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The library · 299 pieces

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GuideTechnology

22 min read

Searching and Sorting: Choose the Right Approach

Linear and binary search done right (invariants, boundaries and overflow-safe midpoints), lower and upper bound, searching on the answer, the main sorting algorithms and their trade-offs, and how to sort anything in Java with comparators.

GuideTechnology

21 min read

Heaps and Priority Queues

How a heap keeps the smallest or largest item ready in O(1), how insert and remove work in O(log n), how to use Java's PriorityQueue, and how to solve top-K, k-th largest and merge-k-sorted problems. Includes how a heap differs from a BST.

GuideTechnology

22 min read

Trees and Binary Search Trees

Tree vocabulary, the four traversals (preorder, inorder, postorder, level-order), recursive and iterative code, and binary search trees: search, insert, and the right way to validate one.

GuideTechnology

24 min read

Recursion and Backtracking

Learn to think recursively: base cases, the call stack and recursion trees. Then use backtracking (choose, explore, undo) to generate subsets, permutations and combinations, avoid duplicates, prune the search and solve N-Queens.

GuideTechnology

20 min read

Hashing: HashMap, HashSet, and Frequency Patterns

How hash tables find things almost instantly, what collisions are, how to use HashMap and HashSet in Java, and the patterns that solve duplicates, two-sum, grouping and counting problems. Includes the equals and hashCode contract.

GuideTechnology

19 min read

Stacks and Queues

Last-in-first-out and first-in-first-out, explained with real examples. Learn the right Java collections (ArrayDeque, not Stack), then solve bracket matching, round-robin scheduling and next-greater-element with a monotonic stack.

GuideTechnology

20 min read

Linked Lists: Nodes, Pointers, and Pointer Reasoning

Build singly and doubly linked lists from scratch in Java, learn to reason about pointer changes step by step, and solve reversal, middle-finding, merging and cycle detection with clear diagrams and dry runs.

GuideTechnology

20 min read

Arrays and Array-Based Problem Solving

How arrays work in memory, why indexing is instant but inserting is slow, and how to solve the classic array problems: maximum, frequency counting, in-place rotation, moving zeroes and subarray sums.

GuideTechnology

19 min read

Time and Space Complexity Without the Confusion

Big O explained by counting steps: constant, logarithmic, linear, n log n, quadratic and exponential growth, best, average and worst cases, auxiliary and recursion-stack space, with dry runs you can check yourself.

GuideTechnology

21 min read

Java Essentials for DSA

Only the Java you need for data structures and algorithms: types and overflow, loops, methods, arrays, strings, a small class, input and output, and the mistakes that trip up almost every beginner.

GuideTechnology

15 min read

Start Here: Your Roadmap from Zero to Job-Ready DSA

What data structures and algorithms are, why employers test them, what you can honestly expect from this free 28-article course, and the repeatable six-step loop you will use on every problem.

GuideTechnology

5 min read

Writing Better AI Prompts: A Practical Guide

Most disappointing AI answers come from vague questions. Learn a simple structure for prompts, how to give context and examples, how to iterate, and how to check what comes back.

GuideTechnology

5 min read

How to Use AI for Studying Without Cheating Yourself

AI can be a patient tutor, a quiz master and a writing coach, or a shortcut that leaves you knowing nothing. Here is how to use it to learn faster, with prompts, routines and rules that keep you honest.

GuideTechnology

7 min read

How to Debug Any Bug: A Calm, Repeatable Process

Random changes and hopeful refreshes waste hours. This is a step-by-step debugging process that works in any language: reproduce, narrow down, form a hypothesis, test it, then fix the cause.

GuideTechnology

5 min read

How Do AI Chatbots Like ChatGPT and Claude Actually Work?

AI chatbots feel like magic, but the basic idea is simple: they predict the next piece of text, based on patterns learned from huge amounts of writing. Here is how that works and why they sometimes get things wrong.