Intelligent Exploratory Testing for Agile Development Teams

You must have heard about modern agile development practices, right? These practices ensure that you add adaptability, rapid iterations, and continuous feedback within your software development and testing cycle. While you’re working in such a dynamic environment, you’ll often feel like traditional testing practices are no longer enough. You’ll have to use advanced practices like intelligent exploratory testing and AI in testing. 

New to intelligent exploratory testing? Don’t worry! We are here for you. Our article will help you understand the basics of intelligence exploratory testing, its importance in agile teams, all the best practices related to it, and finally, certain tools that can help you optimize this process. 

Understanding Exploratory Testing in Agile 

Before you start diving deep into the targeted details, it is very important for us to amplify our basic understanding of intelligent exploratory testing while working in an agile environment. It is basically an unscripted, experience-based approach where the testers will actively work with an application. During their interaction, they will investigate its functionality, usability, and potential vulnerabilities. 

Unlike conventional automated tests or preferred scripts, exploratory testing is highly dynamic and will rely on the creativity and domain knowledge of every tester. In an agile environment, where the requirements will continually evolve, the exploratory testing process will have to focus on: 

• Discovering the edge cases that scripted tests will often miss during the execution process. 

• Validating the user experience while interacting with multiple elements that are present in the application. 

• Adapting the testing practices and also the testing approach depending on the changing requirements of the application. 

• Finally, ensuring rapid defect detection and dissolution so that the teams can quickly deploy the final product to the end users. 

Limitations of Traditional Exploratory Testing 

While we are on the topic of intelligent exploratory testing, various testers must have the question of what it has to offer extra when compared to traditional exploratory testing processes. To justify this area, let us divert our attention toward some of the major challenges faced by traditional exploratory testing: 

• The major challenge is in terms of inconsistencies, as different testers will follow different approaches. These changed approaches will lead to gaps in the testing coverage and will also lead to various elements being untested completely. 

• There will also be major challenges in terms of documentation. This is because testers often struggle to document their findings effectively. Therefore, you will see scenarios where various previously known errors are left unnoted and not tracked eventually. 

• Finally, traditional exploratory testing will have scalability issues as it will become less manageable with the growing application structure. This means that you will find yourself losing track of the core structure when you have to implement thousands of such testing scenarios simultaneously.  

All these challenges can be easily resolved by implementing intelligent exploratory testing. It will enhance your testing capabilities by integrating AI in testing, analytics, and automation. All these additions will have a significant impact in terms of testing coverage, insights and traceability.  

Benefits of Intelligent Exploratory Testing in Agile 

To further justify the integration of intelligent exploratory testing in the modern application development and testing infrastructure, we have shortlisted some of the major benefits testers can implement while using this process: 

• It allows you to use faster feedback loops as you will have access to real-time insights. This process will also enable the agile teams to fix issues quickly and iterate efficiently to release a high-quality application in a short time. 

• Intelligent exploratory testing has an important role in improving the overall test coverage. This is because by using AI capabilities to suggest the testing areas, this process will ensure comprehensive testing coverage while reducing the overall blind spots. As a whole, you can ensure that there is at least one test case dedicated to every element of the application. 

• You must be aware that intelligent tools allow better collaboration with different members of the testing team. Similarly, intelligent exploratory testing also allows the testers to collaborate with the developers and product owners to generate meaningful testing insights. 

• Since intelligent exploratory testing will be deploying automation to handle the documentation process, you, as a tester, can focus more on the exploratory activities. This process not only reduces redundant tasks but also helps improve the overall productivity of the testing workflow. 

• Finally, exploratory testing has a significant role in improving the risk assessment factor. This is because you will be prioritizing the high-risk areas in this process while ensuring that critical bugs are detected and resolved at the earlier phase of the development cycle. The automated documentation process also serves as an added benefit for this step.  

Implementing Intelligent Exploratory Testing in Agile Teams 

If you want to implement intelligent exploited testing in an agile development environment, there are certain steps that you must follow in the correct order. To simplify this infrastructure, we have measured all the required information below: 

1. Defining The Testing Objective: The very first step in the entire implementation process is to define the objectives for the testing process. You must align these objectives with sprint goals so that you can have meaningful insights after the test execution process.  

