Jump Game Problem in DSA Javascript - Time & Space Complexity
We want to understand how the time needed to solve the Jump Game problem changes as the input array grows.
Specifically, how does the number of steps to check jumps grow with the size of the array?
Analyze the time complexity of the following code snippet.
function canJump(nums) {
let maxReach = 0;
for (let i = 0; i < nums.length; i++) {
if (i > maxReach) return false;
maxReach = Math.max(maxReach, i + nums[i]);
}
return true;
}
This code checks if you can jump from the start to the end of the array, where each number tells the max jump length from that position.
Identify the loops, recursion, array traversals that repeat.
- Primary operation: A single loop that goes through the array once.
- How many times: Exactly once for each element in the array.
As the array size grows, the number of steps grows directly with it.
| Input Size (n) | Approx. Operations |
|---|---|
| 10 | About 10 checks |
| 100 | About 100 checks |
| 1000 | About 1000 checks |
Pattern observation: The work grows in a straight line with the input size.
Time Complexity: O(n)
This means the time to decide if you can jump to the end grows linearly with the number of positions.
[X] Wrong: "Because we check jumps from each position, the time is quadratic O(n²)."
[OK] Correct: The code only loops once through the array and updates the farthest reachable index without nested loops, so it does not multiply the work.
Understanding this linear time solution shows you can optimize problems by avoiding unnecessary repeated checks, a key skill in interviews.
"What if the code used nested loops to check all possible jumps from each position? How would the time complexity change?"
Practice
Solution
Step 1: Understand the problem statement
The Jump Game problem asks if it is possible to move from the first index to the last index by jumping according to the values in the array.Step 2: Identify the goal
The goal is to check if the last index is reachable, not the number of jumps or maximum jump length.Final Answer:
If you can reach the last index starting from the first index -> Option AQuick Check:
Jump Game = Reach last index [OK]
- Confusing reachability with minimum jumps
- Thinking about maximum jump length only
- Assuming sum of jumps matters
i to index j in JavaScript, given an array nums?Solution
Step 1: Understand jump condition
You can jump from index i to j if j is within the jump length from i, i.e., j ≤ i + nums[i].Step 2: Match condition with options
if (j <= i + nums[i]) correctly checks if j ≤ i + nums[i]. Other options compare wrong values or use incorrect operators.Final Answer:
if (j <= i + nums[i]) -> Option DQuick Check:
Jump condition = j ≤ i + nums[i] [OK]
- Comparing nums[j] instead of j
- Using < instead of ≤
- Mixing indices and values incorrectly
function canJump(nums) {
let maxReach = 0;
for (let i = 0; i < nums.length; i++) {
if (i > maxReach) return false;
maxReach = Math.max(maxReach, i + nums[i]);
}
return true;
}
console.log(canJump([2,3,1,1,4]));
console.log(canJump([3,2,1,0,4]));Solution
Step 1: Trace first input [2,3,1,1,4]
maxReach updates as: i=0 maxReach=2, i=1 maxReach=4, i=2 maxReach=4, i=3 maxReach=4, i=4 maxReach=8. No i > maxReach, so returns true.Step 2: Trace second input [3,2,1,0,4]
maxReach updates: i=0 maxReach=3, i=1 maxReach=3, i=2 maxReach=3, i=3 maxReach=3, i=4 i=4 > maxReach=3 triggers return false.Final Answer:
true false -> Option AQuick Check:
First array reachable, second not [OK]
- Not updating maxReach correctly
- Returning true too early
- Ignoring the condition i > maxReach
function canJump(nums) {
let maxReach = 0;
for (let i = 0; i <= nums.length; i++) {
if (i > maxReach) return false;
maxReach = Math.max(maxReach, i + nums[i]);
}
return true;
}Solution
Step 1: Analyze loop boundary
The loop runs from i = 0 to i <= nums.length, which means it accesses nums[nums.length], causing undefined access.Step 2: Correct loop condition
The loop should run while i < nums.length to avoid out-of-bounds errors.Final Answer:
The loop condition should be i < nums.length, not i <= nums.length -> Option BQuick Check:
Loop boundary off by one error [OK]
- Using <= instead of < in loops
- Misinitializing maxReach
- Placing return true inside loop
nums = [1,2,0,1,0,2,0], which of the following statements is true about reaching the last index using the Jump Game logic?Solution
Step 1: Trace maxReach for [1,2,0,1,0,2,0]
i=0, maxReach=1; i=1, maxReach=3; i=2, maxReach=3; i=3, maxReach=4; i=4, maxReach=4; i=5 >4, cannot reach index 6.Step 2: Analyze blocking
Zeros at indices 2,4 limit jumps from reachable positions (max=4), blocking paths to end.Final Answer:
You cannot reach the last index because zeros block all paths -> Option CQuick Check:
Max reach=4 < length-1=6 [OK]
- Thinking zeros can always be skipped sufficiently
- Assuming jumps must be fixed length
- Believing backward jumps are allowed
Ready to prove it?
Pass the test and this pattern moves unknown
