This episode explores building a minimal reactive framework using signals as a reactivity primitive. We'll look into implementing a simple component model, composing components, separating the view into static and dynamic parts, and implementing fine-grained reactivity.
In this episode, we'll explore a concept called Signal that has been getting a lot of traction in JavaScript over the past few years. I'll describe a simple implementation so you can understand the internals and then see how it relates to the traditional object-oriented design pattern observer.
Today in less than 20 minutes, we'll explore what maps are and how they work under the hood. We'll talk about the differences between treemaps, hash maps, and hash tables. We'll dig pretty in-depth...By the end of the episode, you'll understand how to implement hash tables using an array, hash function, and a linked list!
Today we'll look into static and dynamic systems. We'll discuss what does it mean for a programming language or a framework to be static or dynamic. In the second part of the podcast, we'll focus on some of the properties of static systems and how they can help in better compile-time optimizations, development experience, and more!
In this episode, we'll look at the very basics of type systems and their enforcement. We'll discuss strongly and weakly typed languages. After that, we'll dig into different enforcement strategies - runtime with dynamic typing and compile-time with static typing.
In this episode, we'll look at what data structures and algorithms JavaScript bundlers use. We'll talk about ECMAScript modules, strongly connected components, depth-first search, and more! Enjoy!
Today we'll talk about using dependency injection across paradigms! You'll understand what this pattern is all about and how to use it. During the episode, we'll touch on topics such as inversion of control, high-order functions, and testability.
Today we'll learn about memoization! Memoization is a practice that helps us improve the performance of our apps using caching. In the episode, we'll also discuss pure functions, caching strategies, and much more!
In this episode of the programming podcast, we'll discuss static analysis and code transformation. In particular, we'll look at the difference between compilers, linters, and formatters. By the end of the episode, you'll understand what tool you should use to improve your development experience and team processes.
In today's episode, you'll learn the four principles of object-oriented programming. We'll discuss abstraction, inheritance, encapsulation, and polymorphism. By the end of the show, you'll understand each one of them; you'll know how they relate to each other, and how to use them in practice.
Today we're going to discuss the binary heap data structure. In this episode, you'll learn where to use heaps in practice, how they can come handy to you during a coding interview, and how to implement them! Along the way, we'll cover heap sort, priority queues, load balancing, and more!
Instead of digging into algorithms and data structures, today, you'll learn about epidemic modeling. In 9 minutes in this episode, you'll get a mathematical intuition on the spread of COVID-19 and the essential variables we can control, which can help us fight the virus.
Today you'll learn how keeping your abstractions more cohesive and less coupled can improve the quality and maintainability of your software.
The chances are that the information from this episode will come in handy to you during a coding interview and likely in real life! In this episode, you'll learn the topological sort algorithm. Along the way, you'll understand what's a dependency graph and how topological sort operates on this data structure. We'll also discuss a few real-life examples where I had to implement topological sort myself!
Have you ever been frustrated during interviews thinking that your interviewer expects you to have memorized a bunch of sorting algorithms you'd never need in real life? In this episode of the podcast learn how to approach such situations. In performance critical systems you may have to implement an efficient sorting yourself. Learn how to beat the built-in algorithm in a few lines of code!
Today you'll learn how at runtime, you can enhance the behavior or existing objects using the decorator pattern. In this episode, we'll discuss the advantages of decorators over inheritance and look at two examples from real-life - implementing a network communication protocol and enriching user interface components.
In the episode today, we'll talk about the trie data structure. You'll learn what tries are, how you can use them in practice, and how to implement them in your favorite programming language!
In this episode, we'll discuss graphs. You'll learn how this data structure looks like and what are its applications. Later on, we'll talk about algorithms for traversing graphs. You'll understand how breadth-first search and depth-first search work and when you should use one instead of the other. Topics we'll also touch on are chromatic graphs and finding the shortest path.
In this episode, we'll discuss two fundamental data structures in computer science - arrays and linked lists. Their understanding is essential not only in your day to day job but also for performing well on your next coding interview. We'll discuss implementation details for both data structures, and we'll talk about when it's better to choose one instead of the other. Along the way, we'll touch on memory hierarchy, caching locality, and different interview problems.
Today we're going to talk about quickselect. This algorithm helps us quickly find the n-th smallest element in unsorted arrays. It'll not only help you improve the performance of your applications, but it's also a very common white-board interview problem.