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2060. Check if an Original String Exists Given Two Encoded Strings

HardStringDynamic Programming
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Problem Description

This problem asks you to determine if two encoded strings could have originated from the same original string.

The encoding process works as follows:

  1. Start with an original string containing only lowercase English letters
  2. Split this string into a sequence of non-empty substrings (in any way you choose)
  3. Optionally replace some of these substrings with their lengths (as numeric strings)
  4. Concatenate everything together to form the encoded string

For example, the original string "abcdefghijklmnop" could be encoded as "ab121p" by:

  • Splitting into: ["ab", "cdefghijklmn", "o", "p"]
  • Replacing the 2nd and 3rd elements with their lengths: ["ab", "12", "1", "p"]
  • Concatenating to get: "ab121p"

Given two encoded strings s1 and s2 (containing lowercase letters and digits 1-9), you need to return true if there exists some original string that could be encoded to produce both s1 and s2. Otherwise, return false.

The key insight is that digits in the encoded strings represent the lengths of substrings from the original. So when comparing two encoded strings, you need to account for the fact that:

  • Letters must match exactly with corresponding letters
  • Digits represent "wildcards" that can match any substring of the specified length
  • A digit sequence like "12" means 12 consecutive characters from the original string

The challenge is handling all possible interpretations of digit sequences (since "12" could mean 12 characters, or it could be "1" and "2" representing 1 and 2 characters respectively) and determining if there's a valid matching between the two encoded strings.

Note: The problem guarantees that no more than 3 consecutive digits appear in the encoded strings.

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Intuition

The key realization is that we need to match two encoded strings character by character, but digits create flexibility since they represent "wildcards" of variable length. Think of it like having two pointers moving through s1 and s2, but sometimes one pointer can "skip ahead" when it encounters digits.

The main challenge is handling the mismatch between positions. When s1 has a digit like "5", it means 5 characters from the original string, while s2 might have those same 5 characters represented as "2" + "3" or as actual letters like "ab3". We need to track this "difference" or "delta" between how many characters each string has consumed from the original.

Consider this example: if s1 = "a3" and s2 = "2bc", both could represent "abbc":

  • s1: "a" + 3 chars ("bbc")
  • s2: 2 chars ("ab") + "b" + "c"

The insight is to use dynamic programming with state dp[i][j][delta] where:

  • i is the current position in s1
  • j is the current position in s2
  • delta represents the "balance" - how many more characters s1 has consumed versus s2

When delta > 0, s1 is "ahead" and needs s2 to catch up. When delta < 0, s2 is ahead. When delta = 0, both strings have consumed the same number of characters from the original string and can potentially match letters directly.

At each state, we have several transitions:

  1. If we see digits, we can interpret them as numbers and adjust the delta accordingly
  2. If delta ≠ 0, we can match letters against the "debt" created by previous digits
  3. If delta = 0 and both positions have the same letter, they can match directly

The answer is true if we can reach dp[n][m][0], meaning we've processed both strings entirely and they've consumed the same total number of characters from the original string.

Learn more about Dynamic Programming patterns.

Solution Approach

The solution uses dynamic programming with a 3D state space represented as a 2D array where each cell contains a Set of possible delta values.

State Definition:

  • dp[i][j] is a Set containing all possible delta values when we've processed i characters from s1 and j characters from s2
  • delta represents the difference in consumed characters: positive means s1 consumed more, negative means s2 consumed more

Initialization:

  • dp[0][0].add(0) - at the start, both strings have consumed 0 characters

State Transitions:

For each state (i, j) with delta value, we have five possible transitions:

  1. Process digits in s1 (when delta <= 0):

    for (let p = i; p < Math.min(i + 3, n); p++) {
    if (isDigit(s1[p])) {
        num = num * 10 + Number(s1[p]);
        dp[p + 1][j].add(delta + num);
    }
}

    When s1 is not ahead, we can interpret consecutive digits (up to 3) as a number and add it to delta.

