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Essential Approaches to Overcome IoT Automation Testing Challenges

 

IoT application testing is an important part of smart device development. Just like any other system, the IoT systems have to operate seamlessly well in the desired environment during their deployment. Therefore, it requires rigorous testing as they are often deployed in heterogenous application platforms with several infrastructural dependencies. The devices are also mostly found far from any supporting and maintenance systems. Testers have to make multiple levels of tests to assure that the devices perform seamlessly in all circumstances.

IoT automation testing becomes particularly challenging as these devices function separately from central IT networks and generate large volumes of data. The data generated is heterogeneous in nature, whereby they require to be classified carefully to be utilized properly. Such uncertainty in the nature of deployment and data usage leads to a challenging environment for testing IoT applications, such that it explains IoT testing as a service (TaaS) as a viable alternative for companies.

Yet, with recent improvements in the efforts towards test standardizations, better IoT-related technology, advanced device design, and engineering as well as advanced IoT test automation frameworks in the market, these difficulties are becoming less and less of a matter to IoT developers and manufacturers.

 

General IoT testing automation challenges

 

Complexity of usage

Usage of IoT applications across several devices and platforms creates a massive challenge for automating IoT testing. The software and hardware mesh in IoT devices rely on each other to drive their purpose. The software runs analysis through the data gathered by the device hardware. They are run on various device firmware platforms, cloud platforms, and operating systems.

Throughout the testing phase, we test the IoT platforms for several device and platform combinations. Each IoT device holds different capabilities and may perform better in some environments and platforms than others. Therefore, they require to be tested across platforms for effective usage.

In the case of cloud-connected IoT devices, usability tests are meant for cloud platforms such as Azure IoT, IBM Watson, and AWS that connect parts from different IoT value chains.

Performing these tests for all combinations of hardware and software platforms, as well as deploying the devices in various environments is not practical on a functional level. There are limitations to performing tests in real environments where parameters are not predictable.

 

Data volume and heterogeneity

Data flowing in by IoT devices have high volume, velocity, and quality that cannot be included in most device environments. The volume of data created from IoT and connected devices are at such insurmountable levels that companies struggle to efficiently curate and utilize the data for further use. This points to enormous loss of data and compromises in terms of storage.

Fast-moving data is a crucial part of IoT; since its functions are dependent on quick and reliable data exchange. Intermittent connections can also point to the loss of data. Strong network connections, therefore, become support for IoT ventures.

Data coming in from IoT devices is also extremely heterogeneous in nature, creating further challenges in processing it. The incoming data is normally unstructured and needs proper tagging and data cleaning for the end processing.

 

Security and information privacy

Information privacy and security have been a long-standing problem with IoT device data collection. In most circumstances, IoT devices are accumulating and sharing sensitive and private information such as health information or business assets data. It will be too risky to ignore these concerns of privacy.

Since the data produced by IoT devices is huge, this could possibly lead to data leaks. Unauthorized access to data from outside the system is still another threat.

DDOS (Distributed Denial of Service) attacks have led down several internet services in the past by attacking their IoT devices. Vulnerable IoT devices are used to create huge network traffic in order to take down the servers. Such events have made IoT providers to step up their security game.

Several data privacy and security standards in IoT device security testing are assumed to be taken in order to guard IoT data against mishandling and misuse.

 

Real-time data availability

The hardware and software required to interact with each other in real-time despite architectural varieties. The availability of data in real-time defines the success of many IoT operations such as supply chain and MedTech. This relies massively on network capabilities.

The networks that provide IoT data should be able to manage heavy and frequent workloads of information. Network failures and bandwidth issues are far too familiar. This attests to the requirement for testing for network performance across situations to find solutions that can circumvent such variations without compromising reliability.

 

Essential approaches to overcome testing challenges

 

Running only the necessary tests

When testing teams encounter several test situations and unending combinations of tests over platforms, the testing process becomes a never-ending method. In order to determine a reasonable set of tests to perform, teams should recognize user behaviors for every product and consumer category.

Common patterns will notify you which combinations of device and OS to target for automation before jumping onto the less important situations. Targeting every test at once is never a good plan when you keep short delivery cycles as a priority. The most popular combinations can meet a greater percentage of end-users.

However, you cannot ignore the least common combinations altogether. Performing smaller sanity tests on them can get a grasp of those extra combinations.

 

Network virtualization

IoT equipment relies massively on network availability. It is hard to perform network tests without replicating real test environments. The tests are intended to visualize the conditions aforehand and find solutions.

Network tests also require huge efforts and resources from the testing teams. Generally, they build a network with all the several conditions set to go. But the more effective way of network testing is by network simulations and network virtualizations. The situations such as response times, device modes, storage, etc., are examined with such a virtualized network.

Since IoT devices are normally unassisted, reading their states at all times is challenging. For this, the testers must shift over from conventional performance test tools to IoT-specific performance testing and monitoring tools.

 

Regular tests and updates

Irregular updates could possibly open up networks to security threats. Part of automating testing and monitoring is to assure that the software is continually tested, patched, and upgraded as soon as an update is released.

On top of that, the tests should run credential tests and authorize user access. Inactive and an open-ended user accesses directly to mishaps that cost the complete organization. Since IoT devices produce large amounts of data, data leaks can reveal sensitive information. This is not in the best interest of the customer.

Test and verify credentials and passwords while also promoting regular upgrades of applications. Since the data created by IoT devices is huge, this could possibly lead to data leaks. 

 

Gateways and protocol tests

IoT devices have very limited to secure them against threats and attacks. Most devices don’t have an additional layer of security beyond the TCP (Transmission Control Protocol) layer. Hence, the test automation must incorporate testing for secure connections after installing secure gateways.

IoT gateways work as an extra layer of security for safe and secure communication. But the numerous communication rules make it difficult to test. The application-level testing will include testing out the communication protocol that serves best for each use case

IoT sensors can also go out of memory with various system requests. IoT gateways can act as pathways for data exchange that will balance this workload. Testing will recognize the best methodologies for every component.

 

Conclusion

IoT test automation is challenging and difficult to master, but with extensive experience and innovative parts to cloud accolades to the credit, TestUnity supports test automation for IoT testing from merchants all over the world.

We make an IoT test automation framework that would integrate different web and desktop components for the UI.

As a result, the manufacturer was able to decrease testing costs and effort by up to 80%. We also fault proofed the test methods through industry-grade certifications.

 

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