Comments (2)
This is important. Until now, I've been OK with what the interviewer was satisfied with and didn't actually prove/calculate optimality. This is bad because 'interviews' are not the goal of Data Structures or Algorithm Design for that matter.
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My quick and dirty way to 'estimate' optimality. For coding questions, I calculate the time complexity of my solution and make sure it is less than 108 ops/second. But, as said, it's not about winning contests, I need to prove optimality.
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Related Issues (19)
- Complementary course I did before this
- Sliding window technique is actually a special case of Dynamic programming HOT 2
- Calculating resource complexity, especially for recurrences HOT 1
- Programmatically + visually working with graphs
- Dividing problem into "very small halves" for DnC may not always work HOT 2
- "Kind of DnC" - using partitioning as a way to avoid brute-force enumeration
- DSA Interview Cheatsheet
- The trick to single pass array problems, and more HOT 1
- Make utils/generators for DSA
- C++ STL YouTube playlist
- Algorithms on Strings course, Coursera
- Geometric algorithms, 2 courses on Coursera
- Competitive programming courses
- OOP roadmap
- Dynamic Programming course
- Deeply study the 2 conditions for DP HOT 2
- Recursive DP vs Iterative DP vs memoization vs tabulation
- Recursion base case may not always be useful even if it's logically valid for the base case, is this true? HOT 2
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