DSA pattern
Greedy
Greedy algorithms make the best choice at each step without reconsidering. Works when problems have greedy choice property (local optimal leads to global optimal) and optimal substructure.
When to use
5 signals- 01Activity selection (intervals)
- 02Jump game problems
- 03Task scheduling
- 04Fractional knapsack
- 05Huffman coding
In interviews, call out the pattern early. It helps interviewers follow your reasoning and keeps your implementation focused. After solving, explain tradeoffs in plain language: why this approach is efficient, where it can break, and what edge cases you would test first.
Practice problems
5 listed- 01Jump GamePractice →
- 02Gas StationPractice →
- 03Task SchedulerPractice →
- 04Meeting Rooms IIPractice →
- 05Partition LabelsPractice →
Build a review loop
Treat each pattern as a repeating cycle, not a one-time read. Solve a fresh problem today, revisit the same pattern in 2-3 days, and run one timed attempt at the end of the week. This turns short-term familiarity into reliable recall for live interviews.
When reviewing, re-derive the core steps from scratch before checking a reference solution. If you can explain the state transitions and edge cases clearly, you are much more likely to execute well under interview pressure.