Test Coverage Metrics: What is, Types & Examples

By Mehedi Hasan Shoab  | Apr 04, 2024 | 8 min read
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    Since even the simplest software solution has many moving parts, software developers have made software testing part of their process. But how do you know you’ve thoroughly tested your product? That’s where test coverage metrics come into play. These metrics provide crucial insights that help you measure the efficiency and completeness of your testing effort. They help measure the extent to which you’ve tested and validated your application for seamless functionality.

    What are Test Coverage Metrics

    Test coverage metrics are qualitative measures that ensure every part of a software is thoroughly tested for quality and reliability. They measure how much a software testing suite has covered the application under development. These agile test metrics help software development teams build a superior product with superior performance while meeting user expectations.

    Test coverage metrics offer insights into the efficacy and completeness of your software testing process. Naturally, high test coverage metrics underpin the capacity to deliver a highly functional solution that functions as expected.

    Test Coverage Metrics

    Types of Test Coverage Metrics

    From code coverage metrics such as statement and branch coverage to path and risk coverage, you’re spoiled for choice when choosing test coverage in software testing.

    Statement Coverage

    It’s the most basic test coverage metric and measures the percentage of executable statements in the code executed during testing. It helps identify untested areas of the code that may contain potential defects by marking them as covered or uncovered. If the code contains 100 code statements but your team has only executed 75 statements, your statement coverage would be 75%.

    Branch Coverage

    Branch coverage is more advanced than statement coverage and measures the number of branches (decision points) covered during testing. A branch is an intersection in the code where the program may perform different actions based on a conditional statement. If the test covers all branches, you’re more confident of the code’s correctness. For instance, executing both branches gives you 100% branch coverage if dealing with a simple if-else statement.

    Function Coverage

    It measures how well you’ve tested the functional requirements of an application. Functional coverage helps you test all the required features and functionalities in an app or software. It’ll help you identify gaps or missing functionalities that you must address before releasing an application. Testing all the functions on the code eliminates the risk of overlooking the core functionalities of a system.

    Path Coverage

    Path coverage is a comprehensive metric that measures the percentage of the possible paths in the code tested. It seeks to ensure all possible branches and statement combinations are tested. While achieving 100% path coverage when dealing with a large codebase is impossible, a thorough testing process delivers valuable insights.

    Mutation Coverage

    Mutation coverage tests the efficacy of your test suite by evaluating its capacity to detect code changes. The test entails introducing mutations and running your test suite to check if it’ll detect the changes. Mutation coverage identifies shortcomings in your test suite to help you improve its effectiveness. Your mutation coverage is excellent if it detects a high percentage of the mutations.

    Integration Coverage

    Integration coverage measures how well the interaction between the different modules of a software system has been tested. It’s a measure of your integration testing efforts, which verifies the interactions and interfaces between various parts of the system. Testing the integration points helps ensure the integrated components of your system work as intended. It also helps identify potential issues that may arise when different parts of your products interact.

    Risk Coverage

    Risk coverage measures the capacity of your testing processes to identify potential risks that may impact functionality, quality, and security. It describes the extent to which you’ve identified or mitigated the identified risks through your testing efforts. It entails identifying, analyzing, and prioritizing the risks based on likelihood and severity, then executing test cases to target them. Risk coverage helps minimize the impact of the identified risk on your final product.

    Condition Coverage

    Condition coverage evaluates how well you’ve tested the possible combinations of conditions within a conditional state or a decision point. It measures combinations you’ve tested and expresses them as a percentage. Condition states help software systems make decisions based on logical expressions such as true and false evaluations. A high-condition coverage helps you test all possible decision outcomes and logical paths with your product’s code.

    Test Coverage Metrics in Action

    To better understand how test coverage works, here’s a breakdown of how to measure test coverage when building an online shopping platform.

    Statement Coverage

    A typical shopping application will have codes for different functionalities. The code for calculating the total checkout price may include calculating taxes, applying discounts, and adding shipping costs. If the code for calculating the total price comprises 100 lines and your coverage analysis reports only 70% of the code was executed, you’ll have a statement coverage of 30%, which is low. Some crucial parts of the code, such as tax calculation branches or discount scenarios, may contain unidentified bugs. Increasing the statement coverage to about 90% can ensure seamless feature functionality.

    Branch Coverage

    Branch coverage can help you ensure all possible paths related to shipping options and payment methods are thoroughly tested for correct functionality. For instance, your app may allow shoppers to checkout with PayPal or a credit card. Based on the user’s preference, the system should follow the branch corresponding to their preferred payment method. As such, your team’s testing process should cover both options to ensure full branch coverage. Ensuring seamless decision point coverage improves customer experience since shoppers can pay for purchases using the most convenient method.

    Function Coverage

    With function coverage, you can test the functions responsible for essential tasks such as processing payments. Ideally, an online shopping app would have functions that support various payment methods. You’ll need to design test cases that cover scenarios such as successful processing using a credit card, debit card, or PayPal and verify the correct amount is charged. It should also test handling invalid or declined payment information and ensure the user’s payment confirmation is correctly displayed.

