How Do You Handle Complex Or Uncertain Scenarios With Specification By Example Tests?

Automation testing incorporating Specification by Example (SBE) is a powerful approach. Often associated with Behavior-Driven Development (BDD), SBE focuses on creating executable specifications through concrete examples of a system’s behavior. While this methodology provides clarity and precision in defining requirements, it is essential to have strategies for handling complex or uncertain scenarios with SBE tests.

Automation testing with complex or ambiguous specifications is a common challenge in the software development lifecycle. Complex specifications refer to requirements that lack essential details, while uncertain specifications can be interpreted in multiple ways. In certain instances, misunderstandings, delays, and, in the most severe scenarios, the deployment of faulty software may arise.

By embracing complexity as a chance for advancement and refinement in SBE tests, testers can guarantee the software’s quality and significantly contribute to the triumph of the entire development process. In a perpetually changing software environment, performing automation testing adeptly under suboptimal conditions is a valuable capability.

Complex or Uncertain SBE Scenarios

Handling complex or uncertain scenarios in SBE tests involves careful consideration and often entails scenarios where the expected behavior is not straightforward or well-defined.

Here are some examples of complex or uncertain SBE scenarios:

Dynamic Permissions: A complex scenario lies in defining specific examples when user roles can change dynamically, affecting permissions during runtime.

Instantaneous Data Synchronization: Synchronizing data in real-time introduces uncertainty related to network latency and conflicts and ensures consistency across distributed systems.

Integrated Lachine Learning Model: Ambiguity arises in defining specific examples due to the dynamic nature of machine learning models and the possible variability in input data.

Versatile UI: Defining examples for diverse devices and ensuring the compliance of the UI introduces complexity, particularly when dealing with an extensive range of form factors.

Interactions with Third-Party APIs: Complexity lies in the behavior of external APIs, including potential changes in response formats, downtime, and unanticipated errors.

Cross-Browser Compatibility: Discrepancies in browser behavior, rendering engines, and JavaScript implementations make it complex to ensure a unified experience across different browsers.

Natural Language Processing Input: It is complex to define examples that cover a diverse range of potential user queries, considering natural language’s innate complexity and uncertainty.

Multi-Tenancy Backing: It is difficult to address scenarios where tenants have unique requirements in a multi-tenant system. Ensuring proper isolation and security measures for each becomes complex.

Offline Operations: Dealing with irregular network connectivity, ensuring data consistency, and supervising conflicts during offline usage pose ambiguity in defining accurate examples.

Security handling: Identifying potential security vulnerabilities, applying updates, and ensuring minimal impact on ongoing operations altogether form a complex scenario.

Tips on Handling Complex or Uncertain Scenarios with SBE Tests

Automation testing is a fundamental component in ensuring a software product’s dependability, functionality, and quality. Nevertheless, the job of automation testing can become stimulating, particularly when faced with case studies or situations that are either complex or uncertain.

Let’s explore various approaches to managing complexity and uncertainty effectively within the context of SBE.

Collaborative Discovery

Collaborative discovery is a foundational principle of SBE. Open discussions among developers, domain experts, and testers are pivotal in fostering a shared understanding of the requirements. This collaboration reveals potential complexities and uncertainties. By linking multiple perspectives, developers can collectively contribute to forming meaningful examples. This will precisely signify the desired behavior of the system.

Iterative Refinement

During the early stages of software development, complexity and ambiguity are inherent. An iterative refinement approach is required rather than defining all scenarios upfront. Begin with simple examples that apprehend the core functionality. Iteratively enhance them as more data becomes available. This makes SBE tests smooth while acknowledging and addressing complexities gradually.

Placeholder Values

Using placeholder values or terms in examples helps when some details are uncertain. These values and terms can serve as temporary placeholders for uncertain information and can be distinguished as more details are unearthed. This method allows the development process to move forward without uncertainties, providing a practical way to handle complex scenarios.

Scenario Outlining

Using scenario outlining serves better than attempting to provide detailed examples for every scenario. Scenario outlining involves capturing complex examples that outline the key interactions and functions. As the teams gain a deeper understanding of the system, they can gradually add details to these outlines. This flexible approach addresses uncertainties and permits the gradual refinement of complex scenarios.

Edge Cases Exploration

Complex SBE scenarios often wait at the edges and boundaries of the system. During the SBE process, it is important to explore edge cases actively. Categorizing and addressing these cases helps accumulate a wholesome understanding of the system’s behavior. This reduces potential issues arising from unnoticed complexities.

Real-Time Documentation

Consider your SBE tests as adaptable documentation that evolves in sync with the system. Regularly update and refine the examples as the system changes or new information emerges. This evolving documentation serves as a reliable reference for the team, ensuring alignment with the dynamic requirements and the system’s current state.

