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Code Implementation
DNA Sequence Analysis Implementation
Below is the implementation of the dna sequence analysis:
solution.js
12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152function longestCommonPrefix(strs) { // Handle edge cases if (strs.length === 0) return ""; if (strs.length === 1) return strs[0]; // Approach 1: Horizontal scanning let prefix = strs[0]; for (let i = 1; i < strs.length; i++) { // Keep reducing the prefix until it's a prefix of the current string while (strs[i].indexOf(prefix) !== 0) { prefix = prefix.substring(0, prefix.length - 1); if (prefix === "") return ""; } } return prefix;} // Alternative approach: Vertical scanningfunction longestCommonPrefixAlt(strs) { // Handle edge cases if (strs.length === 0) return ""; if (strs.length === 1) return strs[0]; // Find the minimum length string let minLength = Infinity; for (let str of strs) { minLength = Math.min(minLength, str.length); } // Compare characters at the same position let result = ""; for (let i = 0; i < minLength; i++) { const char = strs[0][i]; for (let j = 1; j < strs.length; j++) { if (strs[j][i] !== char) { return result; } } result += char; } return result;} // Test casesconsole.log(longestCommonPrefix(["ACGTGGT", "ACGTCAT", "ACGTTGA"])); // "ACGT"console.log(longestCommonPrefix(["GAATTC", "GATTACA", "GATAGC"])); // "GA"console.log(longestCommonPrefix(["TGCAA", "ATCGA", "CGTAT"])); // ""Step-by-Step Explanation
Let's break down the implementation:
- Handle Edge Cases: Check for empty array or single string cases and return appropriate results.
- Initialize Prefix: Start with the first string as the assumed longest common prefix.
- Iterate Through Strings: For each string in the array, compare it with the current prefix.
- Reduce Prefix: If the current string doesn't start with the prefix, reduce the prefix by one character at a time.
- Check for Empty Prefix: If the prefix becomes empty at any point, return an empty string as there is no common prefix.
String Problems
Learning Objective
Implement the dna sequence analysis solution in different programming languages.
DNA Sequence Analysis Implementation
Below is the implementation of the dna sequence analysis in different programming languages. Select a language tab to view the corresponding code.
solution.js
12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152function longestCommonPrefix(strs) { // Handle edge cases if (strs.length === 0) return ""; if (strs.length === 1) return strs[0]; // Approach 1: Horizontal scanning let prefix = strs[0]; for (let i = 1; i < strs.length; i++) { // Keep reducing the prefix until it's a prefix of the current string while (strs[i].indexOf(prefix) !== 0) { prefix = prefix.substring(0, prefix.length - 1); if (prefix === "") return ""; } } return prefix;} // Alternative approach: Vertical scanningfunction longestCommonPrefixAlt(strs) { // Handle edge cases if (strs.length === 0) return ""; if (strs.length === 1) return strs[0]; // Find the minimum length string let minLength = Infinity; for (let str of strs) { minLength = Math.min(minLength, str.length); } // Compare characters at the same position let result = ""; for (let i = 0; i < minLength; i++) { const char = strs[0][i]; for (let j = 1; j < strs.length; j++) { if (strs[j][i] !== char) { return result; } } result += char; } return result;} // Test casesconsole.log(longestCommonPrefix(["ACGTGGT", "ACGTCAT", "ACGTTGA"])); // "ACGT"console.log(longestCommonPrefix(["GAATTC", "GATTACA", "GATAGC"])); // "GA"console.log(longestCommonPrefix(["TGCAA", "ATCGA", "CGTAT"])); // ""Step-by-Step Explanation
1Handle Edge Cases
Check for empty array or single string cases and return appropriate results.
2Initialize Prefix
Start with the first string as the assumed longest common prefix.
3Iterate Through Strings
For each string in the array, compare it with the current prefix.
4Reduce Prefix
If the current string doesn't start with the prefix, reduce the prefix by one character at a time.
5Check for Empty Prefix
If the prefix becomes empty at any point, return an empty string as there is no common prefix.
Language-Specific Notes
JavaScript
- Uses
indexOf(prefix) === 0to check if a string starts with the prefix - Uses
substring(0, length - 1)to reduce the prefix - Alternative approach uses
Math.min()to find the minimum length
Python
- Uses
startswith(prefix)to check if a string starts with the prefix - Uses slice notation
prefix[:-1]to reduce the prefix - Alternative approach uses
all()with a generator expression for concise checking
Java
- Uses
startsWith(prefix)to check if a string starts with the prefix - Uses
substring(0, length - 1)to reduce the prefix - Alternative approach uses
StringBuilderfor efficient string building
C++
- Uses
find(prefix) == 0to check if a string starts with the prefix - Uses
substr(0, length - 1)to reduce the prefix - Alternative approach uses
std::minto find the minimum length
Key Takeaways
- The horizontal scanning approach is intuitive and works well for most cases.
- The vertical scanning approach can be more efficient when the mismatch occurs early or one of the strings is very short.
- Both approaches have the same time complexity of O(S), where S is the sum of all characters in all strings.
- Handling edge cases properly is crucial for this problem.
- This algorithm is useful in various applications like genomics, file systems, and database indexing.
Try It Yourself
Modify the code to implement an alternative approach and test it with the same examples.
Challenge:
Implement a function that solves the dna sequence analysis problem using a different approach than shown above.
Common Edge Cases
Empty Array
If the input array is empty, return an empty string.
longestCommonPrefix([]) → ""
Single String
If the array contains only one string, that string is the longest common prefix.
longestCommonPrefix(["ACGT"]) → "ACGT"
No Common Prefix
If there is no common prefix among the strings, return an empty string.
longestCommonPrefix(["TGCAA", "ATCGA", "CGTAT"]) → ""