Software Quality KPIs: A Complete Guide 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.
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.
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.
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.
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.
Software Testing Metrics What are the metrics for software quality? 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.
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 parameter, 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.
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.
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.
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:
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.
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.
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.
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
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:
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