Testing is an indispensable part of SDLC as you can’t release any software without a thumbs up from the quality testing team. But how can you be confident that the tests you’re running are accomplishing their goals? That’s where the test effectiveness and efficiency test comes into play.
Test effectiveness evaluates the impact of the test environment on the AUT while the efficiency of test operations is determined by test efficiency.
Both of these strategies are crucial for assessing the overall testing efforts of your company. The significance of testing is obvious, yet obtaining industry-standard testing can be rather costly. Testing is estimated to cost up to 25% of the entire cost of a project.
Given the high expense of testing, it is critical that your tests be efficient. For ensuring your test’s effectiveness and efficiency, first, you need to understand how to distinguish between these two terms.
Today, we will discuss Test Efficiency VS Test Effectiveness and learn the best metrics to evaluate both efficiency and effectiveness of your testing efforts.
- What Is Test Efficiency?
- How To Determine Test Efficiency
- Metrics That Cover Test Case Efficiency
- Metrics That Measure Test Coverage
- Defect-Oriented Metrics For Test Efficiency
- What Is Test Effectiveness?
- How To Measure Test Effectiveness
- Test Efficiency VS Test Effectiveness
- Frequently Asked Questions
- Wrapping Up
What Is Test Efficiency?
Test Efficiency is a measure of how much resources were allocated for testing and how much of these resources were utilized. It is essentially the number of test cases executed divided by unit of time.
Test efficiency in software testing is a method of measuring how well project resources were used to fulfill the organizational goal. Essentially, test efficiency compares the resources allocated for testing to the resources actually used throughout testing.
This aids the company in planning resources for future projects with minimal cost and effort. Moreover, as an efficiency test evaluates how well a testing investment has been working, it becomes vital when an organization wants to outsource its testing efforts.
How To Determine Test Efficiency
Whether you test your applications manually or automatically, the testing process requires a significant amount of time, money, and resources. Hence, it is critical to ensure that all tests executed are as efficient as possible.
Now that we’ve established the need for efficiency testing in software deployment, it’s time to learn how to calculate test efficiency. Several variables must be examined when deciding whether a test suite is efficient, including the cost-efficiency of the tests, their success in discovering and eliminating problems, the scope of the test, and so on.
The most important requirement, however, is whether the results of the tests would be enough to provide confirmation of a ready-to-ship product.
Identifying the best methods for determining test efficiency is critical because using the optimum metric can assist provide high-quality, bug-free software to the client. The following are the two most popular techniques for measuring test efficacy:
Metric-based Approach:
A metric-based approach aids in determining how to improve testing procedures when they are not progressing as intended. The generated metrics must be appropriately assessed because they aid in estimating the testing process’s efficiency.
The most widely used metric is the overall number of defects discovered during various stages of testing. Some efficiency formulas for test efficiency measurement are:
Test efficiency = (total number of defects found in unit+integration+system) / (total number of defects found in unit+integration+system+User acceptance testing)Testing Efficiency = (No. of defects Resolved / Total No. of Defects Submitted)* 100
Metrics such as rejected bugs, missed bugs, test coverage, and requirement coverage can be used to evaluate test efficiency when the overall number of bugs is considered.
Expert-based approach:
It is important to remember that metrics that work best for one project may not produce the same outcomes for another. As a result, skilled QA testers must choose the optimal metrics for your project based on their knowledge and analysis. Therefore, in this approach, test efficiency is measured by QA professionals based on their previous project experience.
Metrics That Cover Test Case Efficiency
The ultimate metric for measuring test efficiency is hard to find. Especially, since each project has different requirements. But evaluating test case efficiency is an effective measure of test efficiency. We can calculate this using two efficiency formulas as described below:
1. Total Defect Containment Efficiency
You can find out how efficient your test suite has been in identifying bugs with this ratio. A higher ratio means your test processes worked efficiently and close to zero bugs were found after release. But a lower ratio means your test suite needs drastic improvement. Also, a low ratio means defects are left in the production stage which can be costly to fix after release. You can measure total defect containment efficiency by using the formula: Total Defect Containment Efficiency = (Defects found in test stage/ Defects found in test stage + Defects found after release) * 100
2. Test Passed Percentage
This is more of a summary of your testing progress. It becomes more useful when combined with the defect escape ratio which is another metric used for test efficiency evaluation. If you find that both the defect escape ratio and test passed percentage are high, it means your test suite has failed to identify crucial requirements.
