What are the software quality KPIs that you need to know, to evaluate the quality of a software development process? How does it help us to plan and control the lifecycle of the software development process?

Let’s dive in.

Software quality KPIs help determine the overall quality of a software development process. It reveals the extent, amount, capacity, dimension, and various other attributes of a software process. It also helps in enhancing the effectiveness and efficiency of the software.

In this post, we will look thoroughly into the various metrics to evaluate the quality of software. The software development team and quality assurance team work in coherence to ensure the highest quality standards for software depending on the methodology.

Below listed are top software quality KPIs to determine how well the software meets the functional and non-functional requirements:

Code Quality Metrics

Code quality is an important metric to measure the overall software quality. It signifies how safe, secure, and reliable your codebase is.

Here are five key elements to measure your code for high quality:

Reliability

Reliability analyzes the probability of a system to run without any failure for a specific term of operation. It indicates the total number of defects and software availability.

Usually, the number of defects can be calculated by running a static analysis tool. The software available can be calculated by finding out the mean time between failures (MTBF). Ensure to have a low defect count for developing a reliable codebase.

Maintainability

Maintainability reflects the ease of use in maintaining software. It further looks for the size, consistency, structure, and complexity of the codebase. A maintainable source code depends on factors like testability and understandability.

There is no single metric to ensure software maintainability. Some other metrics like stylistic warnings and Halstead complexity also help enhance the maintainability. Both automation and human reviewers alike are crucial for developing maintainable codebases.

Testability

Testability defines the capability of how well the software aids the testing efforts. It depends on how easily you can handle, observe, isolate, and automate the overall testing process.

Testability is calculated depending on how many test cases you have to find potential faults in the system. Besides, the software size and complexity also have an influence on testability. Applying code-level methods like cyclomatic complexity can help enhance the testability of software.

Portability

Portability calculates the utility of the same software in diverse platforms. In short, it indicates platform independence.

TBH, there isn’t any specific degree of portability. But there are a lot of options to ensure portable code for different platforms. So, it’s better to regularly test code on various platforms, instead of waiting until the development ends. Most testers prefer to set their compiler levels as high as possible. They choose to use at least two compilers for better portability. Maintaining a coding standard also helps with portability.

Reusability

The reusability tells us if existing resources such as code can be used again. Resources with modularity and loose coupling are easier to use.

Reusability is calculated by the total number of independencies. Running a static analyzer is helpful to find these interdependencies.

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Software Testing Metrics

What are software testing metrics? What role does it play in the software development process? It helps project managers plan and runs the software development process in making crucial decisions about process changes. In a nutshell, it helps keep track of the project’s health and monitor team productivity.

Analyzing these metrics helps build soft skills for test engineers and skyrocket their career growth in no time. Of course, this is an added advantage for engineers. Let’s understand them one by one.

1. Derivative Metrics

The derivative metrics highlight the various areas that bear issues in the software testing process. It also guides the team to use concrete steps to enhance the accuracy of the testing.

2. Defect Density

Defect density, another software testing metrics, helps the testing team find the number of defects in software during the software development process. The results then matched with the overall module size reveal if the software is all set for the release. It is the metric that also hints to the team whether it requires more testing for accuracy.

The defect density of any software gets evaluated for a minimum of thousand lines of code, also known as KLOC. Here is its formula.

Defect Density = Defect Count/Size of the Software Module

3. Defect Leakage

Defect leakage is another crucial metric that requires testing by the testing team during the testing process. It allows the software testers to analyze the efficiency of the software testing process before the user acceptance testing (UAT) phase of a product. In some cases, the team of testers fails to detect defects. It gets pointed out by the user, called defect leakage or bug leakage.

Defect Leakage = (Total Defects Seen in UAT/ Total Defects Found Before UAT) x 100

4. Defect Removal Efficiency

The ability of the software development team to remove various defects from the module is defect removal efficiency (DRE). Please note that the process runs before the software release.The number of defects per test type across the various test phases is the DRE. It reveals the efficiency of all the defect removal methods taken up by the test team. In short, it is a resulting parameter to assess the quality and performance of the software.

DRE: Total defects fixed by the development team/ Total defects found at the time of evaluation.

