AI for Software Testing

Duration: 2 Days Instructor-led

Overview 

The future of software testing lies at the intersection of human ingenuity and technological leverage. Our AI for Software Testing course is an immersive and interactive journey to prepare experienced software testing professionals for the AI-empowered future. Through hands-on exercises with leading AI agents and tools, gain first-hand experience generating key artifacts from system test plans to individual test cases. AI can automate the boring and repetitive work of generating test cases, but it can do much more. You will learn how to use AI to evaluate existing tests, structure systems for more effective testing, interpret results, and maintain traceability from requirements to tests. Whilst balancing AI’s power to create testing artifacts with human judgment, you will discover how AI can help streamline the testing process through increased test automation. 

In This Class You’ll Learn 

• Develop test cases, executable automated test scripts, and test suites with the assistance of AI 

• Evaluate strengths and weaknesses of AI-created test artifacts 

• Test against specifications more thoroughly with AI augmentation 

• Employ AI to design combinatorial and exploratory test sets 

• Analyze test results and defect reports using AI. 

• Develop test plans for non-functional requirements with AI 

• Incorporate agile user stories into testing using AI 

• Utilize AI to amplify manual testing efforts 

Course Outline 

Part 1: Introducing Generative AI for Software Testing 

Part 2: Let’s Test with AI 

• Use AI agents to generate and run tests 

Part 3: Modelling for Testing 

• Apply different ways to structure a problem and organize the testing process 

Part 4: Test Planning with AI 

• Use AI to help create an overall test strategy, using a Test Strategy Canvas and, Testing Quadrants 

Part 5: Testing Single Functions 

• Learn how AI can assist with equivalence partitioning, boundary value analysis, state and preconditions when defining tests 

Part 6: Evaluate Tests 

• Identifying missing and redundant tests as well as the level of test coverage 

Part 7: Activities and Processes 

• Use AI to generate use cases in several forms (traditional, Given-When-Then, and graphical) and generate detailed test cases 

Part 8: Planning the End Game 

• Create AI-generated test plans for UAT, alpha, beta, and usability testing 

Part 9: Stories and Scenarios 

• Use AI to present a user story in terms of a set of scenarios that need to pass 

Part 10: Automation 

• Use AI to generate automated test cases 

Part 11: Quality Attributes & Non-functional Requirements 

Part 12: Evaluating AI Readiness 

• Ethical considerations and emerging trends