Understanding Software Testing Automation for Continuous Delivery

Automation is driving the decline of mundane and repetitive tasks. And this holds absolutely true for a software development cycle. 

There is a provision to automate almost every aspect of a software development cycle- coding, testing, and even deployment.

The development stakeholders are highly reliant on tools that help them in source code collaboration, task or workflow management, continuous integration & delivery, writing test scripts, review code, push deployments, and a lot more. 

While there is a lot that these tools can do to automate, manage, and optimize the development cycle, here, in this article, we will specifically talk about automating software testing. 

The idea of software testing automation has been existing in the development ecosystem for quite some time. Still, there are several questions related to it that are doing rounds:

• Does my software development project need automation testing? 
• At what stage of development should automation be introduced? 
• Regression testing is fine. Why automation software testing? 
• How automation testing would benefit my team in long run?
• Regression testing is cost-effective and foolproof. Then why automation? 

We have created this guide to software testing automation that aims to answer all of the above queries related to this topic. Let’s get started. 

What is Automation Software Testing? 

Before this testing practice was introduced, the Quality Analyst (QA) team would review the codebase, business logic, and user experiences of an application, manually. Irrespective of the scale and complexity of the software, the QAs check the application over and again for inconsistencies at different stages of development. This process was slow, error-prone, and proved expensive for large-scale projects as the QA team size would be extensive.

Moreover, manual testing was not able to fit into the modern methodologies of software development like DevOps. To continuously develop, deliver, and deploy an application, a fast-paced testing environment was to be created that ascertains that things can move in a pipeline without human intervention. And that’s how automation software testing was introduced. 

• Automation boosts the regression testing cycle  

No matter what’s the scale of a software development project, manual testing is time-consuming. For every new feature or update that’s introduced to the application, the QA team has to perform the same set of tests again, which brings down the overall efficiency of the testers. Performing regression tests manually has the following limitations: 

a) In a modern development cycle, regression testing can create congestion and delays due to the manual processes being slow. 

b) Every step in the manual regression cycle cannot be performed thoroughly. As the application grows in size, the QAs to test the features change, and the way of testing changes as well. 

When software testing is automated, every feature of the application is tested in exactly the same way.

However, it has to be noted that not all features in an application need to be automated. Manual regression testing will always be there. This way, manual and automation testing compliments each other. 

• Automation gives velocity to the CI/CD pipeline 

Continuous Integration and Delivery (CI/CD) is an integral part of the software development cycle these days. Automation of software testing gives momentum to the CI/CD pipeline.

This happens through Continuous Testing, which involves running automated tests against a new code to verify that the established features don’t break or introduce new bugs. Once the automated test plans pass this phase, Continuous Deployment is triggered. 

Continuous Deployment ensures that the new code is delivered to the customers as fast as possible, without human intervention. This can be possible only with a rigid and automated software testing plan in place. 

Continuous testing promotes the shift-left testing approach. This is a practice that ensures that testing is introduced in the SDLC cycle, as soon as possible. Therefore, it helps in identifying and fixing issues and inconsistencies at an initial stage of development, making deployments faster. 

• Automation maximizes the test coverage

As the application grows in scale and complexity, there could be thousands of test cases to execute. If the frequency of deployment is high, then manually testing an application for all the test cases is not possible for a QA team. 

However, if the repetitive test cases are automated, it will help the team to give more attention to critical features and experiences in the application, manually. 

When a mix of automated and manual testing practices is deployed, it helps the tester to do multi-tasking and saves them from repetitively testing the same features and business logic, over-and-again. The Quality Analyst team thus has time to invest in improving their efficiency and ROI. 

• Automation saves up to 60% of the testing time (on average)

Automation testing saves time. And it saves a significant amount of time!

On average, automation software testing saves up to 60% of the testing time. 

The best part of automation is it enables the QA team to schedule testing and execute it from a remote location. The test reports can be accessed and shared remotely, which accelerates the testing cycle to a great extent. 

CUSTOMER SUCCESS STORY: Learn how automating the regression suite helped an eCommerce firm reduce chances of error leakage and cut down the testing efforts of critical features by 75-80%.

Creating an Automation Strategy(Right Tests for Automation)

Before executing an automation cycle, it is important to be clear about what needs to be achieved with it. The QA team needs to have a strategy that clearly defines the type of test cases that needs to be automated. Here are a few examples of test cases that can be automated. 

• End-to-End Tests

End-to-end testing checks for functionality and performance of the application under product-like circumstances and data. This replicates a live product environment so that testing can be performed from a real user perspective from start to end. 

It includes test plans that cover user-level stories like “a user can log in”, “user can change the password”, etc. End-to-end testing ascertains that the end-users are having a bug-free and seamless user experience, even when a new code is published. When automating software testing, it is essential to automate critical E2E tests for business-critical flows. 

• Unit Tests 

In unit testing, the smallest testable parts of a software application, called units, are independently scrutinized for their functionality. It verifies that there are no dependencies on the codebase and for a certain input, the function matches the expected output. Unit tests are inexpensive, easy to implement, and provide a high return on investment. 

• Integration Tests

A software application consists of several modules (that are usually coded by different programmers). Integration testing involves combining several modules together and checking for any kind of interaction defects between them. For example, how the application interacts with the 3rd party services. 

• Performance Test

Performance testing is the practice of evaluating the performance of a software in terms of speed, reliability, application size, robustness, etc. This includes testing an application for factors such as browser/page/network response times, acceptable concurrent users, server request processing time, etc. 

CUSTOMER SUCCESS STORY: How Daffodil optimized a gaming platform with an average response time of 1.8 seconds for 10K concurrent users.

Regression VS Automation Testing? (Which one does your project actually need?)

One of the common questions that Daffodil, as a software testing services provider, usually encounter is- does my project needs to automate testing? Or Which testing approach would work best for our project? 

The answer to these queries lies in the use case of both the testing approaches. 

Regression testing is a manual approach to verifying the functionality of an application. As long as the scale of the application is small and regression gives maximum test coverage, it is absolutely fine to go with it. 

Software testing automation comes into the picture when the scope of the application is extensive and manual testing is not enough to provide full test coverage to the project. Therefore, choosing between the two test approaches needs an evaluation of the project in terms of scale & budget, frequency of releases, available tools, and the development approach followed (For example, the DevOps approach to development is incomplete without automation testing).

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