The market of embedded computing has been growing constantly, and this trend is expected to continue in the near future. Notably, embedded systems are key components for the Internet of Things (IoT) and for Cyber Physical Systems (CPSs). In the embedded software industry, secure software development is critical. This is especially true because embedded software often involves vital industries, such as medical devices or automotive solutions.
When we’re talking about medical emergencies or transport, software failures can literally become a matter of life and death. Additionally, the growing complexity of embedded software can come with security costs if you don’t apply the right testing procedures. Software development models, such as the V-Model, play a crucial role in ensuring software quality and security.
This blog will explain how fuzz testing can optimize testing efficiency within the V-model methodology. It will dive into the principles of fuzz testing and its impact at different stages of the V-model testing process.
Contents
- What is V-model testing?
- V-model testing and embedded software: the testing stages
- How does fuzz testing help in each testing stage?
- Discover Code Intelligence and Fuzz Testing
What is V-model testing?
The V-model, sometimes also referred to as the verification and validation model, is a development process that pairs each developmental stage to a corresponding testing phase. It provides developers with a systematic and visual representation of the software development process. The two legs of the V represent the progression of the process, starting with the requirement gathering, followed by design, implementation, testing, and maintenance. The V-model combines a sequential and structured approach, clear traceability, and a strong emphasis on verification and validation.
V-model testing has several practical benefits:
- The model ensures that testing happens alongside development. This parallel structure allows you to identify issues early in the development process, greatly reducing the risk of errors in the implementation phase.
- The V-Model promotes cooperation between the testing and development teams. This collaboration allows you to better understand project requirements, design choices, and testing methodologies, which improves the overall effectiveness and efficiency of the development process.
- Because the V-model incorporates testing operations at every level of the development process, quality insurance is improved.
Would you like to find out more about V-model testing? Be sure to read our detailed guide ‘The V-model and its role in testing embedded software.’
V-model testing and embedded software: the testing stages
In the world of embedded software development, rigorous testing is an absolute must. Proper and thorough testing methods ensure maximum functionality and security. Fuzz testing is an incredibly useful ally if you want to expose vulnerabilities that traditional testing methods may miss. Different testing stages, from unit testing to system-to-system testing, give you the opportunity to identify potential issues at various stages of the development process. Time to look at the various testing stages and the major differences between them.
Unit testing stage
A software application consists of different elements and components. During the unit testing stage, you test each component in isolation. The main goal? Ensuring that each small piece of code works as anticipated and catching bugs in the early phases of the development process. This allows you to resolve issues well before other components of the application or software system are affected.
Integration testing stage
A software system is more than just the sum of its parts. The different units of the application have to be able to cooperate seamlessly, working towards a mutual goal and guaranteeing excellent functionality. In the integration testing stage, you combine the individual units and make sure that all the different modules or components work together correctly, allowing you to spot and solve possible integration issues in a timely fashion.
System testing stage
System testing goes one step further and focuses on testing the embedded system as a whole. In this stage, you verify that the complete software package meets the specified requirements. You can establish if all the components of the solution function properly and to their full potential in a real-world environment.
Acceptance testing stage
The acceptance testing stage is the final leg of the V-model testing journey. It verifies if the system fits the end-user’s needs, wishes and business requirements. Acceptance testing is the stage before the actual release and ensures that the software is fit and ready for release into a real-world working environment.
How does fuzz testing help in each testing stage?
But what role does fuzz testing play in these different testing stages? Although fuzzing can’t help you in the acceptance testing phase, the method can definitely be of great value in the other three stages of V-model testing.
Unit testing and fuzzing
The earlier you start security testing, the faster and cheaper it is for you to fix bugs. So, it’s beneficial for you and your company to start fuzzing at the earliest testing stages.
As you might know, there are two types of tests — positive ("test to pass") and negative tests ("test to fail"). Positive testing verifies that a particular functionality or feature behaves as expected when provided with valid input or when the system is in an expected state. Negative testing validates how the software handles unexpected or invalid inputs, exceptional conditions, and error scenarios. By intentionally providing invalid or unexpected input, these tests aim to uncover potential vulnerabilities, weaknesses, or bugs in the software.
Fuzz testing is a form of negative testing as it investigates how a program should definitely not behave, by automatically generating a ton of invalid inputs and seeing if any of them will trigger undesired behavior. So, you can delegate negative testing to fuzz testing, which would widen the range of scenarios automatically and check thousands of test cases in minutes, while your developers can focus more on positive cases in unit testing and free some time to develop new features.
If your software is hardware-dependent, fuzzing can help with mocking these hardware dependencies. Mock testing is a technique during which the behavior of real objects is simulated through software. Generally, mock testing is done with hardware-dependent functions returning static values. Enhancing such an approach to generate return values based on fuzz data can incorporate runtime context, i.e., information about a system's behavior given specific test inputs. This way, you can test for positive and negative criteria, i.e., unexpected inputs (How does the program behave if values are fed in a different order than expected? How does it behave if no values are sent at all?). More on mocking hardware dependencies can be found here.
Integration/ system testing and fuzzing
Integration and system testing jointly ensure that both the individual modules and the entire system function correctly. When it comes to embedded systems, integration and system testing usually involve hardware-in-the-loop, meaning you are testing the system with the hardware and have both the software and hardware under test.
Hardware-in-the-loop (HiL) testing is essential for validating embedded systems but comes with many challenges. Identifying bugs through HiL testing is time-consuming, delaying feedback and fixes. The high cost of equipment and maintenance creates financial hurdles, while setting up HiL environments is complex and requires careful integration. Scaling HiL for large projects is also resource-intensive and often impractical due to the need for duplicate hardware. That’s why many companies turn to software-in-the-loop testing, when code is tested and validated in a simulation environment in order to early and cost-effectively catch bugs and improve the quality of the code.
Fuzz testing supports this goal by enabling software-in-the-loop (SiL) testing. For example, in the automotive industry, companies can benefit from the AUTOSAR simulator by Code Intelligence and start catching critical bugs and vulnerabilities in SiL at the system level. This testing method is more cost-effective than hardware-in-the-loop (HiL) testing, allowing you to catch issues earlier in the development process.
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Do you want to learn more about testing embedded systems? Then be sure to download the Embedded Software Security Testing Guide to learn more about the top 7 challenges of embedded testing, how to overcome them, and discover the best practices that will help you find the right testing methodology for your needs.
Do you want to learn more about testing embedded systems? Then be sure to download the Embedded Software Security Testing Guide to learn more about the top 7 challenges of embedded testing, how to overcome them, and discover the best practices that will help you find the right testing methodology for your needs.
Discover Code Intelligence and Fuzz Testing
Would you like to discover the power and benefits of fuzz testing and team up with a partner who can provide you with all the necessary expertise and experience? Book a demo to discuss how your testing strategy can benefit from fuzzing.