In Details About C# Unit Testing In Practice

In Details About C# Unit Testing In Practice

Introduction to C# Unit Test

C Unit test

What do you mean by a Unit test?

In the process of developing software, unit tests basically check that discrete pieces of code, often known as units, function as intended by the author. A unit test is a piece of code created by any programmer to test discrete functionalities of larger programs. A “UNIT” in this sense is the smallest component of the vast code part that makes sense to test, typically a method out of numerous methods of some class. Unit testing is always intended to be basic. The test cases are typically expressed as functions that evaluate and assess whether the result returned after running a unit test is equal to the value you anticipated when you wrote the function. Unit testing’s primary goal is to isolate a single piece of code and ensure that it is dependable and correct.

What Unit Testing Is?

Let’s think about what genuinely qualifies now that that is out of the way. Specific pieces of your code are isolated and tested via unit tests. Okay. I’ll admit that I just punted by defining a term with a word already included in the phrase. But in order to span linguistic barriers, the term’s designers purposefully left the designation unclear.

A unit is similar to a method in C#. So, by creating something that tests a method, you create a unit test, and it isolates testing a single aspect of that approach. You shouldn’t make a program called TestAllTheThings and then call each method in a namespace.

That’s all there is to it, basically. You’ll see that I’ve left off certain items that may have come to mind, including test-driven development (TDD), unit test frameworks, test runners, mocks, or other unit testing tools. Let’s avoid jumping the gun. TDD and mocks are independent topics, so put them off till later. For now, disregard test runners and frameworks. Although we’ll discuss them, a unit test isn’t technically speaking required to have them.

Unit Testing in C#: The Simplest Example

Let’s assume that my sales pitch was successful. At the very least, it convinced you to keep reading. Most instructors would begin by giving you a formal description of unit testing at this point. I won’t employ that strategy because I want to demonstrate to you how simple the notion can be. For the time being, disregard test projects, unit test runners, and everything else that makes you think, “Maybe tomorrow.” Here is the unit testing in the familiar and beloved plain old C#.

Consider the following killer implementation that you created.

public class Calculator
{
public int Add(int x, int y)
{
return x + y;
}
}

How would you put it to the test? If this device operated some sort of GUI, you could open it, enter two numbers, and examine the output. “I entered 15 and 20 and get 35, which appears correct.”

However, it takes a lot of manual labor to do that. Additionally, it doesn’t endure after your manual testing attempt. What if you created an automatic verification program? What if you carried out such an action?

static void Main(string[] args)
{
var calculator = new Calculator();

if (calculator.Add(15, 20) != 35)
throw new InvalidOperationException();
}

This could be done fairly easily. You create a new console project with a reference to your code and place it in the same solution as your Calculator class. You may now execute this code whenever you want by writing it in Main. All appears well if it leaves without incident. If you attempt to execute this and receive an exception, someone has modified the Add() method and broken it in some way.

Unit Testing in C# done in the right way

This idea of automated unit testing is actually quite straightforward. And this demonstrates where the custom originated. The ability to automate code checking became clear to developers. Developers that they were, they quickly began creating several frameworks for this. Now that you know how and why they achieved that, you can understand how unit tests function when they are used in a conventional manner.

Consider the Main code from earlier. What occurs if you want to include more test cases? That method becomes disorderly as you continue to pack more and more code into it.

Even if you separate the checks into their own methods, running them still makes it difficult to figure out what went wrong and why. And how are you going to execute all the elaborate tasks that people perform, such as integrating this into your build?

This could be done fairly easily. You create a new console project with a reference to your code and place it in the same solution as your Calculator class. You may now execute this code whenever you want by writing it in Main. All appears well if it leaves without incident. If you attempt to execute this and receive an exception, someone has modified the Add() method and broken it in some way.

Tutorial on implementing Unit Testing


Let’s stay entirely within Visual Studio to keep things as straightforward as possible. Although you have a Calculator class, you want to put it to the test. And you want to fully test it without including your own custom test-running methodology.

Unit test example

You create a class:

public class Calculator 
{ 
public int Add(int x, int y)
{ 
return x + y;
} 
}

You have a single class, Calculator as seen above. You still need to test it, if only to prove your rightness to others.

To accomplish this, let’s add a new console project and reference the project that contains calculator in the manner shown.

