Exploratory testing is a method that focuses on discovering unknown risks and learning about software systems through experimentation, rather than verifying predefined expectations. It combines structured and unstructured approaches, and emphasizes the importance of balancing speed and quality in testing.

Software Testing Unleashed

Software Testing Unleashed - hosted by Richard Seidl. Different guest per episode. The official Show notes contain a comprehensive overview of the episode. Released as audio and video.

• https://www.richard-seidl.com/en/testing-unleashed
• https://www.youtube.com/playlist?list=PL48Mbm-L0hjB1OdwYi9h7jrq9t352-Zk_

Episode Details

• Show Notes: https://www.richard-seidl.com/en/blog/exploratory-testing
• Published: 2026-03-12T05:00:00Z
• Duration: 1818
• Author: Richard Seidl | Software Development & Testing Expert

Overview

The podcast discusses exploratory testing, a method focused on discovering unknown risks and learning about software systems through experimentation, rather than verifying predefined expectations. It contrasts with traditional testing by emphasizing exploration of uncharted areas, such as non-functional requirements (e.g., security, performance, usability), where no prior documentation exists. Exploratory testing can be structured (e.g., through shift-left testing or retrofitting non-functional requirements) or unstructured (e.g., bug bashes), though structured approaches are more common in professional settings. Key applications include identifying edge cases, collaborating with developers to uncover risks early, and integrating AI tools for automation in large-scale testing scenarios. The discussion also addresses common misconceptions, such as equating exploratory testing with random clicking or limited to manual efforts, clarifying that it can be methodical, time-boxed, and enhanced by automation.

The podcast highlights the importance of non-functional requirements in quality assurance, particularly in legacy systems, and stresses the need to de-risk unknown areas through proactive testing. It outlines challenges in QA, such as organizations prioritizing features over quality and under-resourcing non-functional aspects like scalability or security. Best practices include structured risk-based testing, time-boxing sessions, and fostering team alignment to focus on critical issues. The role of collaborationsuch as using practices like “Three Amigos” or pair testingis emphasized to align testing with business goals. Documentation and communication are framed as essential for actionable insights, with recommendations for concise reporting via tools like Slack or Wiki pages.

The discussion also explores AI and automation in exploratory testing, noting tools like Playwright with language models for identifying workflows and retrofitting regression tests. However, it cautions against over-reliance on AI, emphasizing the need for human validation. Techniques like “golden master testing” and characterization testing are described as ways to document existing system behavior without prior requirements. The podcast concludes by advocating for a balance between speed and quality, prioritizing depth over breadth in testing, and using structured exploratory methods to inform scripted/automated tests while avoiding perfectionism. Key takeaways include the value of early risk identification, structured collaboration, and context-driven documentation to integrate quality into development processes.

What If

• What if you used exploratory testing to retrofit non-functional requirements in a legacy system youre maintaining?
  Concrete move: Conduct a 2-hour exploratory session focused on security and performance gaps in a core feature of the legacy app. Use tools like OWASP ZAP for security checks and JMeter for load testing.
  Why now: Many organizations overlook non-functional requirements in legacy systems, and the text emphasizes the importance of proactively uncovering risks like security flaws or performance bottlenecks.
  Expected upside: Youll identify critical vulnerabilities or inefficiencies that could prevent scalability or compliance issues, improving system resilience without requiring upfront documentation.

• What if you time-box exploratory testing sessions with a clear focus on user pain points instead of random bug-hunting?
  Concrete move: Schedule a 1-hour exploratory session targeting a feature recently reported as slow or error-prone by users. Document your process using a test charter and share findings in a Slack post with the team.
  Why now: The text stresses time-capped sessions to avoid wasting effort on irrelevant issues, and aligning testing with user priorities ensures actionable results.
  Expected upside: Youll surface high-impact issues (e.g., a UI bug causing data loss) efficiently, fostering team collaboration to prioritize fixes over abstract QA tasks.

• What if you leveraged AI-driven exploration tools to automate the discovery of edge cases in your API?
  Concrete move: Integrate an AI tool like Playwright with a language model to spider your API endpoints, identify unexpected input behaviors, and generate test scenarios for error handling.
  Why now: The text highlights AIs potential to enhance exploratory testing by automating repetitive tasks and uncovering hidden edge cases.
  Expected upside: Youll reduce manual effort in exploring uncharted API areas (e.g., rate-limiting issues) and create a reusable test suite for regression checks, improving long-term maintainability.

Takeaway

• Implement structured exploratory testing with time-boxed sessions to focus on high-risk areas (e.g., security, performance) and avoid over-investigation, using frameworks like Elizabeth Hendricksons “Explore It!” to maintain clarity and efficiency.

• Collaborate with developers early using “Three Amigos” or pair testing to identify risks in code/design before implementation, ensuring alignment on priorities and reducing rework through shared understanding.

• Leverage AI tools for automation in exploratory testing (e.g., Playwright with language models) to document workflows, identify edge cases, and generate test scripts, particularly for large-scale or repetitive tasks.

• Document test findings using post-session reports and team collaboration tools (e.g., Slack, Wiki, Teams) to capture actionable insights, avoid redundant testing, and ensure outcomes are integrated into development workflows.

• Adopt time-capped exploratory testing (e.g., 1 hour per session) to prioritize depth over breadth, and escalate unresolved issues to the team for decision-making, avoiding unnecessary effort on low-impact risks.