Dynamic Arrays & Amortised Cost, Capstone: Choose the Algorithm
This lesson is part of the course
In this lesson
You count the copies a growing list makes with doubling and with fixed steps, then work out run times for three ways of finding duplicates and choose the one that fits both the time and the memory budget.
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Lessons in this course
- Counting Steps: Single, Nested and Halving Loops Locked
- Growth Tables: n log n, n², 2ⁿ and Where the Curves Cross Locked
- Linear vs Binary Search: Worst-Case Comparisons and a Traced Search Locked
- Sorting Comparisons: n(n−1)/2 vs n · log₂ n and One Traced Pass Locked
- Time Budgets: Steps per Second, Run Times and the Largest n in One Second Locked
- Hash Tables: Load Factor, Expected Probes and Resize Thresholds Locked
- Caching: Hit Rates, Average Access Time and Cache Size Locked
- Dynamic Arrays & Amortised Cost, Capstone: Choose the Algorithm Locked