Software unit testing

Now, let’s do the following in the main of the Calculator Tester.

class Program
{
static void Main(string[] args) 
{ 
var calculator = new Calculator(); 
int result = calculator.Add(5, 6); 
if (result != 11) 
throw new InvalidOperationException();
} 
}

Congratulations!  You’ve just written your very own unit test!

Unit testing best practices

Unit Testing Best Practices

Arrange, Act, Assert

Now let’s think about a different kind of unit test anatomy. Here, I’m referring to the logical elements of an effective unit test. They are in their most fundamental form on the test I wrote. Given the title of this section, it may not come as a surprise that those elements are “organize, act, and affirm.”

To grasp the true meaning of this, make extensive use of the scientific method. Think of your test as an experiment and your test run as a hypothesis. With inputs of 4 and 3, we predict that the add method will return 7.

We first set up all of the equipment we will need to conduct this experiment. Very nothing needs to happen in this situation. We only create an object called a calculator. In other, more complicated situations, you might need to execute a specific constructor or seed an object with some variable values.

After the preparation, we take action. In this instance, we use the add method and record the outcome. The unit testing show’s main attraction is represented by the “act.” Everything before it is preparation, and everything after it is reflection.

And finally, we claim. That one was probably disclosed by the Assert class’s invocation. However, you cannot omit a broad category of action and still have a unit test because the assert idea in the unit test represents it. It backs up the hypothesis directly. The essence of testing is asserting something.

One Assert Per Test Method

Veterans of a particular testing methodology who have experience with unit testing may criticize me for this, but so be it. Although not everyone will necessarily concur, I think you should aim for one assert per test method. Each test formulates and states a hypothesis. (The contrary position would contend that several claims can serve to indicate a single hypothesis.)

I won’t go so far as to claim that a test should never have more than one assertion. However, I will note that the test-to-assert ratio in your unit test suite needs to be pretty darn close to 1.

Unit tests Beginners frequently commit the error of using one test method to evaluate everything. After all, it makes sense to do further tests. This motivates them to assert a lot of things in order to maximize their return on investment with each test.

But keep in mind: experiment, hypothesis. Consider examining the test’s output from the test runner. Even if you claim 20 things, there is still only one failure. How will you be able to tell which of your 20 assumptions failed and what went wrong at a glance?

Avoid Test Interdependence

There should be a setup and teardown procedure for each test. The test runner will carry out your instructions in any order it sees fit, and depending on the particular runner you employ (advanced topic), it may even carry out the instructions simultaneously.

As a result, you can’t rely on the test suite or the class you’re evaluating to keep its state consistent across tests. However, it won’t always be evident to you.

For instance, the test runner can choose to run your tests in the same order each time if you have two tests. You could become dependent on this after being given a false sense of security.

A few weeks later, adding a third test disrupts the balance, causing one of your tests to start failing intermittently due to the ordering.

You’ll be frustrated and perplexed by this. At all costs, avoid this reliance.

Keep it short

I’ve been down this road before and experienced the pain. The urge to abstract test setup (also known as “the arrange”) into other classes should be resisted, especially the urge to abstract it into a base class. Although I would argue that base classes are never acceptable in this context, I won’t say that you’ll never find this abstraction appropriate. Instead, look to avoid it.

It makes sense in this case. You want to know what went wrong when a test fails. Therefore, you want a test where all of the setup logic is immediately apparent. You’ll have a big treasure hunt on your hands if your logic is dispersed throughout the class or spread out throughout different classrooms.

Add to the build

The post will be concluded with what is likely the most significant best practice. When your codebase contains only one test, get started on this one right away because you are just beginning your unit testing journey.

Add the execution of your new unit test suite to the build if your team uses a continuous integration process. The build fails if any tests are unsuccessful. No ifs, ands, or buts, and no exclusions. On this one, believe me. If your team’s development isn’t halted by unit test failures, ultimately, as the pressure to deliver increases, your team will begin to ignore the failures. It is a matter of when, not if. Learning unit testing and perfecting it take time. At first, achieving that mastery will seem exceedingly difficult, but if you don’t put everything on the line, you’ll never succeed. Make your writing count if you’re going to do it.