5. Defect Category

It is one of the most crucial metrics for software evaluation in the software development life cycle. The defect category provides some great insights about the software quality attributes like its utility, feasibility, performance, credibility, and much more. In a nutshell, the defect category refers to the defects regarding the quality attributes of the software product. It gets evaluated with the given formula:

Defect Category = Defects associated with a particular category/ Total count of defects

6. Defect Severity Index

The degree of impact a defect has on software development is the defect severity index. Also known as DSI, it offers findings of the product quality under test and helps ascertain the ability of the test team’s efforts. It aids the team in calculating the degree of the negative impact a defect has on the quality and performance of the software.

Defect Severity Index = Sum of (Defect * Severity Level)/ Total Defects

7. Review Efficiency

Review efficiency is a great metric that helps to curtail the pre-delivery defects in a software product. Using this metric helps the team reduce the cost and the efforts required in error rectification. Besides, it helps prevent defect leakage in the testing stages and establishes the test case effectiveness. Here is the formula to find the review efficiency for any software module in a final testing phase.

Review Efficiency (RE) = Total Count of review defects / (Total amount of review defects + Total amount of testing defects) x 100

8. Test Case Effectiveness

This metric intends to tell us the efficiency of the test cases accomplished by the testing team across every testing phase. It helps in the evaluation of the quality of the test cases.

Test Case Effectiveness = (Total detects detected / Count of active test cases) x 100

9. Test Case Productivity

As the name suggests, this metric helps calculate the number of test cases taken by the testers. It also covers the work done by them during the process. Besides, it helps in estimating the test case design productivity. It is also a basic input for measurement and estimation forecasts.Here is the formula to calculate test case productivity:

Test Case Productivity = (Total Test Cases / Work Done For Test Case Preparation)

10. Test Coverage

Test coverage outlines the extent to which the functionality of a software product gets covered. It is one of the crucial metrics that signal the execution of testing operations. It is a factor to conclude the testing process as well. Here is the formula to evaluate test coverage:

Test Coverage = Total Faults Detected / Predicted Defects

Here is another formula to calculate it:

Required Coverage = (Total requirements covered / Total count of requirements) x 100

11. Test Design Coverage

Much like the test coverage, this indicator determines the percentage of test cases coverage out of the total requirements. It helps in calculating the performance coverage of the test cases designed and enhances the test coverage. The metric is usually found by the team along the test design stage and in percentage. Here is the formula for test design coverage:

Test Design Coverage = (Total count of requirements connected to test cases / Total requirement count) x 100

12. Test Execution Coverage

The test execution coverage metric gives us an idea about the total test cases completed and the count of cases left pending. It asserts the testing coverage along with the test execution, with the help of this formula:

Test Execution Coverage = (Total completed test cases or scripts / Total number of test cases or scripts in the pipeline for execution) x 100

13. Test Tracking & Efficiency

The test efficiency is a crucial factor that keeps all the activities of the testing team in line with the desired result. It makes sure the quality attributes of the testing team are efficient. Here are some software testing metrics that help in tracking and efficiency of software testing:

• Passed Test Cases Coverage: It evaluates the percentage of passed test cases.
  (Passed test count / Total count of tests executed) x 100
• Failed Test Case Coverage: It gauges the percentage of all the failed test cases.
  (Failed test count / Total count of test cases failed) x 100
• Test Cases Blocked: It measures the percentage of test cases blocked through the software testing process. (Count of blocked tests / Total number of tests completed) x 100
• Fixed Defects Percentage: This metric helps the team identify the percentage of fixed defects.
  (Fixed Defects / Total reported defects) x 100
• Accepted Defects Percentage: It means to mention the total number of defects acknowledged by the development team. Here is the formula to measure accepted defects percentage:
  (Defects accepted as legit / Total defect reported) x 100
• Defects Rejected Percentage: It is the percentage of defects rejected by the development team under the test track and efficiency process.
  (Total defects ignored by the development team/total reported defects) x 100
• Defects Deferred Percentage: It concludes the percentage of defects delayed by the team for future releases.
  (Defects deferred for future releases / Total defects reported) x 100
• Critical Defects Percentage: It ideates the percentage of critical defects in software.
  (Critical defects / Total reported defects) x 100
• Average Time Taken To Correct Defects: This formula helps team members to calculate the average time taken in the development and testing phases to correct the defects.
  (Total time taken for bug fixes / Total bugs count)

