Functional Programming: Technical Reasons to Adapt
summary
Argues that immutability + pure functions make code easier to reason about, safer for concurrency, and enable optimizations like lazy evaluation, memoization and parallelism; demonstrates Scala treats parameters as final and warns against Java mutability tricks, shows persistent trie copies 100,000 elements in ~33 ms (shared structure avoids full copies), reproduces Haskell’s automatic memoization, and uses Java Streams with lazy infinite sequences to find the first prime >100 whose sqrt>20 (Java streams findFirst returns 401).
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chapters (13)
- 0:00Why functional programming?
- 4:36Dangers of mutable state
- 14:47History of the paradigm
- 19:12Structured vs functional
- 24:32Data structure efficiency
- 29:51Higher order functions
- 34:47Pure functions and transparency
- 45:53Memorization techniques
- 53:40Purity in Java lambdas
- 1:00:28Imperative vs declarative
- 1:13:13Building function pipelines
- 1:16:40Lambdas and closures
- 1:21:26Lazy evaluation and streams
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