Designing Applications with Functional Programming Constructs
summary
Compares imperative loops to Java Streams and shows the same result can cost eight operations vs 24 naive operations unless streams fuse intermediate ops and use lazy evaluation; warns about garbage from map/filter chains on large datasets (example: three million items called 50 million times). Demonstrates higher‑order functions, lambdas, and purity benefits (referential transparency, memoization) and cites Elm and Redux as practical systems that push impurities to the edges while compiling to JavaScript and working correctly.
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chapters (10)
- 0:00Introduction to functional
- 1:32Understanding imperative
- 5:46Adopting declarative style
- 9:25Higher order functions
- 13:45Using lambda expressions
- 17:49Function composition and
- 25:29Performance and lazy
- 37:25Terminal operations and
- 46:50Immutability for correctness
- 59:15Designing pure systems
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