  2. Process digits in s2 (when delta >= 0):

    for (let q = j; q < Math.min(j + 3, m); q++) {
    if (isDigit(s2[q])) {
        num = num * 10 + Number(s2[q]);
        dp[i][q + 1].add(delta - num);
    }
}

    When s2 is not ahead, we can interpret consecutive digits and subtract from delta.

  3. Match letter in s1 against deficit (when delta < 0):

    if (i < n && delta < 0 && !isDigit(s1[i])) {
    dp[i + 1][j].add(delta + 1);
}

    If s2 previously consumed more characters (negative delta), a letter in s1 can match one of those characters.

  4. Match letter in s2 against surplus (when delta > 0):

    if (j < m && delta > 0 && !isDigit(s2[j])) {
    dp[i][j + 1].add(delta - 1);
}

    If s1 previously consumed more characters (positive delta), a letter in s2 can match one of those characters.

  5. Direct letter matching (when delta == 0):

    if (i < n && j < m && delta == 0 && s1[i] == s2[j]) {
    dp[i + 1][j + 1].add(0);
}

    When both strings have consumed the same amount, matching letters can directly correspond.

Final Check: Return dp[n][m].has(0) - we need both strings fully processed with delta = 0, meaning they represent the same total length from the original string.

The algorithm efficiently explores all possible interpretations of digit sequences and letter matchings, using the delta mechanism to ensure consistency between the two encoded strings.

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Example Walkthrough

Let's trace through a small example: s1 = "l23" and s2 = "4e". These could both represent the original string "love":

  • s1 = "l23" → "l" + 2 chars ("ov") + 3 chars ("e") → but wait, that's only 4 chars total
  • Let me reconsider: s1 = "l23" → "l" + 23 chars? No, that doesn't match with s2 = "4e"

Let me use a clearer example: s1 = "a3" and s2 = "2bc". Both could represent "abbc":

  • s1: "a" + 3 chars ("bbc")
  • s2: 2 chars ("ab") + "b" + "c"

Step-by-step DP traversal:

Initialize: dp[0][0] = {0} (both strings start at position 0 with delta 0)

From state (0, 0, delta=0):

  1. Process digit in s2 at position 0: "2" → dp[0][1] = {-2} (s2 consumes 2 chars, s1 consumes 0)
  2. Direct match letters: s1[0]='a' and s2[0]='2' → no match (one is digit)

From state (0, 1, delta=-2): Since delta < 0, s2 is ahead by 2 chars. We can:

  1. Match letter s1[0]='a' against deficit → dp[1][1] = {-1} (s1 catches up by 1)

From state (1, 1, delta=-1): Since delta < 0, s2 is still ahead by 1. We can:

  1. Process digit s1[1]='3' (since delta ≤ 0) → dp[2][1] = {2} (delta = -1 + 3 = 2)

From state (2, 1, delta=2): Since delta > 0, s1 is ahead by 2 chars. We can:

  1. Match letter s2[1]='b' against surplus → dp[2][2] = {1} (s2 catches up by 1)

From state (2, 2, delta=1): Since delta > 0, s1 is still ahead by 1. We can:

  1. Match letter s2[2]='c' against surplus → dp[2][3] = {0} (s2 catches up completely)

Final state (2, 3, delta=0): We've processed all of s1 (length 2) and all of s2 (length 3) with delta=0.

Since dp[2][3] contains 0, return true - both strings can represent the same original string "abbc" where:

  • s1 = "a3" encodes it as letter 'a' followed by 3 characters
  • s2 = "2bc" encodes it as 2 characters followed by letters 'b' and 'c'

