Have you ever struggled to develop an algorithm solution on a technical interview? In this short tutorial, we'll break down three top algorithm coding questions, starting with the brute force method (step-by-step but not necessarily performant) and transitioning to a more optimized, elegant solution.
If you find another solution, feel free to post it in the comments!
Reverse a string
Task
Given a string, return the reverse of it.
Solution 1
We can use the string.substring() method to take each letter of the str parameter, and append it to a new string. The substring method takes one required parameter and one optional parameter.
The first parameter is the index from which you want the substring to start. This is inclusive meaning if you write myString.substring(1), the output will include the first character.
The second (optional) parameter is the ending index. This parameter is not inclusive. This means that your substring will include all characters until this index plus every remaining character to the right of that index.
Another string method we could use in the brute force method would be the string.charAt() method. The charAt method takes one parameter: the index of the character you want to return.
Let's write two brute-force algorithms for returning the reverse of a string.
// Method 1: Substring
function reverseString(str) {
let reversedString = '';
/* Loop through this process for each character in the str parameter
In order to get the reverse, we'll initialize i to str.length
Add each character, starting from the end, to the new string.
*/
for (let i = str.length; i > 0; i--) {
reversedString += str.substring(i, i-1);
}
return reversedString;
}
// Method 2: CharAt
function reverseString(str) {
let reversedString = '';
/* Loop through this process for each character in the str parameter
In order to get the reverse, we'll initialize i to str.length - 1
while i is greater than or equal to 0.
Add each character, starting from the end, to the new string.
*/
for (let i = str.length-1; i >= 0; i--) {
reversedString += str.charAt(i);
}
return reversedString;
}
Solution 2
One of the quickest inline ways to solve this problem is to split each character in the string into an array index, reverse the items within the array, and turn the items in each index into a concatenated string.
We'll use the following methods:
-
string.split()method which splits each character into an array index. -
array.reverse()method which reverses an array in place. -
array.join()method which concatenates all array values into a string.
You can chain these three functions together for an elegant, inline solution.
function reverseString(str) {
return str.split('').reverse().join('');
}
Longest Word
Task
Return the length of the longest word in the provided sentence.
Solution 1
For the first attempt, you can use the string.split(' ') method to break the individual words within a sentence into array indeces. This tutorial will not account for punctuation, however you could solve for this with a regular expression.
Next, we can iterate through each index of the array and count the number of letters in each word. We can keep track of the longest word value in a variable. If the current word value is larger than the maximum word value currently saved, replace it! Then, just return the variable containing the longest word.
You can loop through the array using a for-loop or the array.forEach() method. I prefer the latter, but I've included both below.
// Solution with for-loop
function findLongestWordLength(str) {
let maxVal = 0;
const wordArr = str.split(' ');
for(let i = 0; i < wordArr.length; i++) {
let word = wordArr[i];
if (word.length > maxVal) {
maxVal = word.length;
}
}
return maxVal;
}
// Solution with array.forEach method
function findLongestWordLength(str) {
let maxVal = 0;
const wordArr = str.split(' ');
wordArr.forEach(word => {
if (word.length > maxVal) {
maxVal = word.length;
}
});
return maxVal;
}
Solution 2
To optimize this solution, we will still use the string.split() method to separate each word into an array index.
Next, we're going to use the array.map() method to carry out some type of expression on the value within each array index. This will return a completely new array, so we'll save that to a new variable.
For each item in the array, return the length of the string and save it in a new array called arrOfLengths.
Finally, we can use the Math.max(...spreadOperator) method with a spread operator in order to return the integer value for the longest string in a sentence.
function findLongestWordLength(str) {
const arrOfWords = str.split(' ');
const arrOfLengths = arrOfWords.map(item => item.length);
return Math.max(...arrOfLengths);
}
Array Of Largest Sub-Array Values
Task
Return an array consisting of the largest number from each provided sub-array. For simplicity, the provided array will contain exactly 4 sub-arrays.
[1,2,3,4]
[5,18,0,12]
[3,5,12,5]
[28,9,2,34]
Should return => [4,18,12,34]
Solution 1
For the first pass through, we can start with a nested for-loop.
For each item in the outer array, go through its sub array and find the largest value, then push that into a new array.
