Common Patterns
String Matching & Parsing
Pattern matching, parsing, and text processing — from regex-style matching to building simple parsers and interpreters.
String matching problems show up in AI coding interviews because they're the kind of problems that naturally decompose into multiple components: a regex to extract fields here, a state machine to track context there, maybe a trie for fast lookup against a known set. Being able to decompose problems like this is an important skill for a software engineer. Can you break a messy text-processing task into clean pieces? Can you tell the AI what to build for each piece and then wire them together correctly?
Think log analyzers that extract structured data from messy output, template engines that expand variables inside strings, config readers, validators for structured formats, and autocomplete over a fixed vocabulary. These are things real engineers build all the time, which makes them perfect for an interview format that's trying to simulate real work.
Nobody expects you to walk in knowing the KMP algorithm or Aho-Corasick by heart. Interviewers care about whether you can recognize what kind of string problem you're facing, pick a reasonable approach, and implement it correctly with AI assistance. What matters is engineering judgment.
Recognizing the pattern
String matching problems are easy to spot in the prompt because the vocabulary is a dead giveaway. The harder skill is recognizing which sub-pattern applies, because this is a toolkit pattern with four distinct shapes underneath.
Vocabulary that flags string matching:
- Validate, match, find, extract, classify. These are the verbs. If any of them appear in the prompt, you're almost certainly in this pattern.
- A format described by example. "Each line looks like LEVEL [timestamp] message" or "valid IPs look like 1.2.3.4." When the input format is shown rather than fully specified, you're being asked to write a matcher.
- A fixed vocabulary or schema. Known error codes, config keys, command names. Anything with a closed set of valid values to check against.
Once you've recognized the pattern, the next question is which tool. Use this lookup:
| If the problem is... | Reach for... |
|---|---|
| Find one fixed pattern in a text | Brute force string search |
| Match against many fixed patterns | Trie |
| Validate a format with distinct modes or phases | Finite state machine |
| Extract structured fields from a line | Regex |
The most common failure mode on these problems is reaching for one tool when the problem actually needs a combination. A log analyzer might layer regex extraction underneath a state machine that handles multi-line entries, or a trie that classifies extracted error codes against known signatures. The "Combining the pieces" section below covers that explicitly.
Pattern matching fundamentals
Trie-based multi-pattern matching
Finite state machines
Regular expressions
Combining the pieces
Prompting the AI
Verifying the AI's code
When to use vs. alternatives
What interviewers expect
Putting it together
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