Solution Implementation

1def possiblyEquals(s1: str, s2: str) -> bool:
2    """
3    Determines if two strings with wildcard numbers can possibly be equal.
4    Numbers in strings represent that many lowercase letters.
5  
6    Args:
7        s1: First string containing letters and numbers
8        s2: Second string containing letters and numbers
9  
10    Returns:
11        True if the strings can possibly be equal, False otherwise
12    """
13    s1_length = len(s1)
14    s2_length = len(s2)
15  
16    # dp[i][j] stores set of possible delta values at position (i, j)
17    # delta represents the difference in wildcard counts between s1 and s2
18    # positive delta means s1 has more wildcards to consume
19    # negative delta means s2 has more wildcards to consume
20    dp = [[set() for _ in range(s2_length + 1)] for _ in range(s1_length + 1)]
21  
22    # Initialize: at position (0, 0) with no wildcard difference
23    dp[0][0].add(0)
24  
25    # Process all positions in both strings
26    for i in range(s1_length + 1):
27        for j in range(s2_length + 1):
28            # Process each possible delta value at current position
29            for delta in dp[i][j]:
30              
31                # Case 1: Parse consecutive digits in s1 as a wildcard number
32                if delta <= 0:
33                    wildcard_value = 0
34                    # Parse up to 3 consecutive digits (max wildcard is 999)
35                    for next_pos in range(i, min(i + 3, s1_length)):
36                        if is_digit(s1[next_pos]):
37                            wildcard_value = wildcard_value * 10 + int(s1[next_pos])
38                            # Add this wildcard value to delta
39                            dp[next_pos + 1][j].add(delta + wildcard_value)
40                        else:
41                            break  # Stop if we encounter a non-digit
42              
43                # Case 2: Parse consecutive digits in s2 as a wildcard number
44                if delta >= 0:
45                    wildcard_value = 0
46                    # Parse up to 3 consecutive digits (max wildcard is 999)
47                    for next_pos in range(j, min(j + 3, s2_length)):
48                        if is_digit(s2[next_pos]):
49                            wildcard_value = wildcard_value * 10 + int(s2[next_pos])
50                            # Subtract this wildcard value from delta
51                            dp[i][next_pos + 1].add(delta - wildcard_value)
52                        else:
53                            break  # Stop if we encounter a non-digit
54              
55                # Case 3: Match a letter in s1 with pending wildcards from s2
56                if i < s1_length and delta < 0 and not is_digit(s1[i]):
57                    # Consume one wildcard from s2 to match letter in s1
58                    dp[i + 1][j].add(delta + 1)
59              
60                # Case 4: Match a letter in s2 with pending wildcards from s1
61                if j < s2_length and delta > 0 and not is_digit(s2[j]):
62                    # Consume one wildcard from s1 to match letter in s2
63                    dp[i][j + 1].add(delta - 1)
64              
65                # Case 5: Match two identical letters when no wildcards are pending
66                if i < s1_length and j < s2_length and delta == 0 and s1[i] == s2[j]:
67                    # Both letters match, move to next position with delta = 0
68                    dp[i + 1][j + 1].add(0)
69  
70    # Check if we can reach the end of both strings with balanced wildcards
71    return 0 in dp[s1_length][s2_length]
72
73
74def is_digit(char: str) -> bool:
75    """
76    Checks if a character is a single digit (0-9).
77  
78    Args:
79        char: Character to check
80  
81    Returns:
82        True if the character is a digit, False otherwise
83    """
84    return char.isdigit()
85
1/**
2 * Determines if two strings with wildcard numbers can possibly be equal
3 * Numbers in strings represent that many lowercase letters
4 * @param s1 - First string containing letters and numbers
5 * @param s2 - Second string containing letters and numbers
6 * @return true if the strings can possibly be equal, false otherwise
7 */
8public boolean possiblyEquals(String s1, String s2) {
9    int s1Length = s1.length();
