Programming
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90 articles
- Programming4 min
How to Add Tests to Legacy Code: Characterization Tests and Seams
First lock in current behaviour with characterization or snapshot tests, then use seams to cut off the database, network and clock, and only then change code in small verified steps.
Advanced - Programming4 min
Big O Notation Explained: Time and Space Complexity
Big O describes how the running time or memory of code grows as the input size n grows, ignoring constants, so you can tell in advance whether a function will stay fast on large data.
Basics - Programming4 min
Binary Search: How It Works and How to Implement It
Binary search finds an element in sorted data in O(log n) by discarding half the range at each step; the key is to define your bounds and loop condition precisely to avoid off-by-one errors.
Practice - Programming4 min
Trees and Binary Search Trees: A Practical Guide
A binary search tree keeps smaller keys to the left of each node and larger keys to the right, giving O(log n) lookups, but only while the tree stays balanced.
Practice - Programming3 min
Clean Code: Rules for Naming Variables and Writing Functions
Clean code reads like prose: names say what is stored and what is done, functions are short and do one thing, arguments are few and early returns remove nesting. Comments explain why, not what.
Practice - Programming3 min
Code Review Checklist: What to Check in a Pull Request
A good review checks in order whether the code solves the task, is understandable, is tested, has no security holes or bottlenecks — and comments target the code, not the person.
Practice - Programming3 min
Code Smells and How to Refactor Them
A code smell is a sign that structure is getting in the way of change; you fix it with small refactoring steps, each one protected by tests.
Practice - Programming4 min
Singleton, Factory, Strategy, Observer: Patterns in Practice
Strategy swaps algorithms, Factory picks the right implementation, Observer broadcasts events to subscribers and Singleton guarantees one instance. Each helps only for a specific problem, and Singleton is often better replaced with dependency injection.
Practice - Programming4 min
Compiled vs Interpreted Languages: How Code Runs
A compiler translates code into machine instructions before it runs, an interpreter executes it as it goes, and most modern languages mix both via bytecode and JIT — so the specific implementation matters more than the label.
Basics - Programming4 min
Composition vs Inheritance: When to Use Which
Prefer composition by default: build objects from small, replaceable parts. Use inheritance only for a true, stable "is-a" relationship with a shallow hierarchy.
Advanced - Programming4 min
Concurrency vs Parallelism: What's the Difference
Concurrency is handling several tasks at once by switching between them; parallelism is literally running several tasks at the same moment on different CPU cores.
Basics - Programming4 min
How to Write Good Commit Messages: Conventional Commits
A good commit says what changed and why in one short line; Conventional Commits adds a type like feat or fix, and tools use those types to compute the next version and write the changelog.
Practice - Programming4 min
Dates and Time Zones in Code: UTC, ISO 8601 and Common Bugs
Store instants in UTC, exchange them as ISO 8601 strings with an offset, and convert to local time only when displaying to a user, using an IANA zone such as Asia/Tashkent.
Practice - Programming4 min
How to Debug Code: A Systematic Step-by-Step Approach
Debugging is not guessing but a loop: reproduce the bug reliably, narrow down where it happens, form one hypothesis, test it against facts, then lock in the fix with a test.
Practice - Programming3 min
Dependency Injection Explained: Why and How to Use It
Dependency injection means a class does not create its dependencies itself but receives them from outside, usually through the constructor. This makes code easier to test and change, and a DI container simply automates assembling objects.
Advanced - Programming3 min
DRY, KISS and YAGNI: Programming Principles Explained
DRY means one piece of knowledge in one place, KISS means the simplest working solution, YAGNI means not building what you do not need yet; apply them together, not alone.
Basics - Programming4 min
Dynamic Programming: How to Recognize and Solve DP Problems
Dynamic programming applies when a problem splits into overlapping subproblems with optimal substructure; you solve it by defining state, transition and base case, and storing subproblem answers instead of recomputing them.
Advanced - Programming3 min
Error Handling Best Practices: Exceptions vs Return Values
Exceptions are convenient when an error must travel far up the stack, while error values and Result make every failure explicit in the signature. More important than the approach: never lose errors, add context and handle them where a decision can be made.
