Teachers

Let’s get practical

Exercise 1

Break down the problem

Sometimes the hardest part of programming is not writing code, but understanding what needs to be done. In this exercise, your task is to think through the problem before coding.

Problem:

Given a sentence, return the longest word.

Before writing any code, do the following:

Rewrite the problem in your own words.
Identify the input and the output.
Write at least 3 example inputs and outputs.
Describe the steps you would take to solve it using plain English.
List possible edge cases (empty string, punctuation, multiple words with the same length).

For example:

findLongestWord("I love programming")// returns "programming"
findLongestWord("Hi there")// returns "there"
findLongestWord("")// what should this return?

Exercise 2

Find a number using binary search

Sometimes data is already sorted, and checking every value one by one is not the best approach. In this exercise, you will learn about binary search and use it to solve a problem efficiently.

Problem:

Given a sorted array of numbers and a target value, return the index of the target using binary search. If the value does not exist, return -1.

Before writing the solution, make sure you understand how binary search works. You can explore this by searching on Google or YouTube for explanations and visual examples, and then apply what you learn to solve the problem.

For example:

binarySearch([1,3,5,7,9],5)// returns 2
binarySearch([1,3,5,7,9],1)// returns 0
binarySearch([1,3,5,7,9],9)// returns 4
binarySearch([1,3,5,7,9],4)// returns -1

Think about:

Why must the array be sorted?
What happens if the array is empty?
How does this approach differ from checking every element?

Exercise 3

Observe how work grows

When writing code, it’s important to understand how the amount of work changes as the data grows. Look at the code snippets below and think about how many operations happen when the array becomes larger.

For each snippet, answer:

Does the amount of work grow slowly or quickly as the data grows?
Is the time complexity O(1), O(n), or O(n²)?

// A
const firstItem = arr[0];

// B
for (let i = 0; i < arr.length; i++) {
  console.log(arr[i]);
}

// C
for (let i = 0; i < arr.length; i++) {
  for (let j = 0; j < arr.length; j++) {
    console.log(i, j);
  }
}

Think about what happens if the array has:

5 items
100 items
10,000 items

Exercise 4

Observe program behavior

It’s important to understand what your code is doing step by step. Look at the function below, which calculates the sum of numbers in an array.

function sum(numbers) {
  let total = 0;
  for (let num of numbers) {
    total += num;
  }
  return total;
}

Add console.log statements to:

Log the value of total after each addition
Log the current number being added

Run the function with different inputs and carefully observe the output.

Exercise 5

Find and fix the bug

The function below is meant to return the result of multiplying all numbers in an array, but it contains a bug.

function multiply(numbers) {
  let result = 1;
  for (let i = 0; i <= numbers.length; i++) {
    result *= numbers[i];
  }
  return result;
}

Find the issue and fix it.

Test your solution with different arrays to make sure it works correctly.

Exercise 6

Write test cases

Sometimes code looks correct, but testing reveals problems. Look at the function below:

function isEven(number) {
  return number % 2 === 0;
}

Write test cases by describing:

The input value
The expected output

Include test cases for:

A normal case
An edge case
An invalid input

Think about how this function should behave in each situation.

CC BY-NC-SA 4.0 Icons

*https://hackyourfuture.net/*

Found a mistake or have a suggestion? Let us know in the feedback form.

Week 5 - Problem solving methods