01
Arrays
Learn traversal, indexing, searching and manipulation.
ACCESS → TRAVERSE → OPTIMIZE
DSA is not about memorizing hundreds of solutions. It is about learning how to recognise patterns, understand constraints, build logic and translate your thinking into code.
Every beginner sees a new DSA question as a completely new challenge.
Strong programmers see the structure behind the question.
For example, two completely different questions may both use Sliding Window because both involve a contiguous range.
Your first task is not writing code. Your first task is understanding:
What information do I have? What am I trying to find? What work is repeating?
Learn traversal, indexing, searching and manipulation.
ACCESS → TRAVERSE → OPTIMIZE
Understand sequences, characters, substrings and frequency.
SCAN → MATCH → TRANSFORM
Store information to avoid repeated searching.
STORE → LOOKUP → DECIDE
Learn references, pointers and node movement.
CURRENT → NEXT → UPDATE
Learn ordering and controlled access to data.
LIFO / FIFO
Learn traversal, connections and exploration.
NODE → EDGE → PATH
Use arrays when order and indexed access matter.
Ask whether you need to traverse once, search for a pair, maintain a range or repeatedly access positions.
Hash maps help you remember information.
If you are repeatedly searching through the same data, ask whether storing previous information gives faster lookup.
Use a stack when recent unresolved information matters.
Something opened and must close later? Something needs to be processed in reverse?
Graphs represent relationships and connections.
Whenever objects connect to other objects, imagine nodes and edges.
Move two positions strategically instead of checking every possible combination.
Move · Evaluate · Eliminate · Terminate
Maintain a moving range instead of recalculating every possible subarray.
Grow · Review · Optimize · Withdraw
Eliminate half the search space whenever a decision tells you where the answer can be.
Hypothesis · Assess · Left/Right · Finish
Reduce the problem into smaller versions of the same problem.
Break · Ask Smaller · Stop · Expand
Save answers when smaller problems repeat.
Split · Analyze · Verify · Eliminate repetition
Explain the problem in your own language. If you cannot explain it simply, you are not ready to solve it.
Create a small example with only a few values. Move through it manually.
Build the simplest correct approach. Do not optimize before understanding.
Identify repeated work, unnecessary loops or expensive searching.
Match the structure of the problem with a known algorithmic pattern.
Code should be the translation of your logic, not the place where you discover the logic.
Learn the structure. Recognise the pattern. Build the logic. Then write the code.
EXPLORE MY PROJECTS →