Practice - Programming4 min
Data Structures Every Developer Should Know
Pick a data structure by its main operation: index access means an array, key lookup a hash map, order and ranges a tree, "most urgent item" a heap, and relationships between objects a graph.
Basics - Programming4 min
Why 0.1 + 0.2 ≠ 0.3: Floating Point and Money in Code
Floats store numbers approximately in binary, so money should be kept as integers in minor units (cents, tiyin) or in decimal types such as Decimal and NUMERIC.
Practice - Programming4 min
Git Branching Strategies: Git Flow, GitHub Flow, Trunk-Based
Git Flow fits infrequent versioned releases, GitHub Flow fits web products deployed often via short branches, and trunk-based suits teams with strong automation and feature flags.
Practice - Programming4 min
Essential Git Commands: A Cheat Sheet for Daily Work
Daily Git work needs only about twenty commands, such as clone, status, add, commit, switch, merge, pull, push, log and diff, plus a well-configured .gitignore file.
Practice - Programming4 min
Git Hooks: Automating Checks with pre-commit and Husky
Git hooks are scripts Git runs before a commit or push; the pre-commit framework (Python) and Husky with lint-staged (JS) share them across the team and check only the changed files.
Advanced - Programming4 min
Advanced Git: Interactive Rebase, Cherry-Pick and Bisect
Interactive rebase rewrites your local commits (squash, reword, reorder), cherry-pick copies a single commit to another branch, and bisect uses binary search to find the commit that broke the code.
Advanced - Programming4 min
Git Merge vs Rebase: Differences and When to Use Each
Merge keeps history as it happened and adds a merge commit, while rebase rewrites commits into a straight line. Rebase only your own local branches and merge shared ones.
Practice - Programming4 min
Git Stash: How to Save Unfinished Work Without Committing
git stash temporarily moves uncommitted changes onto a separate stack and resets your working copy to the last commit; bring them back with git stash pop or apply, and use a WIP branch for work that will wait for days.
Practice - Programming3 min
Git vs GitHub vs GitLab: What's the Difference
Git is a program that records the history of your code on your machine; GitHub, GitLab and Bitbucket are online services that host Git repositories and build team collaboration around them.
Basics - Programming4 min
.gitignore Guide: What to Ignore and How Patterns Work
.gitignore tells Git which untracked files to keep out of the repository, such as dependencies, builds, local settings and secrets; it does not affect files already committed — those must be removed with git rm --cached.
Practice - Programming3 min
Goroutines and Channels in Go: Concurrency Guide
A goroutine is a lightweight function started with go, a channel is a safe way to pass it data, and WaitGroup plus context control shutdown so goroutines do not leak.
Practice - Programming4 min
Graph Traversal: BFS vs DFS with Code Examples
BFS explores a graph layer by layer with a queue and finds shortest paths in unweighted graphs; DFS goes deep with a stack or recursion and suits cycle detection and topological sorting.
Practice - Programming5 min
Greedy Algorithms: How They Work and When They Fail
A greedy algorithm builds a solution by taking the locally best option at every step and never reconsidering it; it is correct only when the problem has the greedy choice property and optimal substructure, otherwise you need dynamic programming.
Basics - Programming4 min
How Garbage Collection Works in Java, Go and JavaScript
A garbage collector frees objects the program can no longer reach through references; leaks happen when an unneeded object is still reachable, for example from a cache or a subscription.
Advanced - Programming4 min
How Hash Tables Work: Hashing, Collisions and Lookups
A hash table turns a key into an array slot using a hash function, so lookup, insertion and deletion take constant time on average, while collisions are handled by chaining or open addressing.
Basics - Programming3 min
How to Choose a Programming Language for Your Project
Pick a language by five criteria, not by trends: project type, performance needs, ecosystem maturity, availability of developers and the cost of maintaining it for years.
Basics - Programming4 min
How to Read a Stack Trace and Find the Bug
A stack trace is the chain of calls that led to a crash: find the error type and message, then the first frame from your own code — that is almost always where the fix goes.
Practice - Programming3 min
Is PHP Still Worth Using? Modern PHP Explained
Yes, PHP is still relevant: versions 8+ added strict types, enums, attributes and JIT, a large share of the web runs on PHP, and Laravel and Symfony make solid web products fast; pick another language for real-time, ML or heavy computation.