This Is Only the Beginning

Hopefully, you now have a fundamental grasp of unit testing in C#. The core idea is really straightforward and effective. Don’t let the experiences and technologies that have been added on top of it divert your attention from it.

However, keep in mind that in the decades since its introduction and automation, the world has learnt a lot about unit testing. Although you now grasp the basics, there is still a lot of learning and practicing that needs to be done. There is no better time to begin than right now.

Grasp The Software Dev Lifecycle: SDLC Overview

Grasp The Software Dev Lifecycle: SDLC Overview

Software Development Life Cycle

The SDLC: Never-ending fun – the philosophy of software development life cycle

Greetings, dear readers! Earlier in the articles of this blog, we have already touched on various aspects of the methodology and principles of software development. For example, in one of the recent articles, we discussed in detail the definition of a sprint in Agile methodology. We recommend you to read this one if you have not done it yet – It is really very interesting and useful information.

However, the more we write, the more questions arise, since software development is indeed very multifaceted and complex. Therefore, in this article we would like to pay attention to a fairly global thing, the understanding of which will help our regular readers to better navigate the subsequent narrower topics. This one is Software development life cycle – SDLC.

What is SDLC and why to use it?

Okay, first of all, let’s define the meaning of SDLC. Most often, when it comes to software development lifecycle, they mean the process of creating software from A to Z. But such a definition of SDLC is appropriate only when it comes to a specific project. In a broader sense, the software development life cycle is a standardized framework, based on which a team can release a product faster, make it better, minimize risks and avoid situations when you have to rush to finalize already finished software.

Here it is appropriate to pay attention to the word “cycle” in the wording itself. You may have seen this picture before:

SDLC methodology phases Подпись: Software life cycle never stops

Note that deployment (the last phase of the cycle) invariably leads us to the very first one: requirements analysis. This means that the software life cycle never ends. Indeed, there are no products that would be forgotten by the development team immediately after the release. Any software solution periodically needs to be updated, refined, and scaled. That is, after deploying your product, you will invariably have to return to requirements analysis, having already received real feedback from end users in one form or another.

If we are talking specifically about the creation of new software, the SDLC methodology ensures the coherence of the actions of the entire team, since each of the stages consistently and effectively influences the next one. This avoids many mistakes that could later lead to serious difficulties or even failure of the project. In other words, the software dev lifecycle is a kind of development plan template.

Software development life cycle methodology step by step

Well, let`s back to our picture. Here you can see the standard SDLC model with six main software development life cycle phases, which are:

  1. requirement analysis;
  2. planning;
  3. architectural design;
  4. software development;
  5. testing;

Requirement analysis

The first step is quite simple but no less important! Answer the fundamental question: “What are the requirements our product needs to meet?”. At this stage, it is very important to achieve maximum mutual understanding with the customer. Typically, the customer, business analyst, project manager, and members of the project team are involved in this process.

When all the requirements and expectations of the customer are specified, a document called the Software Requirement Specification is drawn up. It contains everything that has been said before. Subsequently, the developers will be guided by the SRS, so that all requirements must be clearly stated, and the document itself must be pre-approved by the customer.

An interesting fact is that during the development process of Instagram, it was the requirements analysis that took the most time. Social networks were not yet so popular, and the developers had almost no reference points, but today it is difficult to find a person who would not have an Instagram account. Isn’t this a great example of how important requirements analysis is and how effective SDLC in software engineering can be? We think it is!

Planning

An integral part of software development life cycle models is the planning process. Often it is combined with requirements analysis, but we believe that these stages should be separated. The fact is that requirements analysis involves communication between the customer and the client in order to understand what the software should be like. And the result of planning is the estimated cost of the project, risks and plans to reduce them, etc.

Simply put, at the planning stage, the team finds out whether what the customer wants is feasible, how much time and resources it will take, and how to implement it with the least loss.

Architectural design

Architectural design in software life cycle usually raises the most questions for those who are just starting to delve into the SDLC. As you surf the web, you can find a lot of different statements like “at this stage you convert your SRS into a project specification” (which is also a kind of plan, so it’s not clear how this stage differs from planning) or “this is the process of creating a software architecture, on the basis of which you will develop your system”, etc.

