Shifting the testing practices to the left of the development lifecycle and integrating them throughout the development value chain makes it possible to release high-quality digital applications. A true testing integration is able to track and improve the required testing metrics and gain valuable insights to make fast and confident decisions.
In this article, we are bringing top 15 software testing metrics that every software engineering team should track to keep a tight check on their progress. If these metrics are not improving and you are seeking some help, reach out to us at marketing@enhops.com
Let’s get started –
3. Defects per Requirement (DPR)
11. Defects per Software Change (DPC)
12. Defect Distribution over Time
1. Escaped Bugs
An escaped bug is a defect or issue that could not be caught into the testing process and slipped into production. Sometimes, this can lead to hampered customer experience or more serious business issues. Usually, this happens due to inadequate test coverage or absence of effective test cases. Other reasons that can lead to escaped bugs are no time to test, ineffective continuous testing strategy, and lack of skilled manpower.
Some tips that can help in preventing escaped bugs are writing thorough test cases to ensure adequate coverage, implementing variety of testing techniques – unit testing, integration testing, and system testing. It is also important to test the software on a variety of devices and browsers using testers from different backgrounds and skill levels. Employing new age testing methods like accessibility testing, agile testing and using an advanced bug tracking system also helps in keeping track of all bugs and resolving them before they hit the release.
2. Test Coverage
Test Coverage measures to what extent test cases written can test the software application’s source code. It is calculated by dividing the number of lines of code executed by the test cases to the total number of lines of code in the program.
For teams that release high business value software frequently, test coverage plays a significant impact on releases. A low-test coverage usually means chances of more defects slipping into production while a high-test coverage helps in releasing high-quality digital applications. Low test coverage can also lead to website or application crashes, data corruption, and security vulnerabilities.
At Enhops, we ensure more than 95% of test coverages for all our engagements by
- Having a team of test specialists writing test cases that cover all functionalities of the software.
- Implementing right test coverage tools help in maintaining the coding standards, tracking the test execution percentage, moving the reusable test cases under regression suite, and adding any additional tests.
- Have an in-depth understanding of the application and set target test coverage goals for each sprint.
- Code refactoring to improve the code readability and testability.
- Achieve as much as automation as possible.
- Integrate testing thoroughly in CI-CD pipelines.
3. Defects per Requirement (DPR)
Defects per requirement measures how many defects are found per requirement. It is calculated by dividing the total number of defects found by the total number of requirements. A high DPR is an indication of not so well-tested software or application. With the unclear requirements, it can be difficult to test the software and find defects. With complex software and changing requirements too, there are high chances of increasing DPR.
As the testing and software development are changing, new age practices like Requirements ambiguity analysis, CI-CD integration, Automated Testing, Shift Left Testing, and Peer Development & Testing can help in reducing the DPR ratio.
4. Test Efforts
Test efforts metric is used to calculate the amount of time and resources spent in testing a decided application or module. It is usually calculated by dividing the total number of hours spent in testing by the total number of defects found. While this is a quantitative measure, the productivity of testing resources must be calculated too to understand the real test efforts.
Measuring test efforts help in improving the effectiveness and efficiency of the testing process. It also throws light on how testing resources can be utilized effectively.
To optimize test efforts, it is very important to engage with testing specialists and have a testing strategy and plan in place. Based on the applications and current organizational skillsets, it is important to start practices like test automation, continuous testing and DevTestOps.
5. Time to Test
Time to test is a leading software metric to determine the exact amount of time taken to test a piece of software. It is usually determined by dividing the total testing time by the number of defects found.
To improve time to test metric, employing test automation is the most effective and highly suggested way. Know more about our test automation services.
6. Test Cost
Test Cost is a software testing metric that ensures that software testing teams are tracking and measuring the financial cost of testing. Test cost is calculated by adding up the costs of all the activities involved in testing such as testing engineers, testing tools and test environments.
To optimize testing costs, it is important to understand the current testing costs and identify areas where testing costs can be saved. This gives teams chance to outsource repetitive and manual tasks to automation and free up test engineers for more productive tasks like accessibility testing or exploratory testing.
While cost optimization is one of the agenda for most of the software development and engineering teams, it is important to understand that the one-time costs incurred in test automation and establishing testing teams can help in releasing quality software and directly impact bottom line.
Partner with cost-effective
test automation service provider
7. Cost per Bug Fix
The cost per bug fix is a software testing metric measures the financial cost of fixing a bug. The more late a big is discovered in the development lifecycle, the higher are the costs associated. Cost per bug fix is calculated by dividing the total cost of fixing bugs by the number of bugs fixed.
The cost of fixing a bug depends on number of factors like severity of the bug, development lifecycle, skillsets of testing teams, and tools and resources available to the development team.
In large testing teams, cost per bug fix can go high when bugs keep on going undetected. It is advisable to identify bugs at early stage to avoid adding up more financial costs. Few ways of reducing cost per bug fix are investing in test automation practices, building testing function in an organization, and using a risk-based testing approach.
