Lesson 1 of 87 min read
Why SDET interviews ask DSA, and Big-O in plain words
SDET and automation interviews usually include one or two coding questions. They are rarely hard puzzles: they check that you can turn a problem into clean, working code and reason about how fast it runs. This lesson explains what interviewers look for and how to talk about speed using Big-O.
Key takeaways
- 1Most SDET coding rounds use easy to medium questions: strings, arrays, maps, counting and simple patterns.
- 2Interviewers score how you think: clarify the problem, list test cases, write code, then test it yourself.
- 3Big-O describes how work grows with input size n. O(1) constant, O(n) one pass, O(n log n) sorting, O(n^2) nested loops.
- 4Space complexity counts extra memory, such as a new map or array you create.
- 5As a tester, your edge-case thinking is an advantage: empty input, one element, duplicates, negatives, very large input.
Same task, two speeds
// Does the array contain a duplicate?
// O(n^2): compare every pair
static boolean hasDupSlow(int[] a) {
for (int i = 0; i < a.length; i++)
for (int j = i + 1; j < a.length; j++)
if (a[i] == a[j]) return true;
return false;
}
// O(n) time, O(n) space: remember what we have seen
static boolean hasDupFast(int[] a) {
java.util.Set<Integer> seen = new java.util.HashSet<>();
for (int x : a) if (!seen.add(x)) return true;
return false;
}
Go deeper
Expert notes beyond the basics
- 01
What the scorecard looks like
Typical SDET coding feedback covers four things: problem understanding, correctness, code quality (names, small methods) and testing. A working simple solution with good tests often beats a clever one with bugs.
- 02
Reading Big-O quickly
Count the loops over the input. One loop is O(n). A loop inside a loop is O(n^2). Halving each step is O(log n). Sorting is O(n log n). Drop constants: two separate loops are still O(n).
Common mistakes to avoid
- - Coding before asking any questions.
- - Saying 'it's fast' instead of giving Big-O.
- - Forgetting empty and null input.
- - Staying silent while thinking.
Try it yourself
Give the Big-O of: (a) printing every pair in an array, (b) finding the max, (c) sorting then reading the first element.
Write your answer on paper or in a sheet first, then compare.
Interview questions
How to answer like a confident QA engineer
- Q1
What is the time complexity of a loop inside a loop over the same array?
Model answer
O(n squared), because for each of the n elements the inner loop does up to n steps. If the inner loop is over a different collection of size m, it is O(n times m). I would mention whether a hash set or sorting could bring it down to O(n) or O(n log n).
- Q2
What is space complexity?
Model answer
The extra memory an algorithm needs as input grows, not counting the input itself. A HashSet of all elements is O(n) space.
- Q3
Is O(2n) different from O(n)?
Model answer
No. Big-O ignores constant factors, so both are linear.
Knowledge check
+5 points
Which complexity describes a single pass over an array?