    Path Coverage

    Path coverage helps ensure various execution paths supporting different user scenarios, such as updating cart quantities, adding items, and completing the purchase, are adequately tested. One test case could check the ease of adding items to their shopping cart, and the cart correctly updates the quantity. Other test cases could entail testing to ensure the cart functions properly when a customer adds multiple items, removes an item from the cart, or displays an error message whenever a customer enters an invalid value.

    Path coverage helps identify how well you’ve tested an application along these execution paths to help you provide a robust shopping experience to the end user. High coverage lowers the likelihood of customers experiencing logical or functional issues while on the platform.

    Mutation Coverage

    With mutation coverage, your team will introduce modified code versions for functions responsible for a critical function, such as calculating the total price. That could mean modifying conditional statements, changing arithmetic operators, or altering variable assignments. They’ll then execute the test suite against the mutations. A low coverage score points means your test suite can’t effectively detect faulty codes or unexpected software changes.

    Integration Coverage

    Integration coverage helps ensure the functionality of key features such as payment getaways, inventory management, and user authentication. Inventory management testing could focus on verifying stock availability and item information before displaying it to the users.

    Testing scenarios could evaluate the system’s capacity to detect and report stockouts and overstocks. They should also validate that inventory is correctly updated after every order.

    A high integration coverage means you’ve thoroughly tested the system’s ability to integrate with external systems to ensure flawless execution. It bolsters your capacity to identify compatibility issues, communication problems, and data inconsistencies likely to arise during integration.

    Risk Coverage

    Risk coverage entails testing the platform against potential risks that could impact its security, performance, or device compatibility. Security risks include SQL injection, cross-site scripting (XSS), and insecure authentication mechanisms. The testing efforts could cover penetration testing, encryption, and resilience against common security issues such as brute force attacks and session hijacking.

    Risk coverage evaluates a system’s capacity to handle these real-world threats and mitigating risks relating to poor performance, security breaches, and user experience issues. A high-risk coverage increases the likelihood of delivering a secure, high-performing, and user-friendly solution.

    Condition Coverage

    Condition coverage entails evaluating different conditions that handle functions such as discounting. Condition coverage for discount conditions would mean testing various combinations of conditions. You can test the software to ensure it applies the correct discount whenever the minimum order value is met or only applies discounts to eligible product categories. A high condition coverage means your team has tested the most possible combinations of conditions within these decision points. It boosts your capacity to detect errors and anomalies and deliver a product that provides a seamless shopping experience.

    Best Practices for Utilizing Test Coverage Metrics

    Test coverage metrics underpin your capacity to deliver a superior product to the market while ensuring it functions as expected. Here are some of the best practices that help ensure flawless results:

    • Set clear testing objectives: Project requirements and software complexity are vital considerations when setting testing objectives. What aspects of the software do you wish to evaluate and improve through the test coverage metrics? A laser-targeted approach will help you focus and align your testing efforts with your required quality standards.

    • Prioritize critical areas: Identify core features and functionalities essential to the software’s operation and deliver the most value to the users. Consider features that will be used frequently or are central to customer experience. That’ll help with resource allocation and test scheduling to ensure a quick turnaround.

    • Select the best coverage metrics: Drill down to metrics that provide the most valuable insights. Popular coverage metrics include statement, branch, and path coverage. Pick the metrics most relevant to the software application and testing requirements.

    • Set coverage targets: You can base the targets on project requirements, industry standards, or internal quality objectives. Coverage targets help track progress, identify shortcomings, and prioritize testing efforts.

    • Use a multi-faceted approach: Combining multiple coverage metrics provides a comprehensive view of your testing efforts. Different metrics offer different insights into the quality and completeness of your test coverage. This approach helps identify blind spots or gaps in your testing processes.

    • Leverage technology: Test coverage analysis tools or frameworks provide detailed visualizations, reports, and insights into the covered and uncovered code. They also measure and analyze your test coverage to identify gaps and guide improvements.

    • Use a feedback loop: You can automate your processes and use coverage metrics as a feedback loop to guide your testing efforts. Analyzing the coverage data helps uncover trends, patterns, and areas of improvement. You may then use the information to polish your test plans and prioritize test cases to focus on high-risk areas.

    • Collaborate and communicate: Sharing and discussing test coverage metrics with developers, testers, and project managers ensures everyone’s on the page. Collaboration helps you effectively address coverage gaps and deliver a superior product. Effective communication and cooperation move everyone toward the desired outcome.

    Build Superior Products and Outpace the Competition

    Test coverage metrics are indispensable tools that complement your software testing efforts to help you deliver a superior product. By assessing the thoroughness of your test coverage, you can quickly identify and address potential gaps, hidden defects, and problem areas long before you’ve delivered the product. Your clients can count on your team to deliver quality products that match their business objectives and offer exceptional user experiences.

    At PractiTest, we specialize in helping companies streamline, optimize, and achieve seamless control over their testing processes. Looking to simplify your testing efforts and deliver flawless products every time? Try PractiTest for free!

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    About the author
    Mehedi Hasan Shoab

    Mehedi Hasan Shoab

    Mehedi Hasan Shoab is a freelance writer for software, marketing, and finance companies.

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