Substring Search Patterns in DSA Rust - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of substring search algorithms?

To find the position(s) where a smaller string (pattern) appears inside a larger string (text).

beginner

Explain the naive substring search approach.

It checks every possible position in the text to see if the pattern matches starting there, moving one by one.

intermediate

What is the key idea behind the Knuth-Morris-Pratt (KMP) algorithm?

KMP uses a precomputed table to skip unnecessary comparisons by remembering how the pattern matches itself.

intermediate

How does the Rabin-Karp algorithm speed up substring search?

It uses hashing to quickly compare the pattern with substrings of the text, reducing character-by-character checks.

intermediate

Why is preprocessing important in advanced substring search algorithms?

Preprocessing helps build data structures or tables that allow skipping parts of the text, making search faster.

Which substring search algorithm uses a prefix table to avoid rechecking characters?

A Naive search

B Knuth-Morris-Pratt (KMP)

C Rabin-Karp

D Bubble sort

KMP builds a prefix table to skip unnecessary comparisons.

What does the Rabin-Karp algorithm use to compare substrings quickly?

A Hash values

B Sorting

C Binary search

D Prefix table

Rabin-Karp uses hash values to compare substrings efficiently.

In naive substring search, how many positions in the text are checked in the worst case?

A None

B Only one

C Half of the text

D All possible starting positions

Naive search checks every possible starting position in the text.

Which of these is a benefit of preprocessing in substring search?

A Slower search

B More memory usage without speed gain

C Skipping unnecessary comparisons

D Sorting the text

Preprocessing helps skip unnecessary comparisons to speed up search.

What is the worst-case time complexity of the naive substring search?

A O(n * m)

B O(n + m)

C O(log n)

D O(1)

Naive search can take O(n * m) time in the worst case, where n is text length and m is pattern length.

Describe how the Knuth-Morris-Pratt algorithm improves substring search compared to naive search.

Think about how KMP remembers pattern matches to skip ahead.

Explain the role of hashing in the Rabin-Karp substring search algorithm.

Focus on how hashing helps quickly find potential matches.

Practice

1. What is the main purpose of substring search algorithms in strings?

easy

A. To find if a smaller string exists inside a larger string

B. To sort characters in a string alphabetically

C. To reverse the order of characters in a string

D. To count the total number of characters in a string

Solution

1. Step 1: Understand substring search goal

   Substring search algorithms check if a smaller string (pattern) appears inside a bigger string (text).

2. Step 2: Compare with other string operations

   Sorting, reversing, and counting characters are different operations unrelated to searching for a substring.

3. Final Answer:

   To find if a smaller string exists inside a larger string -> Option A

4. Quick Check:

   Substring search = find smaller string inside bigger string [OK]

Hint: Substring search means finding a smaller string inside a bigger one [OK]

Common Mistakes:

• Confusing substring search with sorting or reversing strings
• Thinking substring search counts characters
• Mixing substring search with string length calculation

2. Which Rust code snippet correctly checks if the string needle is a substring of haystack?

easy

A. if haystack.index_of(needle) { println!("Found"); }

B. if haystack.find(needle) { println!("Found"); }

C. if needle.in(haystack) { println!("Found"); }

D. if haystack.contains(needle) { println!("Found"); }

Solution

1. Step 1: Identify correct Rust substring method

   Rust's standard library provides contains method on strings to check substring presence, returning a boolean.

2. Step 2: Check other options for syntax errors

   find returns an Option, not a boolean; in is not a Rust keyword; index_of does not exist in Rust standard strings.

3. Final Answer:

   if haystack.contains(needle) { println!("Found"); } -> Option D

4. Quick Check:

   Rust substring check uses contains() [OK]

Hint: Use .contains() to check substring presence in Rust strings [OK]

Common Mistakes:

• Using .find() as a boolean without checking Option
• Trying Python or other language syntax like 'in'
• Using non-existent methods like index_of

3. What will be the output of this Rust code?

let text = "hello world";
let pattern = "wor";
if text.contains(pattern) {
    println!("Pattern found");
} else {
    println!("Pattern not found");
}

medium

A. Compilation error

B. Pattern found

C. Pattern not found

D. Runtime panic

Solution

1. Step 1: Check if pattern is substring of text

   The string "hello world" contains "wor" starting at index 6.

2. Step 2: Evaluate the if condition

   Since text.contains(pattern) returns true, the code prints "Pattern found".

3. Final Answer:

   Pattern found -> Option B

4. Quick Check:

   "hello world" contains "wor" = true [OK]

Hint: Check if substring exists literally inside the main string [OK]

Common Mistakes:

• Assuming contains() checks for whole words only
• Confusing contains() with starts_with() or ends_with()
• Expecting compilation or runtime errors without syntax issues

4. Identify the error in this Rust code snippet for substring search:

let text = "rustacean";
let pattern = "ace";
if text.find(pattern) {
    println!("Found");
} else {
    println!("Not found");
}

medium

A. Missing semicolon after let statements

B. Using contains() instead of find()

C. Using find() without handling Option result

D. Pattern string is empty

Solution

1. Step 1: Understand return type of find()

   In Rust, find() returns an Option<usize>, not a boolean.

2. Step 2: Check if condition usage

   The if condition expects a boolean, but text.find(pattern) returns Option, causing a type mismatch error.

3. Final Answer:

   Using find() without handling Option result -> Option C

4. Quick Check:

   find() returns Option, not bool [OK]

Hint: Remember find() returns Option, not boolean; unwrap or check Some [OK]

Common Mistakes:

• Treating find() as boolean directly in if
• Ignoring Option type returned by find()
• Confusing contains() and find() return types

5. Given a large text and multiple patterns, which substring search approach is best to efficiently find all patterns in the text?

hard

A. Using a Trie or Aho-Corasick algorithm to search all patterns simultaneously

B. Naive search checking each pattern separately in the text

C. Sorting all patterns and text then binary searching each pattern

D. Reversing the text and patterns before searching

Solution

1. Step 1: Analyze naive approach inefficiency

   Checking each pattern separately in a large text is slow because it repeats scanning multiple times.

2. Step 2: Understand advanced multi-pattern search

   Trie-based algorithms like Aho-Corasick build a structure to search all patterns at once efficiently.

3. Step 3: Evaluate other options

   Sorting and binary searching patterns is not suitable for substring search; reversing strings does not help search efficiency.

4. Final Answer:

   Using a Trie or Aho-Corasick algorithm to search all patterns simultaneously -> Option A

5. Quick Check:

   Multi-pattern search uses Trie/Aho-Corasick [OK]

Hint: Use Trie or Aho-Corasick for multiple substring searches efficiently [OK]

Common Mistakes:

• Using naive repeated searches for many patterns
• Trying sorting-based methods for substring search
• Thinking reversing strings improves search speed