Software Testing Metrics: Types, Calculation, Examples
Worldwide, development organizations are looking to build high-quality software products and boost the success rate of their Quality Assurance efforts. After all, quality is an important differentiating factor that users look at while choosing a product. Software testing is, therefore, a critical aspect of the development lifecycle. And so are software testing metrics that throw much-needed light on the progress, challenges, and quality of testing.
What Are Software Testing Metrics?
Software testing metrics help measure and monitor test activities. They provide critical insights into testing activities, team productivity, and the system's quality under test, so teams can measure different aspects depending on what they want to track, control, or improve.
In essence, by providing testing teams with critical testing information, metrics help in
- Unearthing challenges and bottlenecks
- Identifying and eliminating inefficient tasks
- Making changes to testing strategies and tools to improve the testing process.
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Why Are Software Testing Metrics Important?
No matter how much effort you put into software testing, unless you can measure the progress, you cannot know what you are doing or what you need to do for better results. Software testing metrics convey a result or a prediction based on a combination of test data. For instance, they can provide information on the success of the testing activity, the time taken to run a set of test cases or even deliver early warning signs of an unfavorable result.
Software testing metrics also provide clear, quantifiable answers to important questions such as:
- What is being tested?
- How much of the software is already tested?
- What is the cost of testing?
- How is the required testing effort?
- What is the number of test cases?
- How long will it take to test?
- How many bugs/defects are found?
- How can they be resolved?
- Can testing be done on time?
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Software Testing Metrics Life Cycle
- Analysis: Identify the most suitable metrics for your testing process.
- Communication: Educate the testing team and stakeholders about the chosen metrics.
- Evaluation: Collect and verify relevant data, then use this data to assess the value of the metrics.
- Reporting: Create a comprehensive report summarizing the findings and distribute it to stakeholders for feedback.
How to Calculate Test Metrics?
| Metric | Description | Formula |
|---|---|---|
| Defect Density | Measures the number of defects relative to the size of the software module. | Defect Density = Total Defects / Size of the Module |
| Test Case Effectiveness | Evaluate the efficiency of test cases in detecting defects. | Test Case Effectiveness = (Defects Detected / Test Cases Run) x 100 |
| Defect Leakage | Quantifies defects missed during testing but found later. | Defect Leakage = (Defects Found Post-Testing / Defects Found Pre-Testing) x 100 |
| Defect Removal Efficiency | Assesses the effectiveness of the testing process in removing defects. | Defect Removal Efficiency = (Defects Removed / Total Defects at Start) x 100 |
| Test Coverage | Indicates the extent to which the software functionalities are tested. | Test Coverage = (Tested Functionalities / Total Functionalities) x 100 |
| Passed Test Cases Percentage | Measures the proportion of test cases that passed. | Passed Test Cases = (Passed Tests / Total Tests Executed) x 100 |
| Failed Test Cases Percentage | Indicates the proportion of failed test cases. | Failed Test Cases = (Failed Tests / Total Tests Executed) x 100 |
| Test Execution Rate | Tracks the speed of the testing process. | Test Execution Rate = (Test Cases Executed / Planned Test Cases) x 100 |
| Defect Age | Measures the time to fix a defect. | Defect Age = Time of Defect Fix – Time of Defect Discovery |
| Rework Effort Ratio | Assesses the effort spent on reworking or correcting defects. | Rework Effort Ratio = (Rework Effort / Total Testing Effort) x 100 |
Examples of Software Test Metrics Calculation
Example 1:
Consider a scenario where you have the following data from test case development:
- Total Test Cases Written: 200
- Total Test Cases Executed: 180
- Passed Test Cases: 100
- Failed Test Cases: 80
Using this data, you can calculate various metrics. For example:
- Percentage of Test Cases Executed: (180 / 200) x 100 = 90%
- Test Case Effectiveness: (Number of Defects Detected / Number of Test Cases Run) x 100 = (10 / 180) x 100 ≈ 5.55%.
