Problem solving refine karne wale engineers
Algorithmic thinking shuru karein. Dekhein kaise recursion stack banata hai, real-time me sort hotey dekhein aur finally samjhein ki actual server par Big O matters kyu theek hai.
Adjacent pairs compare karo, bade elements har pass mein bubble up hote hain. Production mein kabhi mat lagana — lekin loop invariants aur boundary conditions samajhne ka ye sabse easy entry point hai.
Divide karo, dono halves sort karo, merge karo. Recursion tree ko split aur recombine hote live dekhein. Stable aur guaranteed O(n log n) — koi worst case nahi.
Ek pivot choose karo, uske around partition karo, recurse karo. Average O(n log n) ke saath amazing cache performance — lekin galat pivot choose karo toh O(n²) ka khatara pakka hai.
Max-heap banayein, elements ko order mein extract karein. Quicksort ke unlike guaranteed O(n log n).
Queue use karke graph ko level by level explore karein. Unweighted graphs mein shortest paths dhundhein.
Backtracking se pehle jitna deep ho sake explore karein. Har recursive step ke saath call stack badhte dekhein.
In-order, pre-order, post-order. Ek hi tree par nodes ko different sequences mein visit hote dekhein.
Do numbers dhundhein jo target mein add hote hain. Dekhein ki hash map O(n²) ko O(n) mein kaise badalta hai.
Open aur close brackets match karne ke liye stack use karein. Classic stack application interview question.
Call tree ko exponentially fan out hote dekhein. Samjhein ki memoization kyun zaroori hai.