Analyze Time and Space Complexity | Dataford Interview Questions

How would you handle time and space complexity when writing code for a matching or parsing problem on Alignerr?

Implement find_matches(text, patterns) to return every occurrence of each pattern in text, including overlapping matches. Return matches as [start, end, pattern], where end is exclusive, ordered by start index and then match end. For example, text = "aaaa", patterns = ["aa", "aaa"] returns all five matches shown by those rules.

Constraints: 1 <= len(text) <= 5000, patterns are distinct non-empty lowercase strings, and their total length is at most 5000.

Constraints

1 <= len(text) <= 5000
0 <= len(patterns) <= 5000
Every pattern is non-empty and contains only lowercase English letters
Patterns are distinct
The sum of pattern lengths is at most 5000

Function Signature

def find_matches(text, patterns):

Your question is Analyze Time and Space Complexity. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

How would you handle time and space complexity when writing code for a matching or parsing problem on Alignerr?

Constraints: 1 <= len(text) <= 5000, patterns are distinct non-empty lowercase strings, and their total length is at most 5000.

Constraints

1 <= len(text) <= 5000
0 <= len(patterns) <= 5000
Every pattern is non-empty and contains only lowercase English letters
Patterns are distinct
The sum of pattern lengths is at most 5000

Function Signature

def find_matches(text, patterns):

Your question is Analyze Time and Space Complexity. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.