Many of them do not give a complete understanding of the essence of architectural design. Here we need to correctly pose the question, the answer to which we give at this stage (yes, this is still a process of preparation for real work). So, the question is: “How are we going to achieve our goals?”.

In this phase, we recommend considering several key design elements to make final design decisions: operational excellence, safety, reliability, performance efficiency, and cost optimization.

Software development

Finally, we no longer answer any questions, but get down to business! So, your main task is to do an amazing job, justify the trust of the customer and be satisfied with the result. Fill up with hot coffee, roll up your sleeves and do it! There’s nothing more to say.

Testing

Developers vs testers is a never ending story. However, the systems development life cycle methodology does not prioritize one over the other. You must understand that there will be no release of the product until your product meets the specifications. Everyone makes mistakes, even developers (and here one tester smiled).

Deployment

Each development cycle ends with software deployment. And then it starts all over again.

You see, in theory, deployment is all that makes a program usable in a production environment, from installing it on a computer to releasing updates. But we have already understood that the cycle inevitably moves to a new round. Therefore, by deployment we mean the processes accompanying the release of programs, but not their support in the future – for this we have to start again with a requirements analysis.

By the way, congratulations on the release!

Step 7?

For the sake of completeness, another phase of the software development life cycle should also be mentioned. This is maintenance, which is not always distinguished as a separate stage. DevOps engineers are working in this direction. In fact, they are engaged in the maintenance of the system after its deployment. But in a broader sense, they have a more significant mission – to be a bridge between the OPS and development teams. When both use common tools for error detection or performance checks, this fundamentally changes the SDLC experience.

SDLC models to implement: benefits and peculiarities

Now let’s take a look at the most popular examples of SDLC models

SDLC models

Waterfall

Of all the known software development lifecycle models, the waterfall is the oldest and, to some extent, the most primitive. According to this concept, the entire development process is divided into several stages, and each next cannot be started until the previous one is completed. The waterfall has one significant drawback: if small tasks were not completed during any stage, they can create a big problem in the future, because the plan for subsequent stages does not involve patching these “holes”.

Agile

Based on the name of the agile methodology, it is clear that this approach is designed for the flexibility of the development team. The project is broken down into continuous cycles, which are also divided into smaller iterations. At the end of each iteration, the product (or some part of it) is tested, which prevents small unsolved problems from becoming a serious problem in the next stages.

Today, more and more teams are abandoning the waterfall in favor of an agile methodology. It should be noted that among the newer SDLC approaches, agile is the most developed. It is also divided into several different sub-methodologies: Scrum, Kanban, etc.

Iterative model

The project is divided into several iterations, and at the end of each we have a version of the product ready for deployment/ The version already meets some functional and non-functional requirements (not all). The final iteration leads to the release of a product that meets the full list of requirements.

V-Shaped SDLC

A more flexible version of the waterfall. The development stages also strictly follow each other, but testing is carried out at each stage, which allows you to respond to shortcomings in time.

Spiral model

This model is also based on iterations, but the spiral approach can also include methods that are characteristic of other models.

The development process is managed by the project risk assessment system, which will be unique in each case. Thus, the spiral is the most flexible of the SDLC models.

The Big Bang

A very simple SDLC model that does not require careful planning, but is associated with the greatest risks. In view of this, the Big Bang model is only applied to small projects where the developer has more opportunities to show their creativity.

It’s also a very fast development, even spontaneous in a way. On the other hand, we all know how much beauty the Big Bang created, right?

On a final note

The SDLC framework helps development teams reduce production time, increase productivity and potential profit, save budget and minimize project risks. In general, this is a plan for conducting technical work, but if you look more broadly, you can think of it as a guide to life. You can apply SDLC to a variety of topics. Think of the SDLC as a blueprint for expected success and it won’t take long.

Review of the Best CD CI Tools in 2023 – Choose The Most Related

Review of the Best CD CI Tools in 2023 – Choose The Most Related

CI CD tools

What is CI/CD and the Best Tools You Must Know

 

Overview

By adding automation to the various stages of app development, CI/CD is a technique for regularly delivering apps to clients. Continuous integration, continuous delivery, and continuous deployment are the three core CI/CD concepts. The challenges integrating new code can provide for development and operations teams are addressed by CI/CD (AKA “integration hell”).

