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.
Isolate the unit to be tested with an automated stubbing or mocking framework to keep the testing scope small and targeted to the unit under test. Benefits include 1) Simpler test code that’s easier to create, maintain, understand, and debug. 2) Run test cases simpler and faster. 3) Encourages developers to think about logical paths through the code and expected behavior.
Automating unit test execution into CI builds ensures developers receive rapid feedback on code changes that potentially impact the reliability and functionality of the application. Test impact analysis is an accelerator that uses code coverage to efficiently run the optimal suite of test cases that verify code changes prior to committing or merging.
Spend less time meeting industry requirements with unit test automation for safe, secure, and reliable code. Look for solutions that are TÜV SÜD certified for automotive standards ISO 26262, railway standards EN 50128, and functional safety IEC 61508 for all ASIL and SIL levels. Tool Qualification Kits for DO-178B/C are also good to look for.
Unit testing tools help teams that develop enterprise and embedded applications by thoroughly testing code and achieving test passes and code coverage goals. For safety-critical development, unit testing tools account for all coverage types from statement and branch to MC/DC and object code.
Achieving a robust safety net with high code coverage by creating unit tests manually is a long, drawn-out process. Test automation helps take the sting out of creating so many unit tests where developers can focus their attention on testing complex code and backfilling code coverage gaps.
With automated AI assistance, unit testing best practices are more approachable for the entire team. It gives novice unit testers a better understanding of how to write good unit tests. It helps expert unit testers save time and effort by creating meaningful tests, providing valid asserts that test the true functionality of the code.
Give your software developers the right testing tools to increase productivity and speed to market.
Parasoft’s suite of products for unit testing is available for Java and C/C++ programming languages.
When you implement a Parasoft tool, you can be sure that your new code works as expected without
negatively impacting the existing functionality.
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 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.
C/C++test is made for today’s high-velocity Agile DevOps environments. It integrates tightly into your CI/CD pipeline and containerized deployments.
Cut down on labor, costs and expedite time to market by automating compliance verification and validation demands, including reports and audit trail.
Parasoft’s AI/ML solution reviews static analysis findings, then organizes, predicts relevance, and prioritizes code violation findings.
Achieve static code analysis, unit testing, and high code coverage with JUnit to accelerate the delivery of secure and reliable Java applications.
Get a complete view of quality and compliance with aggregated reports and advanced analytics across Parasoft testing solutions.
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 Achieve static code analysis, unit testing, and high code coverage with JUnit to accelerate the delivery of secure and reliable Java applications.
Jtest integrates tightly into your CI/CD pipeline for real-time static analysis, unit testing, and code coverage testing.
Jtest users can easily generate, augment, and reuse unit tests with AI assistance, reducing costs and time.
Jtest provides code coverage compliance and visibility into what code has been tested and how thoroughly.
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.
Reduce the risk of C# or VB.NET development in the Microsoft framework with deep static analysis, security, and coverage for enterprise and embedded applications.
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.
Implement a proactive unit testing practice to drive the success of your projects. Provide your team with concrete policies to make the process scalable and sustainable. Some common sense policies:
Execute a daily, hourly, or continuous integration delivery process with automation for unit and regression testing. Provide each team member with review access for test fails, test passes, and code coverage reports. Provide teams with analytics that measure how much sprint-modified / release-modified code in the codebase has been covered so they have iterative achievable milestones.
When writing unit tests, it’s important to simultaneously develop application code because the two go hand-in-hand. While strict adherence to test-driven development (TDD) is uncommon due to the rigidity of writing tests before code, developers should strive for creating test code as they’re working on features and bug fixes. This ensures logic and edge cases are carefully considered in the moment instead of as an afterthought.
Establish a zero-tolerance policy for unreviewed test fails. Test fails can indicate issues with the test or real regressions in the application. Either way, they should be addressed immediately. Allowing failing tests to linger dilutes the value of unit testing and may lead to real issues getting lost in the noise.
Refactor the tests as needed when the code changes. It’s important to maintain tests, especially if they fail. Tests lose value if they’re not kept up to date when the application changes. Each test failure costs time and money to investigate.
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.
