Test Efficiency: How It Differs From Test Effectiveness?

Two crucial concepts in software testing are test effectiveness and test efficiency. While both terms are often used interchangeably, they have distinct meanings and contribute differently to the overall testing process. Understanding the difference between test efficiency and test effectiveness is key to optimizing software quality.

In this article, we will talk about test efficiency and test effectiveness, their importance, and how they are calculated. Let’s dive in.

What is Test Efficiency?

Test efficiency is a measure of how many resources were allocated and how many of those resources were utilized for testing. It is a measure of how well testing activities are performed in terms of time, cost, and resources while still ensuring the accuracy and completeness of the testing process.

This helps analyze if the project resources were well utilized to achieve the business goal.

Simply put, test efficiency compares the resources allotted for testing to the resources actually utilized for testing. It helps the organizations in planning the resources properly for future projects at less cost and effort.

According to reports, a bug that is not detected until production could cost around $10,000 and even more if it is left undetected. So, it is important to create an effective testing strategy to achieve the best results and deliver high-quality products.

How to Determine Test Efficiency?

The software testing process takes a lot of time, effort, resources, and money, be it manual or automated. Thus, it is crucial to make sure that all the tests run efficiently.

Now that you know what efficiency testing is, let’s learn to calculate test efficiency. To do that, you must analyze many variables like the success rate in finding bugs, the cost-efficiency and scope of the tests, etc. Another valuable requirement is to check if the test results would be adequate to decide if the product is ready to ship or not.

Using the best methods to calculate test efficiency is vital because the optimum metrics could help you deliver bug-free and high-quality products to the client. The two most popular techniques to measure test efficiency are as follows,

• Metric-based Approach
• Expert-based approach

Metric-Based Approach

A metric-based approach helps determine how you can improve testing procedures when they don’t progress as expected. Here, the metrics should be properly evaluated because they help estimate the testing efficiency.

The most used metric is the total number of bugs identified in various testing stages. The formula to calculate test efficiency is as follows,

You can also use other metrics like missed bugs, rejected bugs, test coverage, and requirement coverage to calculate the test efficiency.

Expert-based approach

As the name suggests, in this approach, the test efficiency is calculated by the software testing experts based on their experience and knowledge. You need to understand that the metrics that work best for one project may not work for other projects. That is why QA experts must pick the optimal metrics for a project based on their expertise and analysis.

Best Metrics to Judge Test Efficiency

There are several metrics to judge the efficiency of the testing process. The following are some of the best metrics that can be used to evaluate test efficiency,

1. Metrics That Cover Test Case Efficiency

Total Defect Containment Efficiency

This metric enables you to assess the efficiency of your test suite in detecting bugs. A higher ratio indicates that your testing processes have been effective and fewer bugs were detected after release. Conversely, a lower ratio suggests your test suite needs significant improvements. It also means that more defects might creep into the production, which will be expensive to fix. You can use the below formula to calculate Total Defect Containment Efficiency,

Total Defect Containment Efficiency = (Defects found in test stage/( Defects found in test stage + Defects found after release)) * 100

Test Passed Percentage

This metric is more like a summary of the testing process. It is more valuable when used with defect escape ratio, another metric for evaluating test efficiency. If both the test passed percentage and defect escape ratio are high, then it means that the test suite failed to identify crucial requirements. It further means that your tests are inefficient in finding bugs, and you should improve them instantly. You can calculate the test passed percentage using the below formula,

Test Passed Percentage % = (Number of tests passed / Total number of tests) * 100

2. Metrics that Measure Test Coverage

Test coverage is a vital aspect of the software development cycle. It helps identify the test plan’s quality and its other qualitative aspects. You can calculate test coverage using various formulas. Let’s discuss a few in the below section.

Requirements Coverage

This metric lets you calculate how much of the customer and stakeholder requirements your test suite is covering. You can use the below formula to calculate this,

Requirement Coverage = (Number of requirements covered / Total number of requirements) * 100

Functional Coverage

This metric lets you evaluate how much of the functional requirements your test suite is covering. Simply put, it lets you determine if your test suite will test all the vital functions. You can use the below formula to calculate functional coverage.

Functional Coverage = (Number of functional requirements invoked by test plan / Total functional requirements) * 100

Product Coverage

Product coverage calculates the parts of the product that have been tested against the total number of parts of the product. Simply put, it is the ratio between the tested parts of the product to the total number of parts available for testing.

Product Coverage = Total Parts of Product Tested / Total Parts of Product Available for TestingThis metric illustrates the test coverage in terms of the number of product areas covered by the tests.

Test Execution Coverage

It shows the ratio of test cases executed to the total number of test cases. It helps identify how many test cases have been executed so far. You can calculate the test execution coverage as follows,

Test Execution Coverage = (Number of tests run / Number of tests to be run) * 100

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3. Defect-Oriented Metrics for Test Efficiency

Defect-oriented metrics help categorize defects based on the type, cause of origin, or severity. Defect severity and defect density index are the most popular defect metrics. Let’s discuss them in the below sections,

Defect Severity Index

The Defect Severity Index estimates the impact a defect might have on a product’s component or function you are testing. Further, it informs about the quality of the product under test and will also help you evaluate the testing team’s efforts.