In particular, CI/CD brings continuous monitoring and continual automation throughout the whole lifespan of an app, from the integration and testing stages to the delivery and deployment stages. Development and operations teams collaborate in an agile manner using either a DevOps or site reliability engineering (SRE) methodology, and these interconnected processes are collectively referred to as a “CI/CD pipeline tools.”

Differences Between CI and CD?

There are numerous definitions for the abbreviation CI/CD. Continuous integration is always referred to as “CI” in CI/CD, and it is a method that automates development. A successful CI involves routinely building, testing, and merging new code changes to an app into a shared repository. It offers a solution to the issue of having too many potentially incompatible branches of an app in development at once.

Continuous delivery and/or continuous deployment are similar ideas that are occasionally used interchangeably and are denoted by the “CD” in “CI/CD.” Both are concerned with automating pipeline steps after the initial stages, however they are occasionally used independently to highlight the extent of automation.

Continuous delivery typically entails that an operations team can deploy a developer’s changes to a live production environment after they have been automatically checked for bugs and submitted to a repository (such as GitHub or a container registry). It provides a solution to the issue of the development and business teams’ limited visibility and communication. In order to ensure that deploying new code requires the least amount of work possible, continuous delivery was created.

The alternative meaning of “CD” is continuous deployment, which is the process of automatically pushing changes made by developers from the repository to a live environment where users can access them. It deals with the issue of operations teams being overburdened with manual tasks that impede app delivery. By automating the following pipeline stage, it expands on the advantages of continuous delivery.

CI CD differences

Both the connected practices of continuous integration and continuous delivery, as well as all three connected practices of continuous integration, continuous delivery, and continuous deployment, may be referred to as CI/CD. It gets even more difficult because “continuous delivery” is occasionally used to refer to continuous deployment procedures as well.

In the end, it’s probably not worth your time to get mired in these semantics; instead, just keep in mind that CI/CD is truly a process that adds a high level of ongoing automation and continuous monitoring to app development. This process is frequently represented as a pipeline.

Depending on how much automation has been incorporated into the CI/CD pipeline, each situation will determine what the terms mean. Many businesses begin by using CI, and as time goes on, they go toward automating delivery and deployment, for example as part of cloud-native apps.

Our specialists can assist your company in creating the cultures, tools, and practices required to create new apps and upgrade old ones in a more effective manner.

Continuous Integration

The objective of contemporary application development is to have numerous developers working on various aspects of the same app concurrently. The effort that results, however, can be laborious, manual, and time-consuming if an organization is set up to combine all branching source code together on one day (known as “merge day”). This is so that modifications made to an application by a developer working alone won’t necessarily conflict with other changes being made to the same application at the same time. Instead of the team deciding on a single cloud-based IDE, this issue may be made worse if each developer has customized their own local integrated development environment (IDE).

Continuous Delivery

Continuous delivery automates the deployment of that validated code to a repository after the automation of builds and unit and integration testing in CI. Therefore, it’s critical that CI be already included in your development pipeline in order to have a successful continuous delivery process. A codebase that is constantly prepared for deployment to a production environment is the aim of continuous delivery.

Every step in continuous delivery—from merging code changes to delivering builds fit for production—involves test automation and code release automation. The operations team can then swiftly and easily deploy an app to production after that procedure is complete.

Continuous Deployment

Continuous deployment is the last phase of an advanced CI/CD process. Continuous deployment automates the release of an app to production as an extension of continuous delivery, which automates the release of a production-ready build to a code repository. Continuous deployment largely relies on well-designed test automation since there is no manual gate at the pipeline level prior to production.

Continuous deployment actually allows a developer’s modification to a cloud application to go live minutes after it is written (assuming it passes automated testing). It is now much simpler to regularly gather and take into account customer feedback. When all of these related CI/CD techniques are used, deployment of an application becomes less hazardous, making it simpler to release app modifications incrementally rather than all at once. A significant upfront investment is also required because a number of testing and release phases in the CI/CD pipeline need the creation of automated tests.

CI/CD Tools List

What are Ci/CD tools?

A team can automate development, deployment, and testing with the aid of CI/CD systems. Some technologies specialize in continuous testing or related tasks, while others manage development and deployment (CD) and the integration (CI) side.

Lets start and present the 14 best and most used CI/CD tools.
Without separating CD tools from CI tools the below list includes 7 of each of the categories.