2. Choose The Right Tools: After you have defied your testing objective, you can move on to choosing the right AI-powered tools that will allow you to implement proper intelligent exploratory testing. While implementing this process, you can consider using tools like Applitools Eyes and Session-Based Test Management (SBTM). While Applitools Eyes will help you implement AI-powered visual testing for UI elements, SBTM will help document exploratory sessions in a systematic format. 

3. Use AI For Test Guidance: After you have chosen your required tools for implementing the workflow, you must use AI-based analytics to identify the high-risk areas. These areas will be your priority while implementing the testing process. The main idea behind this approach is that it will help ensure that at least the basic infrastructure of the application is functional in all instances.  

4. Implement Continuous Feedback Mechanisms: The next step in the implementation workflow is to ensure that exploratory test cases are integrated within the agile workflow. You can perform the integration process by using dashboards and other automation steps.  

5. Automate Documentation And Reporting: The final step in this regard is to use AI-powered test recorders for capturing user sessions and generating meaningful reports. These reports will also help you to find the faulty elements within the application and implement the required debugging and troubleshooting steps.  

Sample Implementation Of Intelligent Exploratory Testing 

To better understand the implementation process, let us consider the example of an e-commerce company that has adopted this practice to improve the quality of its mobile applications. Initially, they faced challenges with UI changes and inconsistent test coverage. 

For the organization, the implementation process will begin by adding AI-driven exploratory testing tools for analyzing historical defect patterns and then moving on to automated session recording for capturing the exploratory test sessions. Finally, they will wrap up the testing scenario by using risk-based testing insights to prioritize the testing efforts.  

This entire workflow will help reduce the critical bugs reaching the production phase, improve the test coverage, and also enhance collaboration between testers and developers.  

Best Practices for Agile Teams 

Let us now divert our attention toward some of the best practices that we suggest all the agile teams implement within the testing workflow while working with intuitive exploratory testing. These practices have been carefully chosen to have a significant impact on not only the development sustainability but also the quality of the application as a whole: 

• We suggest the testers establish an exploratory mindset. By using this mindset, you can think creatively, analyze user behaviors, and also explore the application beyond the scripted tests. Practices like these are crucial to analyzing the app’s functioning when exposed to real-world usage. 

• It is very important to integrate the exploratory process with continuous integration and continuous deployment pipelines. This will help you ensure that the entire workflow becomes a part of the Agile release rather than becoming an afterthought. It is also important to conduct these processes simultaneously with the development phase.  

• We strongly encourage the testers to implement cross-functional collaboration. This collaboration can involve developers, designers, and product owners in the exploratory testing sessions. By implementing this approach, you can bring diverse perspectives to the testing session to further analyze the capabilities of the application. 

• We strongly advise the testers to incorporate cloud-based platforms like LambdaTest for integrating intelligent exploratory testing with cloud-based real device testing. LambdaTest is an AI-powered test orchestration and execution platform that lets you perform manual and automation testing at scale with over 3000+ real devices, browsers, and OS combinations. Apart from implementing automated cross-browser testing, this platform will also help you in testing AI components present in your app.  

• Finally, it is a wise choice to use Session Based Exploratory testing or SBT. In this approach, you have to divide the exploratory testing processes into timebox sessions. These sessions will be implemented with structured goals and documentation to ensure a streamlined testing approach.  

Future Of Intelligent Exploratory Testing 

As you already know, machine learning algorithms and artificial intelligence are dominating all the segments related to software development and deployment. It is not rocket science to guess that intelligent automation testing will also be impacted by these new trends. Let us divert our attention to some of the major upcoming additions in this regard: 

• Testers will see the onset of various self-learning AI models, which will help predict defect-prone areas within the software infrastructure. 

• There will also be an onset of automated cognitive testing, which will help improve the UI validation process during the software development cycle. 

• Finally, there will be various AI-powered test bots that will autonomously explore applications based on the set benchmarks in the testing criteria.  

The Bottom Line 

Based on all the factors that we have put forward in this article, we can easily say that intelligent exploratory testing will help you cover the gap between structured automation and human involvement. This approach will make it an ideal way for agile development teams implementation. By using all the techniques that we have put forward in this article, you can enhance the testing efficiency to improve the software quality and also deliver as per your user expectations. 

With the continuously evolving solution of agile development, you must integrate intelligent exploratory testing to ensure high-quality, defect-free applications. This approach will also help the organizations to have a competitive advantage as they’ll be delivering reliable and user-friendly products faster and more efficiently.

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