10    int s2Length = s2.length();
11  
12    // dp[i][j] stores set of possible delta values at position (i, j)
13    // delta represents the difference in wildcard counts between s1 and s2
14    // positive delta means s1 has more wildcards to consume
15    // negative delta means s2 has more wildcards to consume
16    Set<Integer>[][] dp = new HashSet[s1Length + 1][s2Length + 1];
17  
18    // Initialize all sets in the dp array
19    for (int i = 0; i <= s1Length; i++) {
20        for (int j = 0; j <= s2Length; j++) {
21            dp[i][j] = new HashSet<>();
22        }
23    }
24  
25    // Initialize: at position (0, 0) with no wildcard difference
26    dp[0][0].add(0);
27  
28    // Process all positions in both strings
29    for (int i = 0; i <= s1Length; i++) {
30        for (int j = 0; j <= s2Length; j++) {
31            // Process each possible delta value at current position
32            for (int delta : dp[i][j]) {
33              
34                // Case 1: Parse consecutive digits in s1 as a wildcard number
35                if (delta <= 0) {
36                    int wildcardValue = 0;
37                    // Parse up to 3 consecutive digits (max wildcard is 999)
38                    for (int nextPos = i; nextPos < Math.min(i + 3, s1Length); nextPos++) {
39                        if (isDigit(s1.charAt(nextPos))) {
40                            wildcardValue = wildcardValue * 10 + (s1.charAt(nextPos) - '0');
41                            // Add this wildcard value to delta
42                            dp[nextPos + 1][j].add(delta + wildcardValue);
43                        } else {
44                            break; // Stop if we encounter a non-digit
45                        }
46                    }
47                }
48              
49                // Case 2: Parse consecutive digits in s2 as a wildcard number
50                if (delta >= 0) {
51                    int wildcardValue = 0;
52                    // Parse up to 3 consecutive digits (max wildcard is 999)
53                    for (int nextPos = j; nextPos < Math.min(j + 3, s2Length); nextPos++) {
54                        if (isDigit(s2.charAt(nextPos))) {
55                            wildcardValue = wildcardValue * 10 + (s2.charAt(nextPos) - '0');
56                            // Subtract this wildcard value from delta
57                            dp[i][nextPos + 1].add(delta - wildcardValue);
58                        } else {
59                            break; // Stop if we encounter a non-digit
60                        }
61                    }
62                }
63              
64                // Case 3: Match a letter in s1 with pending wildcards from s2
65                if (i < s1Length && delta < 0 && !isDigit(s1.charAt(i))) {
66                    // Consume one wildcard from s2 to match letter in s1
67                    dp[i + 1][j].add(delta + 1);
68                }
69              
70                // Case 4: Match a letter in s2 with pending wildcards from s1
71                if (j < s2Length && delta > 0 && !isDigit(s2.charAt(j))) {
72                    // Consume one wildcard from s1 to match letter in s2
73                    dp[i][j + 1].add(delta - 1);
74                }
75              
76                // Case 5: Match two identical letters when no wildcards are pending
77                if (i < s1Length && j < s2Length && delta == 0 && s1.charAt(i) == s2.charAt(j)) {
78                    // Both letters match, move to next position with delta = 0
79                    dp[i + 1][j + 1].add(0);
80                }
81            }
82        }
83    }
84  
85    // Check if we can reach the end of both strings with balanced wildcards
86    return dp[s1Length][s2Length].contains(0);
87}
88
89/**
90 * Checks if a character is a single digit (0-9)
91 * @param c - Character to check
92 * @return true if the character is a digit, false otherwise
93 */
94private boolean isDigit(char c) {
95    return c >= '0' && c <= '9';
96}
97
1#include <vector>
2#include <unordered_set>
3#include <string>
4#include <algorithm>
5
6class Solution {
7public:
8    /**
9     * Determines if two strings with wildcard numbers can possibly be equal
10     * Numbers in strings represent that many lowercase letters
11     * @param s1 - First string containing letters and numbers
