Advanced Topics in Computer Science
Unit 2: Sorting, Searching, and Algorithm Efficiency
Students compare algorithms by correctness, runtime, memory, and implementation complexity, with sorting and searching as the main laboratory.
Unit Focus
What this unit is really teaching
This unit builds the Big-O vocabulary needed for data structures, competitive programming, and college CS.
Key Topics
- +Linear search, binary search, and preconditions for efficient lookup
- +Selection sort, insertion sort, merge sort, quicksort ideas, and heap sort preview
- +Best, average, and worst-case runtime reasoning
- +Big-O, Big-Omega, and Big-Theta intuition at an age-appropriate level
- +Empirical timing experiments and input-size growth
- +Stability, in-place sorting, recursion depth, and memory tradeoffs
Practice Work
Implementation and analysis tasks
Student task
Benchmark several search and sort algorithms on random, sorted, and nearly sorted data.
Student task
Create an algorithm comparison report with traces and runtime tables.
Need support with Unit 2?
Work through the concepts, code, edge cases, and runtime analysis with 1:1 guidance.