Three Mindsets of Test Driven Development (TDD)

In this video, Dave Farley explores an effective approach to TDD. Test Driven Development is a Continuous Delivery and DevOps idea that requires us to adopt three distinct mindsets. Most developers new to it don’t get this right. How can we do better at automated testing and software design?



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Three Mindsets of Test Driven Development (TDD)
Alayna  Rippin

Alayna Rippin


Test Driven Development (TDD) with React Testing Library & Mock Service Worker

Let’s step up our testing game with two useful libraries that lend themselves excellently to a TDD approach.

Setting up

Whenever I want to try out something React-related, I use the library create-react-app. It gives you a ready-to-work-with basic React application with no configuration needed. Recent versions also come bundled with React Testing Library, so if you use the latest create-react-app, you can start using React Testing Library straight away. If not — install @testing-library/react and @testing-library/jest-dom in your existing React application.

I am going to implement the following functionality: a simple recipe list with a search function. It will look something like this to a user in a mobile browser:

Image for post

Image credits: Burger Photo by Robin Stickel on Unsplash, French Toast Photo by Joseph Gonzalez on Unsplash, Salmon Photo by Casey Lee on Unsplash

Starting with a failing test

I want to use a TDD approach, so let’s start with a failing test. At this point, there is no component yet, so of course whatever test we write is going to fail. But let’s start small; I want a component named ‘Recipes’ that renders the expected heading text. Here is my test for that expectation:

	import React from 'react';
	import { render, screen } from '@testing-library/react';

	test('renders the heading', () => {
	  render(<Recipes />);

	  expect(screen.getByRole('heading')).toHaveTextContent('Recipe Finder');

React testing library exports a render method, which will render a component and all of its child components. It also exports a screen object, holding a number of queries we can use to select different elements in our rendered component (and its child components too). The **getByRole **query lets me select the heading element and make an assertion on its text content.

Why select the heading element by its role and not for example a CSS class? The guiding principle of React Testing Library is “The more your tests resemble the way your software is used, the more confidence they can give you.” Therefore, we want to write our tests as close as possible to how the ultimate tester — the end user — will be using the application. Users don’t see CSS classes or data attributes; they interact with text, label text and semantic elements and roles. Using queries such as getByRole also encourages us to write accessible code, since these selectors are available to everyone, including users of screen readers.

Making the test pass

Our first test fails as expected.** Recipes is not defined.** But this is the first step in TDD — a failing test. Now, let’s make it pass by writing the simplest possible component with the correct heading and then importing it in our test file. Now, let’s re-run the test. It passes!

	import React from 'react';

	const Recipes = () => {
	  return (
	      <h1>Recipe Finder</h1>

	export default Recipes;

Using further queries, we can make similar expectations for the input element and the “Find” button. The button also has a role, but for the input field, I will use the getByPlaceholderText query, since that is probably the closest query to how the user would find it on the page.

Start with a failing test…

	import React from 'react';
	import { render, screen } from '@testing-library/react';
	import Recipes from './Recipes';

	test('renders the heading, input field and button', () => {
	  render(<Recipes />);

	  expect(screen.getByRole('heading')).toHaveTextContent('Recipe Finder');
	  expect(screen.getByPlaceholderText('Enter an ingredient to find recipes...'))

… and implement the changes necessary to make it pass:

	import React from 'react';

	const Recipes = () => {
	  return (
	      <h1>Recipe Finder</h1>
	          placeholder="Enter an ingredient to find recipes..." 
	        <button type="submit">Find</button>

	export default Recipes;

This way, we know what we expect from our code and more importantly — we will know if we break any functionality if the previously passing tests suddenly fail.

An important step in TDD is the refactor step, where we improve our code to for example make it easier to read, become more efficient and remove any duplication. The test should still pass after we refactor.

Setting up our mocks

When the application first renders, I want to display a list of all my recipes, just like in the visual design above. This requires some kind of communication with an API. We are going to use Mock Service Worker to mock the HTTP-requests, so that we can control the response data. Install Mock Service Worker with npm like this:

npm install msw --save-dev

With Mock Service Worker, we are not mocking a specific module (unlike if we were to use Jest.mock), which means that it makes no difference if I use fetch or a third-party library such as axios to get the data. This makes it incredibly flexible. Let’s add the following imports to our test file:

import { rest } from 'msw';
import { setupServer } from 'msw/node';

Here is how I set up mocking a call to the recipe list endpoint:

	import React from 'react';
	import { render, screen } from '@testing-library/react';
	import Recipes from './Recipes';
	import { rest } from 'msw';
	import { setupServer } from 'msw/node';

	const allRecipes = [
	  { id: 1, title: 'Burger' }, 
	  { id: 2, title: 'French toast' }, 
	  { id: 3, title: 'Salmon' }

	const server = setupServer(
	  rest.get('/api/recipes', (req, res, ctx) => {
	    return res(ctx.json({ recipes: allRecipes }));

	beforeAll(() => server.listen());

afterAll(() => server.close());

If you have worked with NodeJS and Express, the syntax looks very familiar. GET requests to ‘/api/recipes’ will respond with JSON containing the allRecipes array, just like a real API would. These two lines make sure the server starts listening (intercepting) before the tests run and closes its connection when the tests in this file have finished running:

beforeAll(() => server.listen());
afterAll(() => server.close());

#tdd #react-testing-library #react #test-driven-development #testing

Fredy  Larson

Fredy Larson


How long does it take to develop/build an app?

With more of us using smartphones, the popularity of mobile applications has exploded. In the digital era, the number of people looking for products and services online is growing rapidly. Smartphone owners look for mobile applications that give them quick access to companies’ products and services. As a result, mobile apps provide customers with a lot of benefits in just one device.