Feedback Loops Automation

Incorporate your SBE tests seamlessly within your continuous integration pipeline to create automated feedback loops. This facilitates swift validation of the system’s behavior with every modification to the codebase. Automated testing delivers prompt feedback, empowering the team to recognize and resolve issues linked to complexity or uncertainties in real-time.

Collaboration Tools

Fostering effective communication and collaboration is paramount in navigating uncertainties within SBE. Employ collaboration tools and platforms designed to enhance communication and facilitate documentation sharing. These tools establish a centralized space where stakeholders can contribute, engage in discussions, and refine examples. Transparent communication ensures the timely resolution of uncertainties, keeping everyone well-informed.

Review Regularly

Regularly review and conduct retrospectives to assess the efficacy of your SBE approach. Reflect on the outcomes, pinpoint areas for improvement, and adjust your testing strategy accordingly. These sessions offer a valuable opportunity for the team to address challenges, share insights, and collectively enhance the SBE process.

Pursue Clarifications

In the presence of uncertainties, actively seek clarifications from stakeholders. Promote a culture of open communication where team members feel encouraged to ask questions and seek additional information. Proactively addressing uncertainties through clear communication aids in refining examples and ensures a more precise representation of the desired system behavior.

Cloud Testing with Complex SBE Scenarios

Handling complex or uncertain scenarios in SBE during cloud testing involves an all-inclusive approach that includes wide-ranging testing, collaboration, and cloud-specific tools. By addressing a variety of complex scenarios and leveraging cloud testing skills, teams can ensure the excellence and reliability of cloud platforms even in the face of complexity and uncertainty.

Here are specific strategies for managing complexity and uncertainty in SBE scenarios within a cloud testing environment:

All-Inclusive Environment Configuration: Ensuring that SBE scenarios cover a comprehensive range of cloud configurations includes testing across different cloud configurations, providers, and regions, such as various compute resources, network setups, and storage options.

Scalability and Elasticity Testing: Developing SBE scenarios that examine the scalability and elasticity of the application under different load conditions is crucial. Employing cloud testing tools can simulate various traffic levels to assess the wellness of the system’s scalability.

Latency and network variability handling: Include SBE scenarios that test the response time and behavior of the system under diverse network latencies. Utilizing cloud testing tools helps simulate diverse network conditions and practical scenarios.

Third-party service incorporation: Developing SBE scenarios to cover possible disruptions in third-party services and utilizing cloud testing environments assists in simulating interruptions or alterations in the behavior of external services.

Data privacy and security: Including security-intensive SBE scenarios that resolve potential vulnerabilities and breaches, leveraging cloud security tools, and conducting penetration testing allows the application to meet high-end privacy and security requirements.

Cross-browser and cross-platform testing: Incorporating cross-browser and cross-platform testing in complex SBE scenarios and applying cloud testing platforms to offer diverse browsers and devices aids in comprehensive testing.

Data migration and backup scenarios: Creating SBE scenarios that cover data migration and backup processes and using cloud testing tools to simulate such scenarios ensure that the application performs as expected throughout data operations.

Constant integration and deployment pipelines: Integrating SBE tests into the continuous integration pipeline guarantees that complex scenarios are executed automatically with each code change. This provides continuous feedback on the effect of changes on the cloud platform.

Monitoring and alerting: Including monitoring and alerting scenarios in SBE tests and utilizing cloud monitoring tools to create alerts based on performance metrics safeguard the continuous monitoring of the system’s health.

Chaos engineering and fault injection: Developing chaos engineering practices as part of complex SBE scenarios and using cloud tools to inject faults into the system helps simulate failures. This is beneficial in observing how the cloud platform responds and recovers.

Cloud testing platforms like LambdaTest help you automate complex or uncertain scenarios with specifications. LambdaTest is an AI-powered test execution and orchestration platform that empowers developers and testers to perform automation testing seamlessly on over 3000+ real browsers and operating system combinations.

LambdaTest’s automation capabilities extend beyond the conventional, making it a valuable tool for tackling intricate testing scenarios. Its user-friendly interface and advanced features empower teams to automate tests seamlessly using frameworks like Selenium, Playwright, and Appium, enabling efficient and effective testing across different browsers and operating systems. LambdaTest is a versatile and powerful ally for those seeking to optimize their automation testing processes.


Automation testing of software with complex or uncertain specifications is a formidable challenge, but it’s a challenge that testers can overcome with the right mindset, techniques, collaboration, and tools. In this article, we’ve explored complex SBE scenarios, ways to handle those complex and uncertain scenarios with SBE tests, and cloud testing with complex SBE scenarios.

As testers navigate the complex terrain of complex and ambiguous specifications, they become advocates for collaboration, quality champions, and continuous improvement drivers. The challenges may continue to exist. But with the right tools and techniques, testers can master them and ensure that the software under automation testing meets the highest standards of excellence and quality.