Welcome

A transformation language has a type system based on formal languages. Rather than define classes or data structures, one defines grammars. A parser is constructed automatically from the grammar, and the parser is used for two purposes: * to parse the input language, * and to parse the structural patterns in the program that performs the analysis.

In this setting, grammar-based parsing is critical because it guarantees that both the input and the structural patterns are parsed into trees from the same set of types, allowing comparison.

Colm is not-your-typical-scripting-language ™: * Colm’s main contribution lies in the parsing method. Colm’s parsing engine is generalized, but it also allows for the construction of arbitrary global data structures that can be queried during parsing. In other generalized methods, construction of global data requires some very careful consideration because of inherent concurrency in the parsing method. It is such a tricky task that it is often avoided altogether and the problem is deferred to a post-parse disambiguation of the parse forest. * By default Colm will create an elf exectuable that be used standalone for that actual transformations. * Colm is a static and strong typed scripting language. * Colms' is very tiny and fast and can easily be embedded/linked with c/cpp programs. * Colm’s runtime is a stackbased VM that starts with the bare minium of the language and bootstraps itself. * creates aVM is very tycan be embedded in C as it It runs in a embeddable vm, the language is bootstrapped.

Colm is developed and used intensively by Colm Networks to develop fast network traffic automata and systems for traffic identification, decoding, pattern matching, and extraction of security events. But colm is also the driving force in the Ragel State Machine Compiler

Colm’s development started by Adrian Thurston during his Ph.D. thesis period after intensive study of TXL.

Colm is meant to create executables or object files that can be linked in other programs. This make is ideal for tasks like high performance transformations, but not very convenient for throwaway-oneliners that are common with tools like sed or awk.