12     * @param s2 - Second string containing letters and numbers
13     * @returns true if the strings can possibly be equal, false otherwise
14     */
15    bool possiblyEquals(std::string s1, std::string s2) {
16        int s1Length = s1.length();
17        int s2Length = s2.length();
18      
19        // dp[i][j] stores set of possible delta values at position (i, j)
20        // delta represents the difference in wildcard counts between s1 and s2
21        // positive delta means s1 has more wildcards to consume
22        // negative delta means s2 has more wildcards to consume
23        std::vector<std::vector<std::unordered_set<int>>> dp(
24            s1Length + 1, 
25            std::vector<std::unordered_set<int>>(s2Length + 1)
26        );
27      
28        // Initialize: at position (0, 0) with no wildcard difference
29        dp[0][0].insert(0);
30      
31        // Process all positions in both strings
32        for (int i = 0; i <= s1Length; i++) {
33            for (int j = 0; j <= s2Length; j++) {
34                // Process each possible delta value at current position
35                for (int delta : dp[i][j]) {
36                  
37                    // Case 1: Parse consecutive digits in s1 as a wildcard number
38                    if (delta <= 0) {
39                        int wildcardValue = 0;
40                        // Parse up to 3 consecutive digits (max wildcard is 999)
41                        for (int nextPos = i; nextPos < std::min(i + 3, s1Length); nextPos++) {
42                            if (isDigit(s1[nextPos])) {
43                                wildcardValue = wildcardValue * 10 + (s1[nextPos] - '0');
44                                // Add this wildcard value to delta
45                                dp[nextPos + 1][j].insert(delta + wildcardValue);
46                            } else {
47                                break; // Stop if we encounter a non-digit
48                            }
49                        }
50                    }
51                  
52                    // Case 2: Parse consecutive digits in s2 as a wildcard number
53                    if (delta >= 0) {
54                        int wildcardValue = 0;
55                        // Parse up to 3 consecutive digits (max wildcard is 999)
56                        for (int nextPos = j; nextPos < std::min(j + 3, s2Length); nextPos++) {
57                            if (isDigit(s2[nextPos])) {
58                                wildcardValue = wildcardValue * 10 + (s2[nextPos] - '0');
59                                // Subtract this wildcard value from delta
60                                dp[i][nextPos + 1].insert(delta - wildcardValue);
61                            } else {
62                                break; // Stop if we encounter a non-digit
63                            }
64                        }
65                    }
66                  
67                    // Case 3: Match a letter in s1 with pending wildcards from s2
68                    if (i < s1Length && delta < 0 && !isDigit(s1[i])) {
69                        // Consume one wildcard from s2 to match letter in s1
70                        dp[i + 1][j].insert(delta + 1);
71                    }
72                  
73                    // Case 4: Match a letter in s2 with pending wildcards from s1
74                    if (j < s2Length && delta > 0 && !isDigit(s2[j])) {
75                        // Consume one wildcard from s1 to match letter in s2
76                        dp[i][j + 1].insert(delta - 1);
77                    }
78                  
79                    // Case 5: Match two identical letters when no wildcards are pending
80                    if (i < s1Length && j < s2Length && delta == 0 && s1[i] == s2[j]) {
81                        // Both letters match, move to next position with delta = 0
82                        dp[i + 1][j + 1].insert(0);
83                    }
84                }
85            }
86        }
87      
88        // Check if we can reach the end of both strings with balanced wildcards
89        return dp[s1Length][s2Length].count(0) > 0;
90    }
91  
92private:
93    /**
94     * Checks if a character is a single digit (0-9)
95     * @param c - Character to check
96     * @returns true if the character is a digit, false otherwise
97     */
98    bool isDigit(char c) {