Likewise, companies use mobile apps to increase customer loyalty and improve their services. Mobile Developers are in high demand as companies use apps not only to create brand awareness but also to gather information. For that reason, mobile apps are used as tools to collect valuable data from customers to help companies improve their offer.

There are many types of mobile applications, each with its own advantages. For example, native apps perform better, while web apps don’t need to be customized for the platform or operating system (OS). Likewise, hybrid apps provide users with comfortable user experience. However, you may be wondering how long it takes to develop an app.

To give you an idea of how long the app development process takes, here’s a short guide.

App Idea & Research


_Average time spent: two to five weeks _

This is the initial stage and a crucial step in setting the project in the right direction. In this stage, you brainstorm ideas and select the best one. Apart from that, you’ll need to do some research to see if your idea is viable. Remember that coming up with an idea is easy; the hard part is to make it a reality.

All your ideas may seem viable, but you still have to run some tests to keep it as real as possible. For that reason, when Web Developers are building a web app, they analyze the available ideas to see which one is the best match for the targeted audience.

Targeting the right audience is crucial when you are developing an app. It saves time when shaping the app in the right direction as you have a clear set of objectives. Likewise, analyzing how the app affects the market is essential. During the research process, App Developers must gather information about potential competitors and threats. This helps the app owners develop strategies to tackle difficulties that come up after the launch.

The research process can take several weeks, but it determines how successful your app can be. For that reason, you must take your time to know all the weaknesses and strengths of the competitors, possible app strategies, and targeted audience.

The outcomes of this stage are app prototypes and the minimum feasible product.

#android app #frontend #ios app #minimum viable product (mvp) #mobile app development #web development #android app development #app development #app development for ios and android #app development process #ios and android app development #ios app development #stages in app development

My Experience with Test-Driven Development (TDD)

Anyone who has worked on an I.T. project will know this familiar scenario: a project with a tight timeline has a bug that needs fixing before deployment. Once the code has been written, manual testing is performed before the code review is done, and the code is merged to the source control. You then run the risk that more bugs and issues may have been introduced from the code merge; meaning that you’ll either need to write more tasks to resolve this issue or the new code changes will need to be reverted in source control.

A lot of things could lead to problematic code. The following are a few main reasons for this:

  • Lack of test cases written for the application
  • The tests were written after writing the functional code
  • Failing to regression test

So how might be avoid this scenario? I suggest using Test-Driven Development (TDD).

What is TDD

TDD is an approach to development that emphasizes testing code before the code is written.

In the first step, the developer writes the test. Then, the test is run to see if it fails. This state is called “Red” because in most of the frameworks when a test is failed it is highlighted in the color red. The reason for running the test before writing the code is to make sure it fails the way the developer expects it to. If, for any reason, if a test passes at this moment it means that there is something wrong with the test itself.

After that, the developer writes the minimal code to see if the test passes. This state is called “Green”. Finally, the code and the tests are refactored to make them clean, simple, and readable. This state is called “refactor” which makes the code ready for the next iteration of writing the test, then writing the functional code, and refactoring again. This is called the “Red-Green-Refactor” approach of TDD.

My experience using TDD

When I first started using TDD, it was not easy as it seemed. It took some time and practice to understand how to write the tests before writing the code. After some time practicing TDD, I saw the magic; I started to write the code faster and was able to spend more time in the planning phase rather than spending time fixing bugs later on.

Initially, while code reviewing, I realized the code quality had gone down and more effort was required in the code review phase. Over time, as the team became better aquainted with TDD, the code quality got even better than what it was before implementing TDD. This is because the team started to write the code in smaller testable chunks, which made unit testing as well as integration testing easier and debugging faster.

As TDD requires developers to write extra code, it made some of the developers in our team hesitant at the start. To overcome their hesitance, we chose smaller tasks to acquire the skill and implement it. Developers learned the process at their own pace, we gave them the time and assistance they required to master this framework, and ultimately as the team matured, development, debugging, and refactoring time reduced considerably.

Value added by TDD for me

Test-Driven Development allowed me to write higher quality code. By “higher quality” code, I mean that the code is reliable, maintainable, loosely-coupled, has high cohesion, is easily testable, modular, reusable, and has good separation of concerns.

Now I am able to spend more time focusing on the functionality details before implementing it. With TDD, I can plan on how to go about writing functional code in the early stages of software development. The bug count has also been reduced considerably as I am able to identify any missing functionality in the early stages of development.

#coding #test-driven-development #tdd #testing #programming

Phát triển hướng kiểm thử TDD (Test-Driven Development) - P1: Giới thiệu

Phát triển hướng kiểm thử TDD (Test-Driven Development) là một phương pháp tiếp cận cải tiến để phát triển phần mềm trong đó kết hợp phương pháp

#tdd #test #driven #development

Bria  Nolan

Bria Nolan


Database Unit Testing and Test-Driven Database Development

Apache JMeter [for load testing on database] If we want to do accurate testing then you should get first knowledge of database tables, structure. Once we are familiar with the database which we are going to test, then we can test the database more accurately and in more detail. Testing Database as a Manual Tester For automation database testing we will need to write a script. Testing Database with respect to Specific Database (For Example – MYSQL ) Testing corresponding to SQL database is performed at the bottom of the database under the Demo portion. So for this, we can refer to Demo section, which is written especially for SQL Database.

Test-Driven Database Development (TDD) is a software development process which includes test-first development. It means that the developer first writes a fully automated test case before writing the production code to fulfill that test and refactoring.This article will give an overview of Test Driven Database Development and Database Unit Testing.

#big data engineering #behavior driven development #test driven development #testing