Also, it means your tests are not efficient enough to detect the bugs and you must improve them immediately. Test Passed Percentage % = ( Number of tests passed/ Total number of test ) * 100
Metrics That Measure Test Coverage
Test coverage metric is used to identify the scope of the test suite as in how much of the application requirements are covered by the current test plans. In an ideal world, your test plan would cover every test case, but in reality, that is not possible.
Because testing every single thing for large or complex projects would take immense time and resources. As a result, you must first identify the high-risk features, critical business requirements, functionalities or modules where defects frequently occurred during production, and so on.
Then make sure your test plan covers these areas. There are many test coverage metrics for determining test efficiency. Some of them are discussed below:
Requirements Coverage
This ratio shows how much of the customer & stakeholder requirements have been covered by your test suite. You can calculate this using the formula described below: Requirement Coverage = ( Number of requirements covered / Total number of requirements) * 100
Functional Coverage
This inquires about how much of the functional requirements have been covered by the test suite. Functional coverage simply determines whether all the important functions were tested by your test suite. It can be measured by the formula: Functional Coverage = (Number of functional requirements invoked by test plan/ Total functional requirements) * 100
Product Coverage
This metric depicts the coverage of the test in terms of the quantity of products on which the application has been tested on. A web app, for example, has to be tested on a variety of operating systems such as Windows, Linux, Android, and iOS to ensure that the program runs efficiently on a wide range of platforms.
Test Execution Coverage
This is the ratio of test cases executed compared to the total number of test cases. It helps to learn how much of the essential test cases have been completed thus far. It can be calculated as Test Execution Coverage = (Number of tests run / Number of tests to be run) * 100
Defect-Oriented Metrics For Test Efficiency
Defect-oriented metrics classify defects based on their type, severity, or cause of origin. The most popular defect metrics are defect severity and defect density index.
Defect Severity Index
This metric evaluates the impact a defect has on a function or component of the application you are testing. Additionally, DSI informs you about the quality of the software being tested. It can also help you in evaluating the testing team’s efforts. Defect Density Index = (Summation of Defect * Severity level) / Total number of defects
Defect Density
Defect density can tell us whether the product under test is ready for deployment or if it needs to be tested more. The industry standard for defect density is 1 defect/ 1000 LOC. However, this depends on the complexity of your code and the developer team’s skill level.
As this ratio measures the density of defects and code size, you may get a higher number even with a skilled development team. Because experienced coders write highly optimized code that may be smaller in size and thus generate high defect density.
Defect Density = Defect count/Size of the release
What Is Test Effectiveness?
Software Test Effectiveness is a measure to judge the effect of the test environment on the application. Additionally, it can be defined as the measure of how effectively testing is executed. This metric also evaluates the effects of a specific test environment on the final software.
Test effectiveness = Number of defects found divided by number of test cases executed.
Test effectiveness in software testing portrays the percentage of number of bugs identified by the testing team and number of overall bugs found in the software. We can identify if our tests were good enough and if the test cases cover the entire requirement scope with test effectiveness.
It is basically an assessment of the defect capturing ability of a test suite. If the test effectiveness is high, it means the tests are capable of tracking most of the bugs and the overall test suite will require less maintenance.
How To Measure Test Effectiveness
Software Test Effectiveness covers three aspects: How much the customer’s requirements are satisfied by the system. How well the customer specifications are achieved by the system. How much effort is put into developing the system. The goal of the software testing life cycle is to identify software bugs.
These defects can either be valid or invalid. Valid defects must be rectified and retested, whereas invalid defects must be closed off or disregarded.
