Max sum of k in a row
one step at a time.
Slide a window of k numbers along the array: add the number that comes in, subtract the one that goes out.
Free to use. Step forward and back at your pace, and share a link to the exact step you are stuck on.
What you actually watch.
The part a dry run on paper loses: the state, at every step.
Slide a window of k numbers along the array: add the number that comes in, subtract the one that goes out. That sentence is easy to agree with and hard to hold in your head on step nine, which is where most people lose the thread.
So the visualiser keeps it in front of you: the window growing and shrinking, with the running total inside it. The line of code being executed is highlighted as the picture changes, so the drawing and the code never drift apart. Step forward, step back, or let it play.
Put your own input in. Max sum of k in a row on a clean example teaches you the shape; max sum of k in a row on an empty input, a single element, or one with duplicates teaches you the thing an interviewer asks about.
How it runs, step by step.
The same order the visualiser moves in, so the list and the picture match.
- 1Grow the window by taking in the element on the right.
- 2Update the running total or count for what just entered.
- 3While the window breaks the rule, drop elements from the left.
- 4Record the best window seen so far. The left edge never moves back.
Where people get this one wrong.
These are not made up. Each one is a switch in the tool: turn it on, run the same input, and watch the state go wrong.
- Brute forceRe-adds all k numbers of every window: about n × k additions instead of about 2n. Try a wide window.
Inputs worth trying.
The cases that teach something. Each one is a preset in the tool, with the reason it is there.
- k = 1Each window is one number, so this finds the maximum. Sliding saves nothing here.
- k = nOnly one window fits, so the loop never slides.
- All negativeEvery sum is below 0. best starts from the first window, never from 0.
- k > nNo window fits at all.
- Every window tiesOnly a bigger sum replaces best, so the first window is kept.
- Wide windowRun brute force here too: it re-adds 6 numbers for every window.
What it costs.
The two numbers an interviewer will ask for, and what they mean here.
- Time
- O(n)counted as real operations while it runs, not quoted from a table
- Space
- O(1)what the algorithm holds besides the input itself
- Pattern
- Sliding windowGrow the right edge, shrink the left, never look back.
Once you can see it, go and use it.
Watching is the first ten minutes. The pattern sticks when you solve with it.
Everything in the app, in one place.
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About max sum of k in a row.
Open it in the app and the answers are easier to see than to read.
Open the visualiserWhat does the max sum of k in a row visualiser show?
Every step of the algorithm on input you choose: the window growing and shrinking, with the running total inside it, with the line of code being executed highlighted beside it. You can step forward, step back, or let it play. Spelled visualizer or visualiser, it is the same tool.
What is the time complexity of max sum of k in a row?
O(n) time and O(1) space. The visualiser counts the real operations as it runs, so you can watch the number grow instead of taking the formula on trust.
Can I use my own input?
Yes. Type your own array, string or graph and the algorithm runs on that, including the edge cases that break a solution in an interview.
Is it free?
Yes. The app is free to start, with 100 AI credits when you sign up and 100 every month, and watching an algorithm costs no credits.