8. Bugs Found versus Planned
This metric measures how many bugs were found to how many bugs were planned to be found. Usually with the right test automation plan and strategy, it is possible for teams to create a balance between bugs found and bugs planned.
If the bugs planned versus bugs found are on same range, the test automation and testing practices are working well, but if there’s a huge difference, it requires adopting a well-defined testing framework and strategy.
9. Defect Density
Defect Density refers as the number of confirmed defects detected in the software application or the module developed. It is counted as per thousand lines of code known as KLOC. Defect Density is crucial in determining whether the software application or piece of code is ready to be pushed into production.
Measuring defect density helps project managers and product owners in deciding if the software is fit for production. It also helps in comparing various software components and identifying the areas that requires more efforts from testers. This metric can often unveil the best software application module that can be put into automated testing. Curious to know how? Talk to us at marketing@enhops.com
Don't let defects ruin your software releases. Get in touch with us to understand how our Test Automation Practices can prevent defects before they happen.
10. Test Execution Status
This metric measures how many test cases are being executed successfully. This metric is important to understand how testing cycle is progressing and in how much time all test cases would be executed. This information can be used to track progress over time and to identify any areas where the testing process is falling behind.
To achieve 100% test execution status, testers must prioritize testing requirements based on criticality and severity of the defects. It is imperative to manage the defects using a defect tracking and management system, integrate all your unit, system, and integration tests across builds, and focus on creating test data using business and application logic. Executing crucial business cases across different browsers and run less crucial business cases on a single browser.
11. Defects per Software Change (DPC)
Defects per software change (DPC) is a metric that measures the number of defects found in a software system per change made. It is measured by dividing the number of defects found by the number of changes made.
Defects per Software Change (DPC) helps testing teams in identifying high defects areas, measuring and tracking the effectiveness of their testing process and development changes, and communicate about the software quality to stakeholders.
DPC can be reduced by using Test and Behavior Driven Developments. BDD testing ensures better collaboration between business and QA stakeholders and makes sure that the poorly defined requirements are resolved at an early stage. Test Driven Development encourages writing tests even before the development so the code is written to pass those tests and quality is being integrated from day 0. Another process that must be adopted is automated regression testing to find defects in pre-production environment due to code changes.
12. Defect Distribution over Time
Defect distribution over time is a metric that measures how many and what kind of defects are found in software being tested over a period. This metric is helpful in measuring the effectiveness of new testing processes or tools implemented.
Analyzing defect distribution over period can help in understanding the defect types and how they are distributed. This helps testing teams in implementing coercive actions to remediate those issues.
13. Defect Leakage
This is one of the most important metrics that measures how many defects are being released into the production. The higher the defect leakage, the lower the efficient testing processes are.
Some of the new-age methods that help in reducing defect leakages are Test Automation and Quality Engineering methods. Quality engineering focuses on test automation, using AI-ML tools for outsourcing mundane tasks in testing, and using testing activities related data to bring in innovation and continuous improvement. Test automation can free up testers to focus on more complex and strategic testing tasks, improve test coverage, and reduce human error.
Engineering teams can significantly reduce the number of defects that leaked into production by following best practices like creating and maintaining a comprehensive test strategy and using variety of test automation techniques. It is also important to analyze results and trends to foster innovation and continuous improvement.
14. Test Case Productivity
Test case productivity measures the number of test cases that are created and executed per unit of time. It is calculated by dividing the number of test cases by the time spent on creating and executing the test cases.
Test automation tools can help in improving the overall process by automating the creation and execution of test cases. This improves the test case productivity by making processes repeatable and less error-free.
15. Test Review Efficiency
This software testing metric measures the percentage of test cases that are reviewed and approved on time. It is calculated by dividing the number of test cases that are reviewed and approved on time by the total number of test cases that need to be reviewed.
Test review efficiency helps in understanding the quality of tests before their execution. They help in identifying any potential defects in the test cases before their execution.
Organizations implementing test automation practices, DevTestOps, DevOps must measure their after before of test review efficiency to understand if they are improving the testing process or not.
At Enhops, we work with our clients and before the actual engagement begins, we help them map their current processes and testing maturity levels. After the actual engagement, we help them understand how the mature test automation methods has improved their testing efficiency and overall delivery processes. If you wish to assess your current testing processes, write to us – marketing@enhops.com
Software Testing Metrics: A Key to Quality
It’s a world of data and to continuously improve and innovate, its essential to track right metrics. For Software Testing, metrics are essential to improve the overall efficiency and effectiveness of tools and processes. These metrics uncover the gaps and identify areas for improvements to make right business decisions about where and how to allocate more testing resources.
We have talked about some of the most important metrics in our above blog post. Testing teams can use these metrics to benchmark their performance and communicate the importance of testing process to other stakeholders.