project-work

Demonstrating caching algorithms

Why

learning software development life cycle

requirement collections, designing, coding, unit testing

learning how caching algorithm works

learning how to write modular code

Features

eviction policy : algorithm which determines which element is removed incase my capacity of the cache is exceeded.

learnings

• cache and it's internal implementation
• eviction policy and it's application in real life
• how to come up with optimised version from high time complexity code
• how classes are imlpemented and it's importance

DAY 1

DAY 2

• added Base Class CACHE
• added Derived Class MinimumKeyRemovePolicyCache
• added Derived Class MaximumKeyRemovePolicyCache

DAY 3

brute force - LRU Cache TC: O(capacity) Data Structure : VECTOR

DAY 4

example:

DAY 5

optimised code

DAY 6

compiling and running rest cases :)

Challenges⚡️

• making sure current functionality doesn't break while adding new features (solution : testing and different testcases in the following push commands)
• avoiding repeated code (solution : analyse and create a single function for common feature)
• working on time complexity for put function [ O(n) to O(log n) ]