Basics - Programming3 min
Java vs Kotlin: Key Differences and Which to Choose
Kotlin is the standard for new Android projects; on the backend both run on the JVM and interoperate fully, so the choice depends on your team, existing codebase and preferred frameworks.
Basics - Programming3 min
What Are Closures in JavaScript? Explained with Examples
A closure is a function that remembers the variables from where it was created and keeps access to them even after the outer function has finished running.
Basics - Programming3 min
How the JavaScript Event Loop Works: Tasks and Microtasks
JavaScript runs on one thread: first synchronous code, then every microtask (promises, await), and only then the next task (setTimeout, events).
Advanced - Programming3 min
JavaScript Promises and async/await: A Practical Guide
A promise is an object holding a future result and async/await is cleaner syntax on top of it; run independent requests in parallel with Promise.all and catch errors with try/catch.
Practice - Programming4 min
var vs let vs const in JavaScript: Scope and Hoisting
Use const by default and let when the variable must be reassigned; avoid var, because it is function-scoped and hoisted with undefined, which causes subtle bugs.
Basics - Programming3 min
Kotlin Coroutines: A Practical Introduction
Kotlin coroutines let you write async code sequentially: suspend functions do not block threads, launch and async start work inside a scope, and cancellation flows down the hierarchy.
Practice - Programming4 min
Linked List vs Array: Differences and When to Use Each
An array stores elements side by side, so index access is O(1) and iteration is cache-friendly; a linked list stores scattered nodes joined by pointers, so it only wins when you insert or remove at a node you already hold.
Basics - Programming5 min
Luhn Algorithm: Validating Uzcard, Humo and Visa Card Numbers
The Luhn algorithm is a simple checksum that catches most typos in a card number before the form is submitted; it cannot tell whether a card exists — only the payment provider can.
Practice - Programming4 min
Higher-Order Functions: map, filter and reduce Explained
A higher-order function takes or returns another function; map transforms each element, filter keeps the ones that pass a test, and reduce folds a collection into one value.
Basics - Programming3 min
Mocks, Stubs and Fakes: How to Isolate Code in Tests
A test double stands in for a real dependency: a stub returns canned data, a mock verifies calls, a fake is a simplified working implementation. Replace only what is slow or external.
Practice - Programming4 min
Pass by Value vs Pass by Reference: How Arguments Work
Most popular languages pass a copy of the value, and for objects that value is a reference, so a function can mutate a shared object but cannot rebind the caller's variable; true pass by reference exists only where the language says so explicitly, like ref in C# or pointers in Go.
Basics - Programming3 min
PHP Composer and PSR Standards: Setting Up a Modern Project
A modern PHP project starts with composer.json: Composer installs dependencies and provides PSR-4 autoloading, while PHP-CS-Fixer and PHPStan enforce PSR-12 style and catch bugs before runtime.
Practice - Programming3 min
Property-Based Testing: Hypothesis and fast-check in Practice
Instead of a few examples you describe a property that holds for any input, and Hypothesis or fast-check generate hundreds of cases and shrink any failure down to a minimal example.
Advanced - Programming4 min
Pure Functions and Immutability: Writing Predictable Code
A pure function returns the same result for the same input and changes nothing outside itself. Combine pure functions with data you never mutate, push side effects to the edges, and most "it changed somewhere" bugs disappear.
Practice - Programming4 min
Testing in Python with pytest: Fixtures, Parametrize and Mocks
pytest tests are plain test_* functions with ordinary assert; fixtures prepare data and resources, parametrize runs one test over many inputs, and mocks replace the network and external services.
Practice - Programming3 min
Python asyncio Explained: async, await and the Event Loop
asyncio lets one thread handle many I/O operations while they wait for the network or disk; it does not speed up CPU-bound work — use processes for that.
Advanced - Programming3 min
Python Decorators: How They Work and How to Write Your Own
A decorator is a function that takes a function and returns a new one with extra behavior before or after the call; the @decorator syntax is just shorthand for func = decorator(func).
Practice - Programming4 min
Python Generators and yield: Processing Large Data Efficiently
A generator hands out values one at a time via yield instead of holding the whole collection in memory, so you can process a file of any size line by line with almost constant memory use.
