Resources

Textbooks

We don’t have a textbook for the course. Here are some references:

• Introduction to Data Structures and Algorithms in Java from a previous incarnation of this course.
• Open Data Structures by Pat Morin — mathematically precise, freely available online.
• Data Structures and Algorithm Analysis by Clifford A. Shaffer — free PDF, good complement to CLRS.

For more advanced material, refer to the following texts:

• algorithms.wtf - Jeff Erikson: Algorithms — a free, very readable introduction to algorithms & data structures.
• CLRS — Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms (4th ed.) — the gold standard reference for rigorous algorithm analysis.
• Sedgewick & Wayne — Algorithms (4th ed.) — accessible coverage with strong emphasis on implementation.

Kotlin Reference

You already know Kotlin; these are lookup references for the parts that come up most in DSA work.

• Collections overview — List, Set, Map, ArrayDeque, mutability, and collection operations.
• Sequences — lazy evaluation; useful when chaining transformations over large datasets.
• Kotlin standard library API — full API reference; search for sortedWith, groupBy, fold, etc.

DSA in Kotlin

• Data Structures & Algorithms in Kotlin (Kodeco / Ray Wenderlich) — works through the canonical structures and algorithms with Kotlin implementations.
• Hands-On Data Structures and Algorithms with Kotlin (Packt) — production-oriented; good for seeing idiomatic Kotlin applied to classical problems.

Algorithm Visualization

These tools are language-agnostic and useful for building intuition:

• VisuAlgo — step-through animations for 24+ structures and algorithms; supports custom input.
• Algorithm Visualizer — open-source, community-driven; lets you trace execution with annotated pseudocode.

Complexity Reference

• Big-O Cheat Sheet — time and space complexities for common structures and sorting algorithms at a glance.

Practice

Both platforms support Kotlin submission:

• LeetCode — graded problems across all difficulty levels; good for targeted practice by topic.
• Codeforces — competitive programming with an active Kotlin community; useful for timed practice.

Typesetting (LaTeX)

Technical documents in this course may require mathematical notation. LaTeX is the standard tool.

Good starting points:

• Getting to Grips with LaTeX — practical tutorial for newcomers.
• Overleaf — browser-based LaTeX editor; no local installation needed.
• Detexify — draw a symbol and get the LaTeX command for it.
• The Wikibook on LaTeX — comprehensive reference organized by topic.

For local editing, any text editor works. Recommended options:

• Visual Studio Code with the LaTeX Workshop extension
• TeXStudio — dedicated LaTeX IDE