99        return c >= '0' && c <= '9';
100    }
101};
102
1/**
2 * Determines if two strings with wildcard numbers can possibly be equal
3 * Numbers in strings represent that many lowercase letters
4 * @param s1 - First string containing letters and numbers
5 * @param s2 - Second string containing letters and numbers
6 * @returns true if the strings can possibly be equal, false otherwise
7 */
8function possiblyEquals(s1: string, s2: string): boolean {
9    const s1Length = s1.length;
10    const s2Length = s2.length;
11  
12    // dp[i][j] stores set of possible delta values at position (i, j)
13    // delta represents the difference in wildcard counts between s1 and s2
14    // positive delta means s1 has more wildcards to consume
15    // negative delta means s2 has more wildcards to consume
16    const dp: Set<number>[][] = Array.from(
17        { length: s1Length + 1 }, 
18        () => Array.from(
19            { length: s2Length + 1 }, 
20            () => new Set<number>()
21        )
22    );
23  
24    // Initialize: at position (0, 0) with no wildcard difference
25    dp[0][0].add(0);
26
27    // Process all positions in both strings
28    for (let i = 0; i <= s1Length; i++) {
29        for (let j = 0; j <= s2Length; j++) {
30            // Process each possible delta value at current position
31            for (const delta of dp[i][j]) {
32              
33                // Case 1: Parse consecutive digits in s1 as a wildcard number
34                if (delta <= 0) {
35                    let wildcardValue = 0;
36                    // Parse up to 3 consecutive digits (max wildcard is 999)
37                    for (let nextPos = i; nextPos < Math.min(i + 3, s1Length); nextPos++) {
38                        if (isDigit(s1[nextPos])) {
39                            wildcardValue = wildcardValue * 10 + Number(s1[nextPos]);
40                            // Add this wildcard value to delta
41                            dp[nextPos + 1][j].add(delta + wildcardValue);
42                        } else {
43                            break; // Stop if we encounter a non-digit
44                        }
45                    }
46                }
47
48                // Case 2: Parse consecutive digits in s2 as a wildcard number
49                if (delta >= 0) {
50                    let wildcardValue = 0;
51                    // Parse up to 3 consecutive digits (max wildcard is 999)
52                    for (let nextPos = j; nextPos < Math.min(j + 3, s2Length); nextPos++) {
53                        if (isDigit(s2[nextPos])) {
54                            wildcardValue = wildcardValue * 10 + Number(s2[nextPos]);
55                            // Subtract this wildcard value from delta
56                            dp[i][nextPos + 1].add(delta - wildcardValue);
57                        } else {
58                            break; // Stop if we encounter a non-digit
59                        }
60                    }
61                }
62
63                // Case 3: Match a letter in s1 with pending wildcards from s2
64                if (i < s1Length && delta < 0 && !isDigit(s1[i])) {
65                    // Consume one wildcard from s2 to match letter in s1
66                    dp[i + 1][j].add(delta + 1);
67                }
68
69                // Case 4: Match a letter in s2 with pending wildcards from s1
70                if (j < s2Length && delta > 0 && !isDigit(s2[j])) {
71                    // Consume one wildcard from s1 to match letter in s2
72                    dp[i][j + 1].add(delta - 1);
73                }
74
75                // Case 5: Match two identical letters when no wildcards are pending
76                if (i < s1Length && j < s2Length && delta === 0 && s1[i] === s2[j]) {
77                    // Both letters match, move to next position with delta = 0
78                    dp[i + 1][j + 1].add(0);
79                }
80            }
81        }
82    }
83  
84    // Check if we can reach the end of both strings with balanced wildcards
85    return dp[s1Length][s2Length].has(0);
86}
87
88/**
89 * Checks if a character is a single digit (0-9)
90 * @param char - Character to check
91 * @returns true if the character is a digit, false otherwise
92 */
93function isDigit(char: string): boolean {
94    return /^\d{1}$/g.test(char);
95}
96

