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Algorithm
A practical guide to coding interviews: what interviewers assess, common problem patterns, a step-by-step solving routine and how to explain complexity.
Coding interview strategy is the set of habits and techniques for solving an algorithm problem under time pressure while explaining your reasoning out loud. It combines a repeatable procedure (clarify the problem, work through examples, start from brute force, optimize, code and test) with a small toolkit of recurring patterns such as hash maps, two pointers, sliding windows and prefix sums.
Many companies screen developers with coding tests and live coding rounds, and they grade more than the final answer: understanding, problem solving, code quality, testing and communication all count. A clear process helps you show those skills even when you do not reach the optimal solution, and it carries over directly to everyday debugging and code review.
Study by pattern rather than by sheer volume: learn one pattern, solve a few problems that use it, then explain the solution and its complexity out loud as if to an interviewer. Practice under a timer, check your code against edge cases and a brute-force reference, and finish with mock interviews.
Clarify input sizes, edge cases and output format first; the answers often decide which algorithm is feasible.
State a simple correct solution and its complexity, find the repeated work and remove it with the right data structure.
Clues such as “sorted”, “contiguous” or “seen before” point to two pointers, sliding windows or hash maps.
Narrate your decisions, trace small examples by hand and check edge cases before calling the code done.
longest_unique_window returns the length of the longest substring with no repeated character. It advances the right edge one step at a time, remembers where each character was last seen and, on a repeat inside the window, jumps the left edge just past it, so each index is handled a constant number of times: O(n) time. Run python sliding_window.py to print the results for a few sample strings.
sliding_window.py
def longest_unique_window(s: str) -> int:
"""Length of the longest substring without a repeated character (sliding window)."""
last_seen = {}
left = best = 0
for right, ch in enumerate(s):
if last_seen.get(ch, -1) >= left:
left = last_seen[ch] + 1
last_seen[ch] = right
best = max(best, right - left + 1)
return best
if __name__ == "__main__":
for text in ["tastedev", "abba", "interview", ""]:
print(f"{text!r}: {longest_unique_window(text)}")
python sliding_window.pySix chapters that take you from installation to the core ideas of Coding interview strategy.
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