Practice - Programming3 min
Python Type Hints: A Practical Guide with mypy
Type hints do not change how Python runs, but they let mypy catch bugs before execution; start with new and critical modules and tighten checks step by step.
Practice - Programming3 min
Python Virtual Environments: venv, pip and Poetry Guide
A virtual environment is an isolated folder with Python and the packages of one project; create it with venv or Poetry and pin dependency versions in a file.
Practice - Programming3 min
Python vs JavaScript: Which Language to Learn First
If you want to build websites and interfaces, start with JavaScript; if you care about automation, data, AI or bots, start with Python. Both suit beginners — your goal decides, not which one is "better".
Basics - Programming4 min
Race Conditions and Deadlocks: Causes and How to Prevent Them
A race condition happens when threads change shared data without synchronization; a deadlock happens when threads wait on each other's resources in a cycle. Fix them with synchronization, a consistent lock order and less shared mutable state.
Advanced - Programming4 min
Recursion Explained: Base Cases, Call Stack and Examples
Recursion is a function solving a problem by calling itself on a smaller subproblem; it needs a base case where the calls stop, otherwise the call stack overflows.
Basics - Programming4 min
Regular Expressions for Beginners: Syntax Cheat Sheet
A regular expression is a text-matching pattern built from character classes, quantifiers, anchors and groups; learn those four building blocks and you can read most regexes.
Basics - Programming3 min
Advanced Regex: Lookahead, Lookbehind and Named Groups
Lookarounds check context without consuming it, named groups make matches readable, and nested quantifiers like (a+)+ are the main source of catastrophic backtracking and ReDoS.
Advanced - Programming4 min
Regex Examples: Validating Phones, Emails and URLs
Regex checks format, not existence: normalize a phone to digits and match a pattern, check email with a simple pattern plus a confirmation message, and validate URLs with a built-in parser.
Practice - Programming4 min
How to Resolve Merge Conflicts in Git
A conflict happens when two branches change the same lines differently; you pick the final version, remove the markers, run git add and finish the merge.
Practice - Programming4 min
Rust Ownership and Borrowing Explained
Every Rust value has one owner; it can be moved or borrowed — many times for reading or once for writing — and a reference can never outlive the value itself.
Advanced - Programming3 min
Semantic Versioning (SemVer) Explained
SemVer is the MAJOR.MINOR.PATCH format, where MAJOR grows on incompatible changes, MINOR on backward-compatible features and PATCH on bug fixes; a lock file pins the exact dependency versions.
Basics - Programming4 min
SOLID Principles Explained with Practical Examples
SOLID is five rules for keeping code easy to change: one reason to change per class, extension without editing, safe substitution, small interfaces and dependence on abstractions instead of concrete classes.
Practice - Programming4 min
Sorting Algorithms Compared: Bubble, Merge, Quick and More
Simple sorts (bubble, insertion) run in O(n²) and suit tiny arrays, while merge, quick and heap sort run in O(n log n); in real code your language's built-in sort is almost always the right choice.
Basics - Programming4 min
Stack and Queue Data Structures Explained with Examples
A stack returns the most recently added element first (LIFO), a queue returns the oldest one first (FIFO); both are simple wrappers that restrict where you add and remove items.
Basics - Programming4 min
Stack vs Heap Memory: What Every Developer Should Know
The stack is fast memory for a function's local data that is freed automatically when the function returns; the heap is flexible memory for data with any lifetime, but allocating there costs more.
Basics - Programming3 min
Static vs Dynamic Typing: Pros, Cons and Examples
Static typing checks types before the program runs, dynamic typing checks them at runtime; strong versus weak is a separate question about implicit conversions, and gradual typing (TypeScript, Python type hints) lets you combine the best of both.
Basics - Programming4 min
Swift Language Basics: Syntax, Optionals and Structs
Start Swift with five things: let/var, optionals with safe unwrapping, the difference between struct (value) and class (reference), enums and closures — almost all iOS code is built on them.
Basics - Programming4 min
Test-Driven Development (TDD): A Step-by-Step Guide
TDD is a short loop: write a failing test first, then the minimum code to make it pass, then improve the code while the tests keep you safe.