Jenkins, an open source automation server, is one of the most well-known CI/CD systems. Jenkins can manage everything from a straightforward CI server to a full-fledged CD hub.

1. Jenkins

Jenkins

The central build and continuous integration process is carried out by Jenkins, an open-source automation server. It is a standalone Java program providing packages for Windows, macOS, and other operating systems that resemble Unix. Jenkins allows creating, delivering, and automating for software development projects and has hundreds of plugins available.

Jenkins key features:

  • Straightforward OS installation and upgrading
  • A straightforward and user-friendly interface
  • Large community-contributed plugin resource makes it extensible
  • Simple environment setup through the user interface
  • Supports master-slave architecture and distributed builds
  • Create schedules using expressions
  • Supports pre-build steps that use shells and Windows command execution.
  • Offers support for notifications about build status.

License: Free.

2. CircleCI

A CI/CD technology called CircleCI promotes quick software development and publication. The user’s pipeline can be automated with CircleCI, from code development to testing and deployment.

To make builds when new code lines are committed, CircleCI may be integrated with GitHub, GitHub Enterprise, and Bitbucket. CircleCI also offers cloud-managed continuous integration hosting or use local infrastructure that is protected          by a firewall.

CircleCI key features:

  • Integrates with GitHub Enterprise, Bitbucket, and GitHub
  • utilizes a virtual machine or container to run builds
  • Simple bug fixing
  • Automatically parallelizing
  • Rapid tests
  • Individual emails and IM notices
  • Branch-specific deployment that is ongoing
  • highly adaptable
  • Custom commands and automated merging for package uploading
  • Quick setup and limitless creations

License: Starting with Linux plans, one job can be executed without parallel processing with no additional cost. You can choose the plan(s) you require after viewing the cost throughout the signup process.

3. TeamCity

TeamCity

JetBrains’ build management and continuous integration server is called TeamCity.

A continuous integration solution called TeamCity aids in developing and deploying various project kinds. TeamCity interacts with Visual Studio and IDEs and operates in a Java context. The program supports.NET and open-stack applications and may be installed on both Windows and Linux systems.

New UI and direct connection with GitLab are features of TeamCity 2021.1 . Additionally, GitLab and Bitbucket server pull requests are supported. The release contains requests for AWS Spot Fleet, detection of Go tests, and token-based authentication.

TeamCity key features:

  • Provide many options for reusing the settings and configurations of the parent project in the child project
  • Simultaneously does parallel builds in various contexts.
  • Makes it possible to run previous builds, see test history reports, pin, tag, and favorite builds.
  • Simple to interact with, alter, and expand the server
  • ensures the CI server is operational and reliable
  • Flexible user administration, user roles assignment, grouping of users, several user authentication methods, and a log of all user activity for full transparency of all server activities

License: A commercial tool with both open-source and exclusive licensing is TeamCity.

4. Bamboo

Bamboo

A continuous delivery pipeline is created by Bamboo, a continuous integration server, which automates the management of software application releases. Assigning versions, categorizing releases, delivering, and activating new versions on production are all covered by Bamboo.

Bamboo key features:

  • Up to 100 remote build agents are supported
  • Parallelize test runs and receive fast feedback.
  • Generating photos and submitting them to a repository
  • Per-environment rights that let developers and testers deploy to individual environments as needed while the production environment is kept secure
  • Detects new branches in repositories for Git, Mercurial, and SVN and automatically applies the main line’s CI scheme to them.
  • Builds are triggered based on changes found in the repository. Notifications are pushed from Bitbucket, according to a predetermined schedule, when a build is finished, or any combination of these.

License: Instead of using users, Bamboo bases its pricing levels on agents or “build slaves.” More processes can run simultaneously, either in the same build or in multiple builds, the more agents there are.

5. GitLab

GitLab

GitLab is a collection of instruments for controlling various phases of the software development lifecycle. The main offering is a Git repository manager for the web with tools for issue tracking, analytics, and a wiki.

With each commit or push in GitLab, you have the option to start builds, launch tests, and deploy code. Jobs can be created on another server, in a virtual machine, or using Docker containers.

