End-to-end IoT Test Automation for Enterprise Deployment

 

 

Automating end-to-end IoT testing

Building IoT systems is a complex task as it involves multiple Software Hardware interfaces and interconnected subsystems. With so many moving parts, it is critical to ensure the stability and performance of your IoT solution with every new software release. In addition, as more and more businesses change their model and increasingly rely on data generated by connected things (e.g., equipment as a service), validating the functionality and performance of the end-to-end IoT solution with every software update is essential. Regression testing in the Internet of Things (IoT) refers to testing the software to ensure that any incremental changes or updates have not caused unintended consequences or bugs. It could include testing the device’s functionality, ensuring interoperability with other systems and devices, and checking for additional exposure to security vulnerabilities.

One of the critical challenges for IoT regression testing is setting up end-to-end IoT test automation. Since IoT subsystems include hardware and mobile apps, it becomes challenging to orchestrate end-to-end test automation. An end-to-end Internet of Things (IoT) test is a type of testing that ensures that all components of an IoT system are working together correctly. This can include hardware devices, communication networks, cloud infrastructure, and applications that use the data generated by the IoT system. An end-to-end IoT test aims to ensure that the system functions correctly and can handle the data flow and processing requirements needed for the intended use case. This type of testing can be critical for ensuring that an IoT system is reliable and performs as expected in real-world conditions.

 

 

This is one of the most common methods of implementing end-to-end IoT testing, basically doing every aspect of testing by hand. E.g., a tester would write a step-by-step method to validate the Mobile App functionality by connecting an actual device and logging screenshots of the Mobile app to confirm the results.

While this approach is reliable and easiest to implement, it requires a lot of manual effort and is quite tedious to execute when the number of test cases is significant. It also introduces Tester’s fatigue and confirmation biases and sometimes may result in faulty execution. On the other hand, manual testing may uncover a never seen scenario that was not expected by test scripts.

While manual testing can not be eliminated entirely, it makes sense to automate the repetitive parts, especially regressions, so that tester can focus their energy on the user experience parts. Here are a couple of approaches for automating your end-to-end IoT testing.

Approach 1. Automate using a Robotic Test Harness

 

One approach to automate IoT regression testing is using a robotic arm or a mechanical harness. A robotic harness, such as Matt assisted by a camera, would be a convenient setup for automated end-to-end testing of IoT devices. The harness would mimic user behavior by clicking physical buttons, rotating knobs, and touching the screen. Advanced harnesses could also plug in charging cables and control lighting to simulate advanced features testings.

Setting up a test harness is, however, time-consuming and complicated. In addition, it requires unique expertise in setting up Robotics and computer vision programming. On the other hand, it is quite an accurate way to mimic a virtual testing environment without a manual tester’s input.

Pros:

• Realistic test inputs generation by mimicking user behavior.
• Embedded firmware could be tested without any modification.
• Ease of automation and regression as tests could run 24x7

Cons:

• Costly to set up. Requires high CAPEX investment and lab infrastructure.
• Requires Robotic and Computer Vision expertise to set up and maintain test cases.
• Not scalable for even more than tens of devices.
• Not able to mimic some use cases like Vehicle driving.
• Maintenance and troubleshooting are relatively higher.

Approach 2: Stateful IoT simulators

Advanced stateful IoT simulators like IoTIFY solve this problem by simulating a virtual device behavior on the cloud. They are designed to be stateful by nature, i.e., the device behavior and attributes are stored in memory, and the device state transition through a predefined state machine. Furthermore, the ability to customize the simulation behavior with Javascript enables them to mimic almost every device’s behavior realistically.