros and other features. There’s a throwaway comment about linking it to jQuery, although that isn’t demonstrated in practice: it feels intriguing, though, especially if there’s a way to represent jQuery functionality idiomatically in Lisp.

J.M. Foster. List Processing. Macdonald and Co. 1967.

A slim volume discussing list processing with reference to Lisp and to other list processing systems of the time (including some libraries embedded into Fortran).

The most fascinating part of the book is its bibliography, which references a lot of papers that have disappeared from the collective memory of computer science, but whose implications were profound.

John McCarthy. Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I. Communications of the ACM 3, pp.184–195. 1960.

The original Lisp paper from 1960, which opens:

A programming system called LISP (for LISt Processor) has been developed for the IBM 704 computer…

The paper then proceeds to lay out everything that’s since been built on: the basic constructs, the use of cons cells (pairs) as a data representation, the world’s first garbage collection algorithm, an equational semantics, and ideas for interpretation and compilation. It’s awesome, and humbling to read it and realise its age and the vision of computing it developed.

(Despite this paper being labelled Part I, incidentally, there isn’t a part II.)

Peter Norvig. Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp. Morgan Kaufmann. 1992.

An absolute classic of both AI and Lisp, and really two books in one. The applications presented cover the entire range of “classic” AI up to the late 90s: expert systems, logic programming, symbolic mathematics, knowledge representation, constraint programming, game search, syntax-driven natural language processing, and more.

It uses Lisp as the programming vehicle, and doesn’t shy-away from depth, dealing with the effects of garbage collection (and how to program effectively in its presence), the effects of different representations, low-level optimisation and disassembly, and all the approaches one needs to use Lisp in real, scalable practice.

Edmund Weitz. Common Lisp Recipes: A Problem-Solution Approach. Apress. 2016.

An extensive list of recipes for using common data structures, how the differ in Lisp from the equivalents in other languages, and what novel features Lisp has to offer. A great place to start when moving away from being a beginner, and for dipping into in search of solutions.

It’s probably strongest on the “gotchas” and dangers that Lisp presents, but also has a lot to say about coding style and code optimisation.