GitLab key features:

  • Branching tools are used to see, produce, and manage codes and project data.
  • Using a single distributed version control system, create, develop, and manage code and project data to enable quick iteration and the delivery of business values.
  • Offers scalability and a single source of truth for working together on projects and code
  • Automates builds, integration, and source code verification to assist delivery teams in embracing CI.
  • Delivers safe applications and licensing compliance with container scanning, static application security testing (SAST), dynamic application security testing (DAST), and dependency scanning.
  • Aids in automating and accelerating application delivery and releases.

License: GitLab is a for-profit product and free download. It provides hosting for SaaS on GitLab, your own instance on-premises, in the public cloud, or both.

6. Buddy

Buddy

Buddy is a CI/CD tool that uses code from GitHub, Bitbucket, and GitLab to build, test, and deploy websites and applications. It uses DevOps, monitoring, and notification processes along with Docker containers that come pre-installed with the languages and frameworks that may be built upon.

Buddy key features:

  • Easy to modify Images created using Docker as a test environment
  • Intelligent change detection, cutting-edge caching, parallelism, and general optimizations
  • Create, alter, and utilize test and build environments
  • Workspace, project, pipeline, and action scopes are fixed and programmable, plain and encrypted.
  • Elastic, MariaDB, Memcached, Mongo, PostgreSQL, RabbitMQ, Redis, Selenium Chrome, and Firefox are examples of attachable services.
  • Monitor with infinite history, real-time progress, and logs
  • Workflow management using templates for pipeline cloning, exporting, and importing
  • Superior Git integrations and support

License: Buddy is a freely available.

7. Travis CI

Travis CI

A CI service used to build and test projects is called Travis CI. New commits are automatically found by Travis CI and pushed to a GitHub repository. Additionally, Travis CI will build the project and run tests after each new code commit.

Numerous build configurations and languages, including Node, PHP, Python, Java, and Perl, are supported by the tool.

Travis CI key features:

  • Rapid setup
  • Views of live builds for GitHub projects
  • Pull request assistance
  • Multiple cloud services deployment
  • Built-in database services
  • Auto-deploys when builds pass
  • Pristine VMs for each build
  • Complies with iOS, Linux, and macOS
  • Supports a variety of languages, including R, C, Python, Ruby, Java, C, C#, C++, Perl, PHP, and JavaScript (with Node.js).

License: A hosted CI/CD service is Travis CI. On Travis-CI.com, test runs for personal projects are available for a charge. On Travis-ci.org, open-source projects can be applied for free.

8. Codeship

Codeship

A hosted platform called Codeship allows for many early and automatic software releases. By streamlining the testing and release procedures, it aids software firms in producing better products more quickly.

Codeship key features:

  • Integrates with a variety of tools, services, and cloud computing environments.
  • Simple to use gives developers prompt, detailed help.
  • With CodeShip’s turnkey infrastructure and straightforward UI, builds and deploys are completed more quickly.
  • Option to choose the size, CPU, and memory of an AWS instance
  • creates teams and assigns access to team members and organizations using the notification center
  • Project dashboards, intelligent notification management, and seamless third-party interfaces all work together to give you a high-level picture of your projects’ status.

License: Utilize 100 builds each month for no cost; unlimited builds are available for $49 per month. With bigger instance sizes, you can pay for additional parallel pipelines or concurrent builds.

9. GoCD

GoCD

GoCD is an open-source development and software release solution from ThoughtWorks that supports contemporary infrastructure on CI/CD.

GoCD key features:

  • Dependencies are simple to configure for quick feedback and on-demand deployments.
  • Favors reliable artifacts: A specific changeset serves as the anchor for each pipeline instance.
  • Controls your whole workflow, allowing you to trace changes from committing to deployment at a look.
  • The upstream and downstream are clearly visible.
  • Any version may be used at any time.
  • allows you to distribute any known-good version of your application to any location you want.
  • Utilizes the Compare Builds functionality to obtain a straightforward bill of materials for any deployment.
  • Keeps configuration organized by leveraging the GoCD template system to reuse pipeline setups.
  • There are already many plugins available

License: Free and open-source.

10. Wercker

Wercker

Developers that are working with or considering beginning a new project based on Docker may find Wercker to be a good fit. Wercker assists businesses in using CI/CD, microservices, and Docker with their development teams.

