Dirk Pattinson
RSISE Buliding 115
The Australian National University
Canberra ACT 0200
Australia
E dirk.pattinson@anu.edu.au
T +61 (0)2 6125 8612
F +61 (0)2 6125 8651
The Australian National University
Canberra ACT 0200
Australia
E dirk.pattinson@anu.edu.au
T +61 (0)2 6125 8612
F +61 (0)2 6125 8651
Haskell Online Exercises
They aim to provide the opportunity to self-evaluate programming skills and collect a few problems, together with automated feedback (on functionality only). Try them at http://cs.anu.edu.au/onex/.
Short Haskell Videos
They aim to demonstrate coding skills, starting from scratch.
The Very Basics
- My favourite Number (capitalisation, integers, types, indentation)
- Vectors (type declarations)
- Time Points (product types, function abstraction, where-clauses)
Basic Number Recursion
- Adding Two Numbers (recursion and tail recursion)
- Fibonacci Numbers (combinatorics, guards, code duplication)
- Binomial Coefficients (combinatorics, efficiency)
Programming with Lists: Dale-Chall Readability
- Parsing (the joy of types, lists, lists of lists)
- Scoring (simple list algorithms)
- Experiments (simple IO, to see things running)
Algorithms on Lists: Needleman-Wunsch Sequence Alignment
- Naive Algorithm (types and problem description)
- Efficient Algorithm (basic data organisation)
- Experiments (just to see it run on real-world data)
Basic Data Types: Propositional Satisfiability
- Data Type (inductive types, functions on inductive types)
- Satisfiability (algorithmics on inductive types)
- Exponential Behaviour (experiments on complexity)
Higher-Order Functions
- Map on Lists (standard examples)
- Right Folding (summation, maximum, removal of duplicates)
- Left Folding (summation, digits-to-number, list reversal)
- Filter (prime numbers, some lazy evaluation)
Complexity
- Exponentiation (problem symmetries)
- List Reversal (two takes on list reversal)
- Giving Change (dynamic programming)
- Zero Finding (divide and conquer)
Noughts and Crosses (Minmax Algorithm)
- The Game (intro and logic)
- Evaluating Moves (anticipating the best move of the opponent)
- Choosing the best Move (minmax at work)
- Speeding up (parallelism)
Simple Parallelism in Haskell
- Parallel Quicksort (experiments and stats)
- Tree Algorithms (experiments and stats)