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Regular Expression Matching: the Virtual Machine Approach Russ Cox rsc@swtch.com December 2009 Introduction Name the most widely used bytecode interpreter or virtual machine. Sun's JVM? Adobe's Flash? .NET and Mono? Perl? Python? PHP? These are all certainly popular, but there's one more widely used than all those combined. That bytecode interpreter is Henry Spencer's regular expression library an

Regular Expression Matching with a Trigram Index or How Google Code Search Worked Russ Cox rsc@swtch.com January 2012 Introduction In the summer of 2006, I was lucky enough to be an intern at Google. At the time, Google had an internal tool called gsearch that acted as if it ran grep over all the files in the Google source tree and printed the results. Of course, that implementation would be fairl

Implementing Regular Expressions Russ Cox rsc@swtch.com This page collects resources about implementing regular expression search efficiently. Articles and Notes “Regular Expression Matching Can Be Simple And Fast” An introduction to using finite automata to implement regular expression matching, and why the standard backtracking implementation is a bad idea. Supporting programs: NFA | DFA | bound

Introduction This page is a slice of the history of concurrent programming, focusing on one particular lineage of Hoare's language of communicating sequential processes (CSP) [1] [1a]. Concurrent programming in this style is interesting for reasons not of efficiency but of clarity. That is, it is a widespread mistake to think only of concurrent programming as a means to increase performance, e.g.,

Regular Expression Matching Can Be Simple And Fast (but is slow in Java, Perl, PHP, Python, Ruby, ...) Russ Cox rsc@swtch.com January 2007 Introduction This is a tale of two approaches to regular expression matching. One of them is in widespread use in the standard interpreters for many languages, including Perl. The other is used only in a few places, notably most implementations of awk and grep.

Regular Expression Matching with a Trigram Index or How Google Code Search Worked Russ Cox rsc@swtch.com January 2012 Introduction In the summer of 2006, I was lucky enough to be an intern at Google. At the time, Google had an internal tool called gsearch that acted as if it ran grep over all the files in the Google source tree and printed the results. Of course, that implementation would be fairl

Russ Cox http://swtch.com/~rsc/talks/ Second International Plan 9 Workshop December 2007 Introduction Two popular camps for designing concurrent programs. Threads with locks Birrell, “An introduction to programming with threads” Top-level select loops with events Ousterhout, “Why threads are a bad idea (for most purposes)” Should we use threads or events? Andrew Birrell: threads. John Ousterhout:

Regular Expression Matching: the Virtual Machine Approach Russ Cox rsc@swtch.com December 2009 Introduction Name the most widely used bytecode interpreter or virtual machine. Sun's JVM? Adobe's Flash? .NET and Mono? Perl? Python? PHP? These are all certainly popular, but there's one more widely used than all those combined. That bytecode interpreter is Henry Spencer's regular expression library an

Regular Expression Matching in the Wild Russ Cox rsc@swtch.com March 2010 Introduction The first two articles in this series, “Regular Expression Matching Can Be Simple And Fast” and “Regular Expression Matching: the Virtual Machine Approach,” introduced the foundation of DFA-based and NFA-based regular expression matching. Both were based on toy implementations optimized for teaching the basic id

Regular Expression Matching Can Be Simple And Fast (but is slow in Java, Perl, PHP, Python, Ruby, ...) Russ Cox rsc@swtch.com January 2007 Introduction This is a tale of two approaches to regular expression matching. One of them is in widespread use in the standard interpreters for many languages, including Perl. The other is used only in a few places, notably most implementations of awk and grep.

Implementing Regular Expressions Russ Cox rsc@swtch.com This page collects resources about implementing regular expression search efficiently. Articles and Notes “Regular Expression Matching Can Be Simple And Fast” An introduction to using finite automata to implement regular expression matching, and why the standard backtracking implementation is a bad idea. Supporting programs: NFA | DFA | bound