Understanding how a regex engine processes patterns can significantly improve your ability to write efficient and accurate regular expressions. By learning the internal mechanics, you’ll be better equipped to troubleshoot and refine your regex patterns, reducing frustration and guesswork when tackling complex tasks.

Types of Regex Engines

There are two primary types of regex engines:

1. Text-Directed Engines (also known as DFA - Deterministic Finite Automaton)
2. Regex-Directed Engines (also known as NFA - Non-Deterministic Finite Automaton)

All the regex flavors discussed in this tutorial utilize regex-directed engines. This type is more popular because it supports features like lazy quantifiers and backreferences, which are not possible in text-directed engines.

Examples of Text-Directed Engines:

• awk
• egrep
• flex
• lex
• MySQL
• Procmail

Note: Some versions of awk and egrep use regex-directed engines.

How to Identify the Engine Type

To determine whether a regex engine is text-directed or regex-directed, you can apply a simple test using the pattern:

«regex|regex not»

Apply this pattern to the string "regex not":

• If the result is "regex", the engine is regex-directed.
• If the result is "regex not", the engine is text-directed.

The difference lies in how eager the engine is to find matches. A regex-directed engine is eager and will report the leftmost match, even if a better match exists later in the string.

The Regex-Directed Engine Always Returns the Leftmost Match

A crucial concept to grasp is that a regex-directed engine will always return the leftmost match. This behavior is essential to understand because it affects how the engine processes patterns and determines matches.

How It Works

When applying a regex to a string, the engine starts at the first character of the string and tries every possible permutation of the regex at that position. If all possibilities fail, the engine moves to the next character and repeats the process.

For example, consider applying the pattern «cat» to the string:

"He captured a catfish for his cat."

Here’s a step-by-step breakdown:

1. The engine starts at the first character "H" and tries to match "c" from the pattern. This fails.
2. The engine moves to "e", then space, and so on, failing each time until it reaches the fourth character "c".
3. At "c", it tries to match the next character "a" from the pattern with the fifth character of the string, which is "a". This succeeds.
4. The engine then tries to match "t" with the sixth character, "p", but this fails.
5. The engine backtracks and resumes at the next character "a", continuing the process.
6. Finally, at the 15th character in the string, it matches "c", then "a", and finally "t", successfully finding a match for "cat".

Key Point

The engine reports the first valid match it finds, even if a better match could be found later in the string. In this case, it matches the first three letters of "catfish" rather than the standalone "cat" at the end of the string.

Why?

At first glance, the behavior of the regex-directed engine may seem similar to a basic text search routine. However, as we introduce more complex regex tokens, you’ll see how the internal workings of the engine have a profound impact on the matches it returns.

Understanding this behavior will help you avoid surprises and leverage the full power of regex for more effective and efficient text processing.