As a result, test effectiveness is measured as a percentage of the number of legitimate or valid defects fixed in the application divided by the summation of the number of bugs injected and bugs that escaped.
Test Effectiveness = (number of valid defects fixed/number of defects injected + number of defects escaped) * 100
Metrics That Cover Cost-effectiveness And ROI
Testing large applications manually requires a huge amount of manpower and even then is prone to defects after release. In such cases, automation testing needs to be employed. However, automation testing tools are quite expensive and stakeholders almost never allocate enough resources for testing.
To convince stakeholders of the need for sufficient money and resource allocation, metrics that evaluate cost-effectiveness can be highly useful. Also, these metrics can ensure the stakeholders that Return on Investment (ROI) for the resource allocated to the test team is worthwhile.
ROI and cost-effectiveness can be measured using several formulas and we’ve discussed some of the most used ones below:
Manual Execution Time = (Test implementation time x Number of test cases * Period of ROI) / 8Automated Test Script Execution Time = (Automated test execution time required per test x Number of automated test cases x Period of ROI) / 18Automated Test Maintenance time = (Maintenance time x Period of ROI) / 8
These metrics ensure the stakeholders that their investments are bringing profit and assure the QA lead that the test suites executed are effective.
Test Efficiency VS Test Effectiveness
As a QA manager or a tester, it is a must for you to understand the difference between Test Efficiency Vs Test Effectiveness. Otherwise, you won’t be able to ensure 100% efficiency and effectiveness of your test suite. First of all, test efficiency is internal to the organization concerning how much resources were consumed and how much of those resources were actually utilized.
Software Test Efficiency is the number of test cases executed divided by the unit of time (generally per hour). On the other hand, Software Test Effectiveness judges the Effect of the test environment on the application. It measures the customer’s goal achievement with the delivered product.
So, it is not internal to the organization. Also, Test Efficiency tests the amount of code and testing resources required by a program to perform a particular function while Test effectiveness identifies the impact of specific test environments on the application.
Test efficiency is generally calculated by dividing the total number of test cases run by the unit of time. But test effectiveness is measured by dividing the total number of defects found in the application by the total number of test cases executed.
Test effectiveness is how effectively your testing team has conducted the test suite according to the STLC in order to meet the customer’s requirements. Customer satisfaction or requirement fulfillment plays a crucial role in measuring test effectiveness.
But test efficiency doesn’t concern the customers or stakeholders. It only tests if the resources allocated were used properly to understand if the preliminary test plan was accurate.
Test efficiency helps in minimizing human and machine costs in testing while test effectiveness allows ensuring the final product is in accordance with the client’s needs.
Frequently Asked Questions
1. What Does Efficiency Metric Mean?
Answer: Efficiency metrics are methods for evaluating an organization’s ability in managing its resources effectively.
2. Can ROI Metrics Be Used For Measuring Manual Testing Effectiveness?
Answer: Yes, you can use ROI and cost-effectiveness metrics for evaluating the effectiveness of manual tests. Even though it’s most commonly used for automation tests, you can use it for manual test suites by replacing the number of automated test cases with manual test cases.
3. How To Calculate The Defect Gap Metric?
Answer: Defect gap metric measures the development team’s ability to fix valid defects reported by the test team. You can calculate it using the formula: Defect Gap = ( Number of valid bugs fixed / Total number of valid bugs reported) * 100
Wrapping Up
Test efficiency and effectiveness are critical factors in deciding if the software is ready for deployment as well as determining its market worth. The greater the test efficiency, the higher the test effectiveness.
100% test efficiency establishes the fact that your testing team is top-notch in what they do while 100% test effectiveness ensures the customers that your product and organization are trustworthy. Even though it might sound impossible, you should always strive for 100% test efficiency and effectiveness.
We have discussed all that you need to know about test efficiency vs test effectiveness. Now, it’s time for you to choose the metrics suitable for your project and evaluate your test suite’s efficiency and effectiveness.
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