Defect Density Index = (Summation of Defect * Severity level) / Total number of defects

Defect Density

It tells if the application under test is ready to deploy or if it requires more testing. Defects density’s industry standard is 1 Defect/1000 Lines of Code.

But it depends on your code complexity and the development team’s skill. You might get a higher number even with a highly skilled development team because the ratio measures the defect density and code size. That is because highly skilled developers write well-optimized code that might be small in terms of size.

Defect Density = Defect count / Size of the release

What Is Test Effectiveness?

Test Effectiveness helps measure how effectively testing has been done to meet the customer’s requirement. It can be used to judge the impact of the test environment on the product and assess the effect of a specific test environment on the final product. Simply put, test effectiveness is a measure of how effectively testing is performed, and test efficiency measures the efficiency of test processes.

In software testing, test effectiveness depicts the percentage of bugs detected by the testing team and the overall number of bugs found in the software. Using this metric, you can identify whether the tests were adequate and whether the test cases cover the requirement scope. It is an estimate of the defect-capturing capability of a test suite.

If the test effectiveness value is high, the tests can track most bugs, and the test suite will require less maintenance.

How To Measure Test Effectiveness

Measuring test effectiveness is important to assess the quality of your testing efforts and identify areas for improvement. Test effectiveness focuses on the following aspects as well,

• Are the customer requirements met by the system, and to what extent?
• And how much effort is taken to develop and test the application?

The software testing lifecycle aims to identify bugs in the application. But these bugs can be either valid or invalid. Valid bugs should be fixed and retested, whereas invalid bugs can be disregarded.

Test effectiveness is calculated as a percentage of the number of valid defects fixed divided by the sum of the number of bugs injected and bugs that escaped.

As a result, test effectiveness is calculated as follows,

Test Effectiveness = (Number of valid defects fixed / Number of defects injected + Number of defects escaped) * 100

Metrics that cover cost-effectiveness and ROI

Manually testing large applications will require a massive amount of human resources and is not highly effective for bug detection, cost, and time. That is why most companies prefer to automate the testing process. Though automation testing tools are pretty pricey, they are highly effective. But most stakeholders don’t allocate proper resources for testing. You can persuade stakeholders to allocate sufficient money and resources by using certain metrics to calculate cost-effectiveness, which can be highly useful. Further, these metrics help calculate and demonstrate the ROI of Test Automation, providing stakeholders with concrete proof that the investment will be worthwhile in the long run.

You can use the following formulas to evaluate the test ROI,

These metrics will help stakeholders to understand that their investments are bringing in a profit.

Testsigma – An Effective Solution to Achieve a Higher ROI

Test automation plays a significant role in achieving good test efficiency and test effectiveness rates in software testing. The following are some of the ways in which test automation can benefit the testing process:

• Faster and repeated test execution
• Wide test coverage and regression testing
• Consistency
• Test accuracy
• Parallel execution
• Early bug detection and defect reporting
• Resource optimization
• Continuous integration and continuous testing

By leveraging automation testing tools effectively, businesses can streamline their testing process, improve software quality, and achieve effective testing outcomes.

Testsigma is a robust cloud-based low-code automation platform that lets you automate your tests for web, mobile, and desktop apps, and APIs in one place. It makes your testing 5x faster.

Also, you can perform responsive testing, visual testing, cross-browser testing, API testing, UI testing, integration testing, and more in the same place.

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Test Efficiency Vs Test Effectiveness

You must understand the difference between test efficiency and test effectiveness. If not, it might be difficult to ensure 100% test efficiency and test effectiveness.

Test Efficiency	Test Effectiveness
Test efficiency measures how much resources were allocated and how much of those resources were actually utilized for the project.	Test Effectiveness measures the effect of the testing on the software application.
It is internal to the organization	It is not internal to the organization
It is usually measured by dividing the number of test cases executed by the unit of time (per hour).	It is calculated by dividing the total number of defects found in the software by the total number of test cases executed.
Test Efficiency evaluates the quantity of code and testing resources necessary for a program to execute a specific function.	It helps you identify the impact of specific test environments on the software application.

Conclusion

The concepts of test efficiency and test effectiveness play vital roles in software testing. While they are interconnected, they address different aspects of the testing process and contribute to the overall quality of the software being developed.

While test efficiency focuses on optimizing resources, test effectiveness ensures thorough defect detection. By understanding the difference between these concepts and implementing strategies to improve both, organizations can achieve optimal software quality, reduce costs, and gain a competitive edge in the market.

Frequently Asked Questions

What is test design efficiency?

Test design efficiency helps evaluate the design efficiency of the executed test. It is calculated as follows,

Test Design Efficiency = (Number of tests run / Total time)

What is the test efficiency formula?

Efficiency testing refers to the efficiency of code and testing efforts in making a quality product. One way to calculate it is as the ratio of the “number of bugs found by the testing team” to the “number of bugs found in total by the testing team and the users”. Thus,Test Efficiency = (Total number of defects found in unit+integration+system) / (Total number of defects found in unit+integration+system+User acceptance testing)