14.  Test Effort Percentage

Test efforts percentage evaluates the pre-testing process estimation versus the actual efforts put in by the testers. It helps to understand the changes and polarities in the testing and estimates connate projects in the coming time. Much like the test efficiency metrics, the test efforts gets calculated with the help of various such metrics:

• Count of Test Run Per Time-Period: It means counting the number of tests executed in a specific time frame.
  (Count of test run / Total time)
• Test Design Efficiency: This metric focuses on finding out the design efficiency of an executed test.
  (Total test run / Total time)
• Bug Find Rate: Another prominent metric used in the test effort percentage is bug find rate. It checks the number of bugs/errors identified by the team in the testing process.
  (Total amount of bugs / Total test hours)
• Bug Count Per Test: It tells us the number of bugs found in every test stage.
  (Total defects count / Total test count)
• Average Test Time For A Bug Fix: After calculating all the above metrics, the team finally looks for the time taken to test a single bug fix.
  (Total time gap between fix and retest for all bugs / Total bugs count)

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15.  Test Effectiveness

Contrary to test efficiency, test effectiveness looks for the bugs and defect ability. It also evaluates the quality of a test set and segregates them from the software product and packages. Additionally, the metric gives the percentage of the variation between the total defects count in the software testing and the count of defects in the software.

Here is the formula to measure Test effectiveness:

Test Effectiveness (TEF) = (Total inserted defects + Total defects spotted / Defects count escaped) x 100

16.  Test Economic Metrics

Many factors contribute to the cost of testing like smart brains, resources, tools, and infrastructure during the software product testing. So, it gets crucial for the team to assess the volume of testing along with the accurate costs in the testing process.

Here are the remaining aspects to calculate the test economic metrics:

• Allocated testing cost.
• Real testing cost.
• A gap in the estimated budget.
• Divergence from the schedule.
• Price per bug fix.
• The price of not testing.
• Test Team Metrics

Eventually, the team defines the test team metrics after working through all the other key performance indicators. This metric helps see if the work allocation follows a uniform distribution among all the test team members. It also checks if there is any need for clarification or extra information about the testing process.

Furthermore, test economic metrics are of great help as it aids in knowledge transfer between the team members and facilitates sharing key project details. It does not point out any individual for any defects or irregularities.

The metric is in the form of graphs and charts with the help of the following aspects:

• Repeated defects get distributed to the team members uniformly along with other details like defects reporting, acceptance, and rejection.
• The open defects get allotted to each testing member for a retest.
• Total count of the test cases resolved by each tester.

Testing software applications often requires working on complex processes over and over. Using test automation framework integration early in the testing lifecycle can help in early defects detection. Plus, it helps save on expensive fixes.

Security Metrics

Security metrics offer great insights and help plan vulnerability management activities. Here the general trend of vulnerability comparison matters more than the value numbers during a software development project.

• Total vulnerabilities caught by regular penetration testing

The metric highlights the degree of exposure to security vulnerabilities. Instead, the value of this KPI should reduce with the project advancement, indicating the maturity of the software security. Rather, increasing KPI value hints at the deployment of software updates in a rush.

• Total known vulnerabilities unresolved

The number of fixed vulnerabilities doesn’t reflect a wholesome picture of your software’s security. It’s better to compare your software solution with the open security loopholes. Keeping track of this KPI helps keep a check on the loopholes and plan the right actions on security enhancement.

• Quantity and intensity of security incidents

This metric prioritizes the most vulnerable incidents that need instant attention in the first place. The criterion behind the intensity ranking depends on how severely an incident can affect the software’s reliability.

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User Satisfaction

Like every other domain, user satisfaction in software development is calculated through surveys. Letting the users rate their experience helps understand the good in the application. It also tells the improvements to be done in the next iteration.

Here are three elements to include in your user satisfaction surveys:

• Matching user expectations on performance.
• Easy to use user interface.
• Stability of software functionality.

Takeaway

Software testing metrics combined with code quality, security metrics, and user satisfaction enhance the software quality. Right from ensuring the accuracy of tests to certifying the product quality, these metrics play a vital role in the software development life cycle. Start implementing these software quality KPIs to identify the bottlenecks and enhance the efficiency of your software quality right away.