Perform static analysis, unit testing, and code coverage to develop high-quality C and C++ code that is robust, safe, secure, and compliant with industry standards.
Unit tests work by isolating code functions and/or procedures in a source file for the purpose of individually testing these small units of code for safety, security, and robustness. To isolate code functions or units of code, developers and testers perform stubbing. A stub may simulate the behavior of existing code or be a temporary substitute for yet-to-be-developed code. Users can monitor stub execution to check against certain expectations, such as the number of calls to a given stub or the sequence of stub calls. Users must define expectations inside test cases, and then verify them after the test case execution is finished.
The functions or units generally include input of various types (char, integer, pointers) and the values may differ for each upon the call to the unit. To test the code unit, users manipulate its input values to help ensure correct functional behavior upon valid input values. However, the unit must ensure robustness, therefore the input of values outside expected ranges, including null values, should be used. This flushes out defects like memory access violations, divide-by-zero scenarios, stack overflow conditions, and other safety, security, and reliability errors.
As unit tests are executed, output values may be collected, and inspected for correctness, and reports stored for audit and or compliance purposes. Many development teams also integrate structural code coverage to expose code that has not been tested. Knowing that each individual unit of code has been tested and is sound eliminates risk and helps ensure the delivery of a quality application. For safety-critical applications, 100% code coverage is commonly performed.
There are three types of unit testing performed by software teams.
The developer or test engineer writes test code to exercise a function or unit of code for correctness.
Developers can rely on a GUI and testing framework for the purpose of simplifying the creation of unit tests, managing the tests, and reusing hundreds to thousands of unit tests for regression testing.
A one-click action creates, scales, and maintains unit tests. AI-enabled unit testing significantly cuts the time and effort required to build a comprehensive and meaningful suite of unit test cases.
Get Unit Testing Done Right: Top Tips for Java Developers
Unit testing is more than just a testing technique. It’s a testing method for exercising individual units of source code that provides an excellent way to demonstrate the correct software behavior.
Unit testing is important because it identifies regressions at the earliest stage of software development, where it is the cheapest and least oppressive to fix. Unit tests are small and each test case tests a small scope of code, thus making it easy and quick to identify the problem when reviewing test fails.
Unit tests use mocking and stubbing to isolate from external dependencies, which means they are simple and fast to execute and deliver feedback to the team quickly. Furthermore, this also makes unit test execution easy to fully automate in a CI build.
There are also less obvious benefits to a unit testing practice. Developers that proactively unit test while writing code give themselves the perspective of looking at the code they’ve written through a different lens. In essence, the act of unit testing can be like an additional code review to ensure the code was written correctly and robustly the first time.
Developers thinking about how the interface to their code will be used by other components, and then writing unit tests for those scenarios, are less likely to overlook unhappy paths that could be exposed in later stages of software testing, or worse, in production.
A well-known study by Capers Jones on the economics of software quality shows the earlier a defect is found in the development cycle, the cheaper it is to fix, which sharply contrasts with exponentially increased costs for findings defects later in the cycle. As a result, there is an ROI for investing in a robust regression suite of unit tests.
The ROI of unit testing can also be felt by the reduced rework that comes from implementing requirements correctly the first time.
Automated unit testing solutions are used in software development to efficiently ensure code safety, security, and reliability. By quickly building and auto-generating robust unit test cases, you can ensure code quality through the execution of test cases in any cross-platform, host, virtual, or hardware target environment. Unit testing features include:
Unit testing is an integral part of software development. Automated testing tools, like those used in systems testing, are highly useful for developers and anyone who runs code.
In embedded development environments, where hardware and software systems must work in sync and comply with exacting functional safety standards, unit testing is extremely useful.
The automated unit testing framework quickly delivers robust regression test suites. This is critical later in the life cycle as software updates, patches, or new requirements are implemented.
By optimizing unit and regression testing with automation, teams save time and gain better coverage.
Collect coverage from unit testing, system testing, manual testing, as well as all other test execution methods used. Parasoft C/C++test supports a range of coverage metrics (Branch, Statement, MC/DC, etc.), which teams can use in native and cross application development.Request Demo
Collect and monitor code coverage during manual or automated functional testing performed on your Java application. Users can send coverage data and test results to merge and correlate for analysis, which provides insights about how well the application is tested and your test quality.Start Free Trial
Realize the best ROI from your unit tests with proven practices to test code. Programmers, whether beginners
or experienced developers, can easily incorporate these best practices into data-driven
testing to improve capabilities for testable production code.
Writing meaningful unit tests is a skill. For teams new to unit testing and experienced teams struggling with the cost of maintaining high code coverage, the best way to get started is to incorporate automated unit testing into your organization. Automated unit and regression testing substantially reduce the effort of test creation, maintenance, and execution.
Observing how the AI configures stubs and mocks to isolate the unit under test or ensures that assertions are in place for expected behavior, helps teams build meaningful unit tests that execute quickly and deliver the safety net to code modification that they’re looking for.
Next, establish a code coverage baseline for your codebase. Code coverage measures how much of the code is exercised by your unit tests.
Collecting and analyzing code coverage metrics is an important aspect of delivering software quality. Once your baseline code coverage is known, business risks from untested functionality can be assessed for you to mitigate with additional testing.
For legacy code projects with insufficient code coverage, it’s important to balance development velocity with risk mitigation. These are active projects currently in production, after all.
Here it’s important to measure overall code coverage and modified code coverage analytics. Modified coverage tells you how much code was covered by your unit tests between a baseline build and target build. This helps you focus on ensuring newly written or modified code has high code coverage, giving you an achievable milestone within each sprint. Modified coverage analytics allow Agile testing teams to use code coverage effectively in the process.
Parasoft unit testing solutions for Java and C/C++ programming languages automate test execution and data collection. Our solutions automatically create unit tests to save time and energy at test creation time. The technology sets up the unit test framework. It instantiates objects and configures mocks for appropriate objects and method calls used by the method under test.
With Parasoft, the mundane work is already done for developers. Not only do we provide unit test creation wizards, but we also provide content to complete the process. This sets our solutions apart from others.
Assertions are typically manually implemented. If mocking frameworks are used, a significant amount of manual coding is required. With Parasoft, real-time context-aware assistance in the developer’s IDE is provided. Automatic unit test creation quickly and efficiently completes the missing content from skeleton unit tests to include mocks, stubs, and assertions.
Get the most from your unit testing tool.
Frequently Asked Questions
Developers and software testers can perform unit testing manually by writing unit test cases that exercise the code in development to ensure lower-level behavior is as expected.
Running unit tests is the isolated execution of pieces of code commonly referred to as functions, procedures, or methods for the purpose of ensuring that these units are robust, bug-free, and function as intended.
Each unit of code, function, or procedure, for example, satisfies or helps satisfy a functional requirement. Unit testing validates the requirement through execution, but it also ensures that the unit is of high quality and bug-free.
Application testing requires more than just unit testing. Unit testing is also referred to by some as white box testing because the developer depends on the visibility into the details of the source code. Another type of testing is black-box testing in which the developer only cares about the functional results, but nothing about the internal workings of the code, interface, or API.
Want to know more about testing fundamentals and testing techniques? Check out these resources for an in-depth unit testing tutorial.