🚀 The Power of Memoization in Kotlin! 🧠💡

🔍 What's Memoization? It's a technique that saves costly function results, making your code faster by avoiding redundant calculations. Ideal for functions with input-dependent outputs. 📦 Kotlin Memoization : With Kotlin, you can implement memoization yourself using a simple

Map

. Take a closer look at the (Code Snapshot) image. ✨ How It Works : The

Memoize

class stores function results in a

Map

. When the same input is encountered again, it retrieves the cached result instead of recomputation. 👩‍💻 Practical Usage : Let's say you have a function

sumFactors

that calculates the sum of factors for an integer. Memoize it like this:

val sumFactors = { n: Int -> calculateSumOfFactors(n) }
val memoizedSumFactors = sumFactors.memoize()

memoizedSumFactors(10) // Calls calculateSumOfFactors()
memoizedSumFactors(10) // Returns cached result

🌟 Benefits and Considerations: • 🌟 Speed Boost : Memoization makes slow functions lightning-fast. • 🧐 Code Clarity : Say goodbye to redundant calculations, keeping your code clean and maintainable. • 🧠 Easy Implementation : Kotlin's

getOrPut

function simplifies the process, making it accessible even for beginners. • 🙅‍♂️ Single-Parameter Limit : Memoization works best for single-input functions. • -📉 Explicit Memoization : You must apply memoization explicitly to each function. • 💾 Memory Usage : Storing results consumes memory, so consider this as your cache grows. https://lnkd.in/ds5Y_ut4

for more complex memoization, incluing recursive functions, you can check Arrow's support for them, based on Kotlin's RecursiveFunction

Just one thing: this could potentially lead to concurrent issues, so it's nice to point out that this implementation isn't thread-safe. The quickest solution would be to change the

mutableMapOf

to

ConcurrentHashMap

, but that's for JVM only. Anyway I'm pretty sure it wouldn't require much to create a multi-platform solution for this as well. 🙂

Thanks for pointing that out! 😊👍