Time and Space Complexity

Time Complexity: O(n * m * (n + m))

The algorithm uses dynamic programming with three nested loops:

  • The outer two loops iterate through positions i from 0 to n and j from 0 to m, giving us O(n * m) iterations
  • For each (i, j) position, we iterate through all values in dp[i][j] set. In the worst case, the set can contain O(n + m) different delta values because:
    • Delta represents the difference in "virtual positions" between the two strings
    • The maximum positive delta occurs when s1 has consumed all its digits (up to 3n in value)
    • The maximum negative delta occurs when s2 has consumed all its digits (up to 3m in value)
    • The range of possible deltas is bounded by O(n + m)
  • Inside each delta iteration, we perform operations that take at most O(1) time (the inner loops for parsing digits are bounded by constant 3)

Therefore, the total time complexity is O(n * m * (n + m)).

Space Complexity: O(n * m * (n + m))

The space is dominated by the dp array:

  • We create a 2D array of size (n + 1) × (m + 1)
  • Each cell contains a Set that can hold up to O(n + m) different delta values in the worst case
  • Therefore, the total space complexity is O(n * m * (n + m))

Learn more about how to find time and space complexity quickly.

Common Pitfalls

1. Incorrect Handling of Multi-Digit Numbers

Pitfall: A common mistake is treating each digit independently rather than considering all possible ways to parse consecutive digits. For example, "12" could represent:

  • A single number 12 (matching 12 characters)
  • Two separate numbers 1 and 2 (matching 1 and 2 characters respectively)

Why it happens: It's tempting to greedily parse digits or use a simpler approach that doesn't explore all interpretations.

Solution: The code correctly handles this by using nested loops that try all possible digit sequence lengths (up to 3):

for next_pos in range(i, min(i + 3, s1_length)):
    if is_digit(s1[next_pos]):
        wildcard_value = wildcard_value * 10 + int(s1[next_pos])
        dp[next_pos + 1][j].add(delta + wildcard_value)

2. Misunderstanding the Delta Mechanism

Pitfall: Incorrectly interpreting what the delta value represents or when to allow certain transitions. Common errors include:

  • Allowing digit parsing from s1 when delta > 0 (s1 is already ahead)
  • Allowing digit parsing from s2 when delta < 0 (s2 is already ahead)

Why it happens: The delta concept is counterintuitive - it tracks the "debt" of characters that need to be matched.

Solution: The code enforces correct constraints:

  • Only parse digits from s1 when delta <= 0 (s1 is not ahead)
  • Only parse digits from s2 when delta >= 0 (s2 is not ahead)
  • Only match letters against wildcards when there's a corresponding debt

3. Forgetting to Break on Non-Digit Characters

Pitfall: When parsing consecutive digits, forgetting to stop when encountering a letter:

# WRONG - continues even after hitting a letter
for next_pos in range(i, min(i + 3, s1_length)):
    wildcard_value = wildcard_value * 10 + int(s1[next_pos])
    dp[next_pos + 1][j].add(delta + wildcard_value)

Why it happens: Overlooking that digit sequences must be contiguous.

Solution: Always check if the character is a digit and break if not:

if is_digit(s1[next_pos]):
    wildcard_value = wildcard_value * 10 + int(s1[next_pos])
    dp[next_pos + 1][j].add(delta + wildcard_value)
else:
    break  # Stop parsing when we hit a non-digit

4. Using Insufficient Data Structure for DP State

Pitfall: Using a 2D boolean array dp[i][j] instead of storing sets of possible delta values:

# WRONG - loses information about possible states
dp = [[False] * (m + 1) for _ in range(n + 1)]

Why it happens: Trying to simplify the state space without realizing that multiple delta values can lead to the same (i, j) position.

Solution: Use sets to store all possible delta values at each position:

dp = [[set() for _ in range(s2_length + 1)] for _ in range(s1_length + 1)]

5. Off-by-One Errors in Index Management

Pitfall: Incorrectly managing indices when transitioning between states, especially when parsing multi-digit numbers:

# WRONG - might access out of bounds or skip positions
for next_pos in range(i + 1, i + 4):  # Should start at i, not i+1
    if next_pos < s1_length and is_digit(s1[next_pos]):
        ...

Why it happens: Confusion about whether indices represent positions before or after consuming characters.

Solution: Carefully track that dp[i][j] means we've consumed exactly i characters from s1 and j from s2, and update indices accordingly.

Discover Your Strengths and Weaknesses: Take Our 5-Minute Quiz to Tailor Your Study Plan:

Which two pointer techniques do you use to check if a string is a palindrome?

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