Practice - Programming4 min
Two Pointers and Sliding Window: Patterns for Array Problems
Two pointers and sliding window replace nested loops with a single pass: each pointer only moves forward, so every element is handled a constant number of times and complexity drops from O(n²) to O(n).
Practice - Programming4 min
TypeScript Generics: How to Write Reusable Typed Code
A generic is a type parameter that lets one function or type work with different data while keeping precise types, without falling back to any.
Practice - Programming4 min
TypeScript type vs interface: When to Use Each
For object shapes, type and interface are almost interchangeable. Use interface when extends and declaration merging matter, and type for unions, tuples and computed types. Most importantly, agree on one team rule.
Practice - Programming4 min
How to Undo Changes in Git: reset, revert, restore
restore undoes edits in files, reset moves a branch back in local history, revert adds a new undo commit for code already shared, and reflog brings back what seems lost.
Practice - Programming3 min
Unicode and UTF-8 Explained: Fixing Encoding Problems
Unicode gives every character a number, and UTF-8 turns that number into 1 to 4 bytes. Garbled text appears when bytes are written in one encoding and read in another, so specify UTF-8 explicitly everywhere.
Practice - Programming4 min
Unit vs Integration vs E2E Tests: What's the Difference
A unit test checks one function in isolation, an integration test checks parts working together, and an E2E test runs a full user journey; pick the mix based on where your project actually breaks.
Basics - Programming5 min
Uzbek Latin–Cyrillic Transliteration in Code: Rules and Pitfalls
Uzbek Latin converts reliably to Cyrillic with a lookup table that checks two-character combinations first, once all apostrophes are normalized to one character; the reverse direction loses information (ц, ъ after ў), so store a normalized key for search.
Practice - Programming3 min
What Are Design Patterns and Why They Matter
A design pattern is a proven way to solve a recurring code design problem, not a ready-made library. It gives a team a shared vocabulary but hurts when used without a real problem.
Basics - Programming4 min
What Is a Linter? ESLint, Ruff and Static Analysis Basics
A linter reads code without running it and flags likely bugs and risky patterns, a formatter only rewrites layout, and a type checker verifies types; set up all three with minimal configs and run them in the editor, before commit and in CI.
Basics - Programming4 min
What Is Code Coverage and How Much Do You Really Need
Code coverage shows which parts of the code ran during tests, not whether they were checked; use it to find untested areas, require coverage on new code in CI, and set a moderate floor instead of chasing 100%.
Basics - Programming3 min
What Is C# and .NET: Overview for Beginners
C# is a programming language and .NET is the platform that compiles and runs C# code; today it runs on Windows, Linux and macOS and is used for web, desktop, games and enterprise systems.
Basics - Programming4 min
What Is Functional Programming? Core Ideas for Beginners
Functional programming builds programs from small functions that take data and return new data, passing functions around like values. You describe what to compute, not how to loop step by step.
Basics - Programming4 min
What Is Git and How Version Control Works
Git is a version control system that records your code history as snapshots called commits, lets you work in branches and safely combines the work of several people.
Basics - Programming3 min
What Is Go (Golang) and Where It Shines
Go is a compiled language with minimal syntax, fast builds and built-in goroutines; it excels at APIs, CLI tools and cloud infrastructure but is weaker for GUIs, data science and complex domain modeling.
Basics - Programming4 min
What Is OOP? The Four Principles with Code Examples
OOP builds a program from objects that bundle data and behavior; its four principles (encapsulation, inheritance, polymorphism, abstraction) help you hide details and swap one implementation for another.
Basics - Programming3 min
What Is Python and What Is It Used For
Python is a general-purpose language with simple, readable syntax used for backends, automation scripts, data analysis, AI and bots, but it is slower than compiled languages and rarely used for mobile apps.
Basics - Programming3 min
What Is Rust and Why Developers Love It
Rust is a compiled language that checks memory safety at compile time without a garbage collector; it delivers C/C++-level speed and excellent tooling but takes real time to learn.
Basics - Programming3 min
What Is TypeScript and Why Teams Switch to It
TypeScript is JavaScript with types: your editor and compiler catch bugs before the code runs, and the output is plain JavaScript. Teams switch for reliability and safe refactoring, usually migrating step by step.
Basics
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