How To Improve Automation Test Coverage

Test coverage has become one of the foremost quality metrics that aid developers and testers in estimating the amount of testing achieved in the test cycle as a whole. It helps to understand whether the team has tested enough components holistically or if there’s room for further improvement. Inadequate test coverage leads to the risk of a high proportion of bugs in production, and thus it is imperative for teams to obtain maximum test coverage before the software is rolled-out to production.

While sometimes, code coverage and test coverage are used interchangeably as they are both measures of the codebase’s effectiveness, they are quite different. 

Code coverage is a white-box testing technique that verifies the extent to which code has been executed. It uses static instrumentation for monitoring code execution at critical junctures in the codebase.

However, test coverage is a black-box technique that monitors the number of tests executed based on the test cases written in respect of

• Functional Requirements Specification
• Software Requirements Specification
• User Requirements Specification

Test Coverage can be calculated as the percentage of the application code covered by tests as compared to the entirety of the codebase.

For example, if only 5000 LOC have been covered by test cases out of 10k LOC, then the test coverage is 50%

Automation Test Coverage, thus, can be defined as the percentage of test coverage achieved by automated testing, as compared to manual testing. This article explains how automation test coverage can be expanded in scope in a test cycle.

Steps to Improve Automation Test Coverage

The key philosophy behind increasing automation test coverage is to ensure that automation testing is performed for as much of the code as possible. 

This includes:

• Strategizing in order to scale it across different environments and devices 
• Leveraging parallelization to speed up automation tests, thus improving the ROI
• Including automated tests for visual testing, which has been a traditional domain of manual testers.

Define the Scope and Goals of Embedding Automated Tests into the Testing Cycle

A major pitfall in trying to improve automation test coverage is to try and automate every test case. This is erroneous as no software can replicate the entirety of a manual testers skillset. Thus it is vital to decide the maximum scope of automation testing in a project. This is also known as Automation Feasibility Analysis. 

Test automation works best for cases where test cases have to be executed frequently and in a monotonous manner. 

Some suitable examples include:

• Repetitive actions like registration, login, OTP input, etc.
• Actions that need to be tested on multiple browsers, OS, or system configurations, etc.
• Regression tests that check the correct functioning of pre-existing functionality given the addition of new features.
• Tests that have binary Pass/Fail results and do not require manual re-verification.

Test across real devices and browsers

Another way of strategizing the goals and objectives is by delving into the test coverage techniques themselves and trying to identify the maximum scope of automated tests possible.

There are four coverage techniques that will help in this:

• Product coverage tells us how much of a product is covered by tests
• Risk coverage informs us about the inherent risks from the business logic of an application
• Requirements coverage tracks how many of the requirements are met successfully when the application is fully designed
• Compatibility coverage checks the compatibility across multiple browsers and devices for the application

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While considering product coverage one can break the product down into its constituent components in order to see if all the components have been tested. For instance, if a counter is used to indicate the number of items being added to a shopping cart, then one can test for scenarios to see if it’s successful in incrementing or decrementing the necessary values for the cart. One could also test to see if it accepts negative values.

By identifying the functionality and the usage of the components, you can then determine the best automation tools to help. If there are features like a quiz, then one could do SOA testing in an automated manner to see if the request/response set works correctly.

In terms of risk coverage, you can split the risks inherent in the application and test them thoroughly on the basis of priority.

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• The risks with the highest impact and probability (for example: a shopping cart item failing to be checked out if other elements are added, etc.) must be tested.
• Something that has a high impact but low probability, like a product being out of stock but still showing as available on the product screen, should be tested.
• You could test to see if a user can purchase a product marked as OUT OF STOCK, but the rest of the logic won’t support it in any normal scenario.
• And, you may decide not to test a scenario like what if a user tries to purchase a billion bars of soap.

Once this matrix has been computed, you can easily understand the ROI in automating each of these scenarios and proceed accordingly. The ROI for automating MUST and SHOULD test cases would be very high. And the MUST test scenarios should be a part of every automated regression test cycle due to the prioritization hierarchy.

Requirements Coverage tries to align the functionalities created and tested to the core requirements specification document.

Automated test coverage can be considered in this part as a part of a Shift left methodology.  Shift Left Testing tries to push the importance of testing to the “left,” as in the earlier stages of the pipeline. This aims to identify and resolve bugs as early in the SDLC as possible, and this improves overall software quality and has advantages in reducing time and cost penalties from discovering bugs late in the day.

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Device fragmentation is a major problem that many organizations suffer from as it causes product compatibility issues and hampers a product’s user experience. Test automation frameworks like BrosweStack provide a host of cross-browser testing tools that help prevent this scenario and help increase test automation coverage for Compatibility Coverage scenarios.

Selection of Automation Tools and Frameworks

Software test automation has proven itself to be a reliable and efficient process to achieve faster test coverage and provide greater accuracy at the same time. 

Once the team has decided what needs to be tested, the test pyramid can be used to split the tests in order of their performance

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A strong test pyramid needs a strong base, and that’s where the unit tests come into play. Some automation frameworks like Java’s Mockito and JS’s Simon can be used commonly found in the unit test tier of the pyramid. They help control the component behavior under test. 

However, unit tests are not sufficient to ensure complete quality control in the codebase. Integration tests make up the middle tier of the automation pyramid. Integration tests can help check the cross-functional interactions between different components (both internal and external).

There are a number of very popular tools that can be used for the automation of integration tests, such as Selenium (for the general web), Protractor (Angular), Espresso (Android), or Earl Gray (iOS).

End to End testing is extremely desirable in agile projects, as it goes beyond testing individual units. With the increasing adaptation of web and mobile applications worldwide, the onus to deliver end customer satisfaction and a seamless UX has increased as well. 

This phase of tests deals with user flows based on how users interact with the application and are crucial for the testing process. 

Several popular tools like Cypress and Playwright can be used to perform end-to-end testing in an automated manner

Introduce tools to make automation testing more attractive

One of the major gripes about introducing automation testing to test cycles is the phrase “it’s too much of a hassle,” and it is this mentality that leads to low automation test coverage in the first place.

Introducing the adoption of tools that help leverage the power of automation tests can be an absolute game changer in this field.

For example, parallel testing allows tests to be executed simultaneously over a number of different environments, device combinations, and browser configurations. Thus, a test suite that would take two minutes each on 45 Browser/OS configurations (90 mins overall) can be executed in just 30 mins if we run it on three parallels simultaneously.

Also, automation tools can be introduced into the CI/CD pipeline for conventionally manual processes like Visual Testing. Instead of poring over snapshots manually and trying to edge out false positives, AI-powered tools like Percy can help capture screenshots, compare them against a baseline and highlight any changes.

Increasing the amount of automation test coverage can help provide faster feedback in DevOps pipelines, even reducing the cost of test execution, guaranteeing higher accuracy, and freeing up valuable resources for more exploratory testing and high-value activities.

However, to ensure quality and reliability, these tests must be executed on real devices and browsers. Device fragmentation is a serious concern for companies, and the sites/apps need to work seamlessly across all possible configurations. 

BrowserStack provides 3000+ real browsers and devices that can be accessed for testing from anywhere in the world at any time and can be integrated with a variety of tools like Selenium and Cypress to help boost your automation test coverage.

Try BrowserStack now