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Mobile apps are ubiquitous. With the growing dependency on smartphones, mobile applications have integrated themselves into the digital communication fabric much deeper as essential tools. Interestingly, these apps have transformed how we communicate, work, and exist in a digital environment while offering us “compelling multi-experiences” through immersive devices such as smartwatches, smartphones, and voice-driven devices.
However, as mobile applications become more sophisticated and essential to our lives, the need for high-quality apps with rapid updates and minimal issues has skyrocketed. This brings next-generation mobile automation (NGMA) into the realm. To build compelling multi-experience applications, businesses must embrace NGMA. This groundbreaking approach addresses these needs by using advanced technologies and streamlining mobile app testing, deployment, and maintenance.
What is Next-Generation Mobile Automation?
Next-generation mobile automation is an advanced process of testing mobile applications. It is a leap forward from conventional approaches of manual mobile application testing. It relies on up-to-date technologies like Artificial Intelligence (AI), Machine Learning (ML), and superior complex analytics.
NGMA marks a shift from traditional manual testing methods towards a more intelligent, automated, and data-driven testing paradigm with several advantages leading organizations to deliver secure, seamless mobile experiences. Additionally, it allows organizations to
Critical benefits of Next-Generation mobile automation:
NGMA redefines the traditional approaches towards mobile app development and testing, enabling businesses to unlock significant business improvement in numerous ways as follows:
1. Enhanced test coverage and efficiency:
In NGMA, test cases are generated automatically, and only a subset is selected. This speeds up the testing process and covers a wider range of scenarios than traditional testing.
The integrated approach takes time and guarantees the effective exercise of all the applications, enhancing the quality and reliability of the application in question.
2. Intelligent adaptation to change:
In particular, traditional testing approaches can be quite ineffective and slow in matching the typical rapidly growing rates of technology, platforms, and devices.
NGMA, on the other hand, incorporates continuous feedback and processing, as well as machine learning methodologies, which makes this system capable of learning its operational conditions and responding to these demands and changes in real-time.
This allows the testing strategies to remain pertinent and practical, particularly with new platforms, gadgets, and operating systems.
3. Visual validation and image-based testing:
In addition to image recognition by humans, the NGMA framework also contains enhanced computer vision that provides sufficient check and balance to image checking through the use of advanced image-based testing techniques.
This capability becomes incredibly useful in validating the UI and comparing experiences across multiple devices and screen sizes. It also quickly identifies visual errors and discrepancies that may otherwise remain undetected in functional tests.
4. Performance testing and optimization:
NGMA can achieve improved optimization results by enabling teams to perform extensive performance testing using an analytics engine and real-world data gathered from users.
This encompasses discovering and fixing various performance issues, defining ways to allocate resources efficiently, and performing applications reliably and well even when the required throughput is high.
Next-Generation Mobile Automation: Common application areas and prominent use cases
1. AI-enhanced testing:
This aspect of the framework represents a significant shift from traditional, static testing methods to a more dynamic, intelligent approach. AI algorithms, particularly machine learning models, are employed to analyze patterns in test results, user behaviors, and application performance.
The AI component can:
- Automatically generate test cases based on application usage patterns
- Prioritize tests based on risk assessment and historical data
- Identify and adapt to changes in the application's UI or functionality
- Predict potential failure points and focus testing efforts accordingly
For example, if the AI detects that a particular feature is causing frequent failures, it can automatically increase the test coverage for that area. Similarly, if certain test cases consistently pass, the AI might reduce their frequency to optimize testing time.
This adaptive approach ensures that testing remains relevant and efficient as the application evolves, significantly reducing the manual effort required to maintain test suites.
2. Secure data management with Blockchain:
Blockchain integration addresses the critical needs of data integrity and traceability in the testing process. Each test execution, result, and related metadata is recorded as a transaction on the blockchain.
Key benefits include:
- Immutability: Once recorded, test data cannot be altered, preventing any tampering with results.
- Traceability: The entire history of test executions can be traced, providing a clear audit trail.
- Decentralization: Test data is distributed across multiple nodes, reducing the risk of data loss.
- Smart Contracts: Automated test orchestration and result validation can be implemented using blockchain smart contracts.
In a regulated industry like healthcare or finance, this blockchain integration could provide irrefutable evidence of compliance testing, satisfying stringent audit requirements.
3. Distributed testing via Edge Computing:
Edge computing brings the test execution closer to the data source, which is particularly valuable for mobile and IoT applications that operate in diverse geographical locations.
Key aspects include:
- Reduced Latency: By running tests closer to the end-user locations, the framework can more accurately replicate real-world conditions.
- Improved Scalability: Tests can be distributed across multiple edge locations, allowing for parallel execution and increased testing capacity.
- Context-Aware Testing: Edge devices can simulate local conditions (like network variability), providing more realistic test scenarios.
- Resource Optimization: By offloading some testing to edge devices, central cloud resources are freed up for other tasks.
4. Comprehensive IoT testing:
As IoT devices become more prevalent, IoT testing frameworks need to adapt to their unique requirements. This framework extends its capabilities to encompass the IoT ecosystem.
Key features include:
- Device Simulation: The ability to simulate various IoT devices, allowing for testing without physical hardware.
- Protocol Support: Built-in support for common IoT protocols like MQTT, CoAP, and others.
- Interoperability Testing: Capabilities to test how IoT devices interact with each other and with central systems.
- Performance and Scale Testing: Tools to simulate large numbers of IoT devices to test system capacity.
- Security Testing: Specialized tests for IoT-specific security concerns like device authentication and data encryption.
Tap the new mobile app quality engineering reality with Kellton
With personalized mobile app experiences reigning supreme in every reality, the journey toward digital excellence is fueled by next-generation mobile automation, powering everything from seamless user experiences to groundbreaking IoT innovations. The above-discussed high-impact use cases are the proof. At Kellton, we strongly believe that running automated tests on mobile apps instantly helps QA Engineers better grasp performance bugs, the latest testing tools, software programming practices, and the technology stack.
As a trusted quality engineering partner, Kellton helps keep pace with mobile automation trends—we redefine the future of quality assurance beyond traditional testing by leveraging cutting-edge AI and ML capabilities for predictive quality assurance and driving unparalleled scalability at every development stage.
With Kellton, you're not just adopting mobile automation but embracing a paradigm shift in quality engineering. Our team helps unlock your mobile applications' full potential with high performance and revolutionize your mobile app development lifecycle.
Book a personalized mobile automation assessment with our QA engineers to discover how our tailored quality engineering solutions can transform your mobile strategy from a roadblock to a launchpad for success.