Oracle disclosed that it had finalized a deal to acquire Wercker on April 17, 2017.

Wercker key features:

  • Version control and integrations with Git, including GitHub, Bitbucket, and GitLab
  • Make a local copy of the SaaS environment using Wercker CLI to test and troubleshoot pipelines before deploying.
  • Supports Wercker’s Docker integration helps create small containers with manageable sizes.
  • You can interact with notifications through Walterbot, a chatbot in Wercker, to find out the status of the development.
  • Environment variables aid in preventing the repository from storing sensitive data.
  • Wercker makes advantage of essential security features, such as source code protection to disable test logs, protected environment variables, and user and project permissions that are customisable.

License: Following its acquisition, Oracle did not disclose Wercker’s pricing.

11. Semaphore

Semaphore

A hosted CI/CD solution for testing and deploying software projects is called Semaphore. Through a development process based on pull requests, Semaphore sets CI/CD standards.

Semaphore key features:

  • Connected to GitHub
  • Automates any pipeline for continuous delivery
  • Use the quickest CI/CD platform
  • Scales your project automatically so that you only pay for what you really need Native Docker support. Applications built with Docker are tested and released.
  • Offers Boosters, a feature for Ruby projects that automatically parallelizes builds to cut down on the time it takes to execute the test suite.

License: Flexible. The capacity of your package determines your options for typical CI services. Semaphore 2.0 will scale in the interim based on your team’s actual requirements, so you won’t be charged if you don’t use the product.

12. Nevercode

Nevercode

For mobile apps, Nevercode offers CI/CD. Faster native and cross-platform app development, testing, and publication are all benefits.

Nevercode key features:

  • Automatic setup and configuration
  • Test automation includes code analysis, real-world testing on devices, unit and UI testing, and parallel testing.
  • Automatic publishing: Crashlytics, TestFairy, Google Play, and HockeyApp
  • A thorough summary of your build and test status

License: Flexible. Different continuous integration plans for various needs. Standard plans are available, or you can ask for a plan that is specially created for your needs.

13. Spinnaker

Spinnaker

AWS EC2, Kubernetes, Google Compute Engine, Google Kubernetes Engine, Google App Engine, etc. are just a few of the cloud providers that Spinnaker supports for releasing and deploying software changes across.

Spinnaker key features:

  • Creates deployment pipelines that launch and stop server groups, conduct integration and system tests, and keep track of rollouts. Git events, Jenkins, Travis CI, Docker, cron, or other Spinnaker pipelines can all be used to start pipelines.
  • Create and deploy immutable images to accelerate rollouts, make rollbacks simpler, and get rid of configuration drift problems that are difficult to troubleshoot.
  • Use the metrics provided by monitoring services like Datadog, Prometheus, Stackdriver, or SignalFx to connect your releases and use canary analysis.
  • With Halyard, Spinnaker’s CLI administration tool, you can install, configure, and upgrade your instances.
  • Set up SMS, Slack, HipChat, or email event notifications (via Twilio)

License: Open source.

14. BuildBot

BuildBot

Buildbot is a “Python-based CI framework” that automatically rebuilds and tests the source tree after each change while automating the compile and test cycles to validate code changes. As a result, construction issues are rapidly identified.

BuildBot key features:

  • Automate build processes, application deployment, and the control of complex software-release procedures.
  • Supports rich status reporting, flexible connection with version-control systems, distributed, parallel execution across different platforms, and
  • Executes builds on several slave platforms.
  • Arbitrary build process and handles C and Python programs
  • Python and Twisted are the minimum host requirements.

 License: Open source.

Conclusion

The top 14 CI/CD tools on this list are the ones that are currently selling the best. We hope this list has given you enough information to make an informed decision about the program that best meets your needs. The CI/CD tools listed below are the most developed ones with the crucial features for your projects. Your final decision will be influenced by your needs, the infrastructure that is in place, as well as opportunity for improvement in the future.

The CI/CD and DevOps trends will keep changing, giving the market room to expand and advance. This list will be updated to guarantee that the information is accurate for you as the environment changes. Additionally, Katalon Academy is offering you a free course to assist you learn more about the CI/CD pipeline.

You can also use this free self-assessment to find out where your team stands in the continuous testing maturity roadmap and to receive professional advice on how to enhance your CI/CD.