Whitepaper: End-to-End Testing for IoT Integrity

IoT architectures often create testing challenges for the software team. Fortunately, there’s an effective way to conduct end-to-end testing for IoT system verification.

Ensure the endpoints you leverage in an IoT environment don’t put your brand at risk.

Parasoft End-to-End Testing for Iot Integrity

Download the whitepaper to learn a multi-stage strategy for ensuring the endpoints you leverage enhance your brand.

Here’s what you’ll learn about:
  • Validating endpoints against your development policy
  • Recording and simulating behaviors to expand the scope of your end-to-end testing
  • Validating endpoint security, functionality, and performance against your use cases
  • Managing change and preparing your test environments for the future
  • “Internet of Things” solutions are evolving and testing them requires a comprehensive methodology.
  • Although testing practices and activities are well known, the density and the combination of technologies are changing.
  • In the past, embedded software engineering was positioned apart from other areas of the software development landscape, but this is no longer the case. The entire stack of applications can often function as a single solution.
  • People in charge of system quality must understand the challenges related to low-level embedded testing, as well as the challenges related to service components.
  • Organizations should be equipped with easy-to use, reliable testing solutions that can test a broad array of technologies and help analyze testing results from different sub-components of the solution.
  • Often, end-to-end testing performed at the system level is the first and only choice, mainly because (on the surface) fully assembling the system and testing it seems like the most logical and effective use of QA resources.
  • End-to-end testing should be a part of your QA activities, but relying on it as the primary QA practice leads to late-cycle detection of errors and delays releasing products to market.
  • End-to-end testing is not intended for detecting defects. The system will be able to validate some requirements, but it can’t simulate all types of situations. Building a system that can do this is costly and time-consuming.
  • Components should be isolated and tested early. By shifting testing to the left, organizations can leverage more effective automation to find and fix systemic defects early in the process.

There are two primary challenges associated with decomposing applications into their constituent layers

  1. Designing the solution in a way that is conducive to segmenting it into smaller building blocks with well-defined interfaces
  2. Building automated testing frameworks around these smaller units. It is up to the organization to decide on the level of granularity for testing.

A test plan should include a combination of unit testing, integration testing and end-to-end testing. The proportion of unit tests to integration tests may vary depending on the complexity of the solution. The more complex the solution, the more important unit tests become. As the complexity of the software grows, it becomes more difficult to stimulate high-level interfaces that ensure various paths are executed.

The strategies for isolation depend on the technology and the type of interactions:

  • Isolating the low-level embedded sensor

For more complex cases, use code instrumentation tools, which can automatically stand in place of original definition just before the compilation. Using a code instrumentation tool greatly reduces the effort spent on test asset management.

  • Isolating server components

For simple test cases, use a stub that contains a node.js script to produce standard re­sponses. For more advanced scenarios, a service virtualization tool can allow you to define a response depending on the input pattern. You can also use service virtualization to record actual traffic and replay it to simulate the real operation of a connected system. In some cases, you may want to switch between a real system and virtual asset.

A common grievance amongst testers is the lack of requirements, especially quality requirements that are conducive to crafting applicable tests. Unfortunately, there are no solutions, automated or otherwise, for producing good functional requirements.

If requirements are complete and test cases have been created to cover them, in most cases you’ll gain visibility around the impact of failing test cases.

But you also need a way to test non-functional requirements to understand what happens inside the system as the code is exercised.

  • Is the application secure?
  • Does the application perform reliably?
  • Where is the business risk?

You can answer these questions by implementing a tool to capture code coverage, collect metrics and correlate them with test results to make informed decisions about when to release and the impact of change.

 Automated software quality activities such as testing of requirements, collecting code coverage, unit testing or load testing are not new. They are well-known techniques in software testing, but not necessarily considered when building a “normal” system. In an IoT environment, these techniques must be considered.

About Parasoft

Parasoft helps organizations continuously deliver quality software with its market-proven, integrated suite of automated software testing tools. Supporting the embedded, enterprise, and IoT markets, Parasoft’s technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to web UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. Bringing all this together, Parasoft’s award winning reporting and analytics dashboard delivers a centralized view of quality enabling organizations to deliver with confidence and succeed in today’s most strategic ecosystems and development initiatives — security, safety-critical, Agile, DevOps, and continuous testing.