// For loop
function largestOfFour(arr) {
let arrayOfMaxValues = [];
for (let i = 0; i < arr.length; i++) {
let subArr = arr[i];
let maxSubArrVal = 0;
for (let j = 0; j < subArr.length; j++) {
let currentValue = subArr[j];
if (currentValue > maxSubArrVal) {
maxSubArrVal = currentValue;
}
}
arrayOfMaxValues.push(maxSubArrVal);
}
return arrayOfMaxValues;
}
// For each method
function largestOfFour(arr) {
let arrayOfMaxValues = [];
arr.forEach(subArr => {
let maxSubArrVal = 0;
subArr.forEach(item => {
if (item > maxSubArrVal) {
maxSubArrVal = item;
}
});
arrayOfMaxValues.push(maxSubArrVal);
});
return arrayOfMaxValues;
}
Solution 2
We can use the Math.max(...spreadOperator) method with the array.map() method to loop over each item in the outer array, return the max value from within the sub-array, and return that newly created array directly.
function largestOfFour(arr) {
return arr.map(subArr => Math.max(...subArr));
}
I plan to turn this into a series of posts, so if you enjoyed it make sure to follow me for updates!
Top comments (23)
Love this post!! My only criticism would be that the code transitions between each brute force solution and each optimized solution are not improvements in algorithmic complexity (Big O) but are readability improvements from using standard library functions. I still think it's cool to showcase how knowledge of available standard library methods can clean up solutions tremendously!
Well.. some of them are optimized for better Big O run times, but not all
Unless I'm mistaken (please correct me if I'm wrong), the complexity is O(N) for all 6 solutions, where N is the number of letters in the reversed string, the number of letters in the sentence (because of String#split), and the total number of elements in all the arrays. I definitely apologize for being nitpicky here, but my concern is that newer developers will read this and misunderstand what you mean by "optimize" the solution. In this case you're optimizing readability, which is great, but the algorithmic complexity is unchanged.
I’m not positive how Math.max works and if the last example functions as a double nested loop. The last example wouldn’t necessarily be O(n) as input size grew and varied (but I’m not sure as to specifics). So the first 2 I believe are O(n) while the last one is probably O(n) given that the sub arrays have a finite set of elements, but for growing and variable input could creep up to O(2) But agreed I should change the wording from optimized.
Ahh I understand the confusion now. The last example is definitely tricky because it's easy to read it as one loop. In actuality, Math.max has to iterate over the full argument list in order to produce the maximum, making the last example O(N) if you consider N to be the total number of elements across all of the arrays. You could also say the last example is O(N * M) where N is the number of arrays and M is the number of elements in each array, but this assumes that each array has the same length, which may not be the case.
A great demonstration for beginners, but the terms "brute force" and "optimized" are quite misleading.
Brute force usually means exhaustive search, for example in password cracking, where all the possible combinations of letters are tried. Better term would be "naive".
Optimized usually means faster, better than naive simple method. In these examples no optimized solution is faster than the "brute force". It's still the same asymptotic complexity, but usually more operations, so normally it'd be slower. It's optimized for code size, I give you that.
Actually, all those "ugly", C style version for for loops and nester for loops usually perform better than their functional equivalents, because they usually allocate less memory to store temporaries. For example:
creates an array to store lengths of words. This could be avoided by calculating the maximum on the fly, like in the "brute force" solution. Imagine a situation where you only have memory to store the original list of words, say it's 2GB long. It's still O(n), but requires double the memory.
yes correct! Also in the interviews they(recruiters) would expect us to write the code without using in built methods.
but while working in a software company we should use the in built methods for code readability.
They would? Since when? Where?
In most of the top companies the interviewers will ask us to write the code without using any in build methods.
I guess I understand :/
Great post! I particularly like the use of
Math.maxand spread operator.For returning the length of the longest word I think a single
reducewould be slightly quicker than amapfollowed by aMath.max.e.g.
For anyone interested I posted an performance analysis and some gotchas of these solutions:
Performance measurement of JavaScript solutions to common algorithmic questions (part 1)
Dmitry Yakimenko
Nice work. Would love to see actual performance of each method as well though : )
I'd use this for Longest Word. It's one less iteration, and can be easily modified to return the word.
I've never thought of the trick used in the last two optimized solutions, using
Mathwith a spread operator. Will definitely look into those more!Way better than using Math.max.apply!
Sweet and elegant!
thank you, good article... can you add more problems like these and also can you add javascriptarray problems which can be solved with javascript algorithms?