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How to improve code coverage of Regression Testing without Writing Scripts

What can you do to prevent failures in software that are increasing in size and control the difficulties that arise because of it? Testing such systems can be very tricky and expensive. It is very difficult to balance cost, the number of bugs, and testing coverage. In software testing, test coverage is defined as the amount of codebase covered by a collection of tests. It is a great way of finding the penetration of a set of test cases, or the areas of the requirement not implemented by them. These tests include but are not limited to unit testing, smoke testing, alpha testing, etc. In this article, we will talk about some techniques which can be implemented by you and your team to improve testing coverage to facilitate effective regression testing.

How will this benefit me?

Regardless of if you are a manager, investor, director, member of quality assurance teams, or even a client, you stand to benefit from a testing suite with increased test coverage. In conventional manual testing processes, it is often difficult to gauge how well a certain test or a set of tests has been performed. Testing coverage thus provides us with critical information and shows the teams where to focus their testing. As a result, testing coverage is often synonymous with code quality. And the better that is, the smoother your application will run and you will have more confidence over your code. This will also help in attracting potential customers, as they often tend to perform a thorough audit of the product from a variety of perspectives viz., security vulnerabilities, tests, code coverage, performance, technology stack, etc. A bug-free application makes for a smoother consumer experience and thus helps alluring prospective customers.

Why should I care about regression testing?

Regression testing is a type of testing mechanism that is generally performed after a recent program or code change to confirm that the update has not adversely affected the application. It is a full or partial selection of already executed test cases that are re-executed to ensure the functionality of the program. As this is performed after a major or minor change, testing becomes difficult as changes become more frequent and the codebase increases in size. This makes manual testing unfeasible in most scenarios, and a need for an automated workflow arises. Automated regression testing utilizes computer-based tools and techniques in testing software after it has been changed or updated. It ensures the compilation of the program after an update, performs testing of the workflow or core logic of the software, and also tests any supporting services that are peripheral to and complement the software. This totally eliminates the need for expensively trained professionals as the task is automated. A certain amount of manual intervention is needed, but it substantially reduces the amount of cost spent on labor.

What is testing coverage?

Test Coverage = TE 100 T

Where,
TE = No. of test cases executed,
T = Total No. of test cases

Identification of most critical limitations:

Will address in detail the challenges teams face while performing regression testing, the need for automated testing, and discuss the imperfections of automated testing – how important comprehensive code coverage is and why it is difficult to achieve with automated testing However, there are some downsides to this process. An ideal scenario would be having maximum test coverage with minimal test cases, but more often than not this is not easy to achieve. A huge factor associated with regression testing is its cost, as it needs to be re-executed after every change that is made to a program. And thus if a program has very frequent changes, regression testing is performed after every release and this is unfeasible.

Do’s and Don’ts for effective regression testing.

What we should do:

  • The quality assurance team is to go through the number of requirements subject to be tested for the program.
  • Available resources like computation available and time in hand should also be cross-checked by the team.
  • Build a robust test strategy to cover the requirements and testing methods.
  • Document – Test plan documentation is as important as the actual execution of the tests.
  • Tasks should be prioritized into critical, major, and minor categories for efficient scheduling of tasks. Utilize efficacious automated test suites like CloudQA to keep manual intervention at a bare minimum.

What should we avoid:

  • Being completely dependent on automated testing systems.
  • Wasting time and resources on undetectable or untestable faults.
  • Focusing and emphasizing too much on the code coverage percentage metric.

Now let’s take a look at some viable techniques suitable to improve testing coverage:

1. Removing dead code :
Dead code are blocks of instructions that are executed but the resultant output is never used in any other computation. Removing such redundant code helps in improving testing coverage. This is because testing coverage is a ratio of code executed and total code. Thus, reducing the denominator by getting rid of dead blocks of code is a practical way of increasing coverage without making any negative impact on the functionality of the website.

2. Enhancing the scope and quality of test automation:
Test automation lets you perform more tests in less time. If we only depend on manual testing, it will lead to bottlenecks and consequently slow down your ‘time-to-market’. Continuous integration and continuous deployment with test automation help you identify errors in your product early in the development lifecycle. Automated testing suites especially shine in testing scenarios, such as repetitive tests or tests that expect a specific result. To improve test coverage, try to automate wherever it’s possible and feasible. As a result, you can use the gained time to test on more devices or increase your code coverage.

3. Gather actionable data:
Data collection is a necessary practice for high-quality quality assurance teams. Knowing the industry benchmarks, and customer sentiment can help ensure that your team is focused on testing the most important parts of your application, and provide you the path to improving the overall customer experience. Instead of being relegated as a routine task to be completed, testing takes on a strategic function within software development.

4. Choosing the Right Code Coverage Metric:
Before instituting a test monitoring strategy, it is necessary to define what should be tracked and analyzed. It is thus necessary to choose the most relevant metric for code coverage from the existing metrics such as Function coverage, line coverage, statement coverage, decision coverage, etc. A general rule is to say that a single issue should be monitored by a single measurement, simply to make the analysis easier. Following all metric values makes the results difficult to interpret.

Final thoughts:

To obtain a more informed assessment of your application’s quality it is crucial to conduct a thorough code coverage analysis. For existing software without automatic tests created from the get-go, using a code coverage tool can help ensure quality future product releases. Achieving high test coverage can be done in many ways, but it’s important to look at the strategies behind your coverage goals to make sure they remain efficient. Because having a very high testing coverage at the cost of extreme computation and time required is not feasible for any team or project.

Published on Java Code Geeks with permission by Arun Kulkarni, partner at our JCG program. See the original article here: How to improve code coverage of Regression Testing without Writing Scripts

Opinions expressed by Java Code Geeks contributors are their own.

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