How to improve code coverage of Regression Testing without Writing Scripts
How will this benefit me?
Why should I care about regression testing?
What is testing coverage?
Test Coverage = TE 100 T
TE = No. of test cases executed,
T = Total No. of test cases
Identification of most critical limitations:
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.
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.
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