Example 2:
Let's take another example for calculating software test metrics:
- Total Number of Defects Identified: 20
- Defects Accepted as Valid by the Development Team: 15
- Defects Deferred for Future Releases: 5
- Defects Fixed: 12
From this data, you can calculate metrics like:
- Fixed Defects Percentage: (12 / 20) x 100 = 60%
- Accepted Defects Percentage: (15 / 20) x 100 = 75%
- Defects Deferred Percentage: (5 / 20) x 100 = 25%
Types of Software Testing Metrics
Since software testing metrics offer quantitative measurement data to estimate the progress, quality, and health of the software testing process, they help teams in making better decisions for future testing activities. By getting their hands on reliable data about the testing process, they help understand the type and scale of improvements needed and effectively plan the next steps.
There are different types of metrics that teams can use for ensuring QA. Let’s look at the top 10 metrics for measuring quality assurance success:
Process Metrics
Process metrics provide important information on the testing process, indicating common bottlenecks and the overall level of process efficiency.
1. Test case effectiveness is a software testing metric that measures how effectively test cases detect problems. It helps in answering how good tests are, assessing if high-value test cases are being run, and determining the bug-finding ability of the test case.
2. Cycle time measures the amount of time it takes to complete the entire length of the testing process. It can be in hours, days, or even weeks. It also delivers insight into passed, failed, blocked, incomplete, and unexecuted test executions for easy absorption of the test run status.
3. Defect fixing time showcases the amount of time it takes for testing teams to remedy a problem – from the time of detection to the time of resolution. It also gives a better idea of how soon they can release the product to the market – under budget and time.
Product Metrics
Product metrics shed vital light on the quality of the product and lead to better testing decisions.
1. Number of defects is a software testing metric that helps test engineers dig deeper into the many aspects of software quality. By having information on the number of defects, teams can determine the quality and efficiency of the software product and implement remediation measures accordingly.
2. Defect severity and cause is another metric that allows testers to see how severe defects are. It also provides insight into their root cause and how they will affect the software’s quality.
3. Passed/failed test case metrics inform testing teams of the number of test cases that have passed. Such insight helps ascertain the functionality, performance, stability, usability, and compatibility of the software under test and the efforts needed to reduce the frequency of failed tests.
Project Metrics
Project metrics provide information on the productivity and efficiency of the team, tools, and the project in general.
1. Test coverage metrics measure the test effort. They provide insight into how much of the product or application is successfully tested. It is a clear indicator of the quality of the test plan and estimates the amount of testing performed, including functional requirements and risk coverage.
2. Rework effort metrics help testing teams calculate the actual rework efforts spent in resolving a defect after product delivery. It also helps tweak the product or process to ensure they don’t recur. Using this metric, teams also get vital insight into the time and cost needed to fix a defect. As a result, they can arrive at an approximate deadline for deployment.
3. Cost of testing metric specifies the overall expenditure of the testing process. Since people, infrastructure, and tools contribute toward the total cost of testing, teams need to know how much they intend to spend and how much they end up spending.
4. Budget/schedule variance is yet another important software testing metric that states the difference between actual cost/schedule and planned cost/schedule. It helps teams improve financial and operational planning, work within budgets, and pursue opportunities that accelerate time-to-test.
Manual Test Metrics: What Are They and How Do They Work?
Manual test metrics involve collecting and analyzing data from manual testing activities. These metrics help in understanding the effectiveness and efficiency of the manual testing process. They include metrics like the total number of test cases, the number of test cases executed, and the number of defects found. These metrics are crucial for assessing the manual testing process thoroughness and identifying areas for improvement.
Choose the Best Software Testing Metrics
Software testing metrics play a massive role in QA. It allows testers, agile teams, and test managers to take their testing to the next level. Constantly measuring the test process across different metrics enables teams to establish a baseline and track progress over the next days, weeks, and months.
While there are hundreds of testing metrics that you can choose from, focusing on key process, product, and project metrics can help you in ensuring that your software product meets necessary functionality, performance, reliability, and security standards and delivers a seamless user experience.
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Suma Ganji
Senior Content Writer
Expertly navigating technical and UX writing, she crafts captivating content that hits the mark every time. With a keen SEO understanding, her work consistently resonates with readers while securing prime online visibility. When the day's work ends, you'll find her immersed in literary escapades in her quaint book house.
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