13 posts tagged with "state machine"

At Stately, the Actor Model is one of our favorite programming paradigms, and we think it’s for good reason! The actor model allows developers to build reliable message-based systems by using actors to communicate. This works extremely well with state machines and statecharts, which can also be modeled as actors and can communicate much in the same ways. Read on to learn what the actor model is, the problems it seeks to solve, and how you can use it in your projects to communicate reliably across different entities.

Are you a React developer using XState to model your application logic? Perhaps you’ve heard of XState but have been looking for an easy way to try it out in one of your projects. If so, then I’d like to share with you a pattern I was introduced to when first diving into codebase at Stately, that of using custom machine hooks. This lightweight, reusable way to integrate XState into React components is a delight to work with and I think you might like it as much as I do!

Last week we asked our community, “What are the biggest benefits you’ve had from using state machines?”

At Stately, we’re obviously fans of state machines. Still, we wanted to ask our community the benefits they’ve experienced, whether they were working on a specific project or incorporating state machines into their everyday workflow.

Statecharts are a visual language used to describe the states in a process.

You may have used similar diagrams in the past to design user flows, plan databases or map app architecture. Statecharts are another way of using boxes and arrows to represent flows, but with XState these flows are also executable code that can be used to control the logic in your applications.

XState offers several primitives for representing long-running application processes. These are usually expressed as services. I’ve written a bit about services here - but today I wanted to talk about my favourite way of expressing services: the Invoked Callback.

XState offers several ways of orchestrating side effects. Since it’s a statechart tool, with significantly more power than a reducer, side effects are treated as a first-class concept.

State machines offer several API’s for expressing state. Like other tools, you can keep arbitrary values in a store (usually expressed as an object) called context.

XState offers two options for declaring machine definitions:

import { Machine } from "xstate";

const machine = Machine({ ...config });

…or…

import { createMachine } from "xstate";

const machine = createMachine({ ...config });

This can be confusing for beginners. Why are there two very similar-looking methods? What’s the difference?

The finite state machine is one of the oldest models of computation in computer science. It’s older than the web, older than any programming language you can think of, and probably older than you. Just ask Mealy (1955) or Moore (1956). Finite state machines (FSMs) can be implemented in any modern language using control-flow statements, yet there’s most likely a state machine library (if not many) in all of those languages.

XState can feel overwhelming. Once you’ve gone through Kyle or David’s courses and read through the docs, you’ll get a thorough understanding of the API. You’ll see that XState is the most powerful tool available for managing complex state.

The challenge comes when integrating XState with React. Where should state machines live in my React tree? How should I manage parent and child machines?

Redux is fantastic.

Some of you might disagree, so let me tell you why.

Over the last few years, Redux has popularized the idea of using message-passing (also known as event-driven programming) to manage application state. Instead of making arbitrary method calls to various class instances or mutating data structures, we now can think of state as being in a "predictable container" that only changes as a reaction to these "events".

XState version 4.7 has just been released. This is a minor version bump, but a major reworking of the internal algorithms, a lot of new capabilities, bug fixes, and a better TypeScript experience. It also paves the road for even more utilities, like @xstate/test and @xstate/react, as well as compatibility with other 3rd-party tools across the ecosystem, and even across languages.

I’m going to start this post with an excerpt from the book “Constructing the User Interface with Statecharts”, written by Ian Horrocks in 1999:

User interface development tools are very powerful. They can be used to construct large and complex user interfaces, with only a relatively small amount of code written by an application developer. And yet, despite the power of such tools and the relatively small amount of code that is written, user interface software often has the following characteristics:

• the code can be difficult to understand and review thoroughly:
• the code can be difficult to test in a systematic and thorough way;
• the code can contain bugs even after extensive testing and bug fixing;
• the code can be difficult to enhance without introducing unwanted side-effects;
• the quality of the code tends to deteriorate as enhancements are made to it.

Despite the obvious problems associated with user interface development, little effort has been made to improve the situation. Any practitioner who has worked on large user interface projects will be familiar with many of the above characteristics, which are symptomatic of the way in which the software is constructed.