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Modern Test Analysis & Design  


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Length: 5 day (40 hours)

 

This course focuses on the analytical core of software testing. It moves away from tool-specific training to master the science of Test Design. You will learn how to break down complex business requirements into logical test conditions, identify hidden risks, and choose the most efficient testing techniques (Black-Box, White-Box, and Experience-Based) to ensure maximum coverage with minimum effort.

By 2026 standards, this course also integrates AI-Assisted Test Case Generation and Shift-Left Analysis, teaching you how to influence quality at the requirement stage rather than at the end of the cycle.

Foundation Knowledge: A solid understanding of the Software Development Life Cycle (SDLC) and basic testing terminology.

Certification (Recommended): Holding an ISTQB Foundation Level (CTFL) certificate is highly encouraged as this course builds on those core concepts.

Experience: 1–2 years of practical experience in a QA or testing role is ideal to grasp the real-world complexities of risk-based testing.

Analytical Mindset: Comfort with logical puzzles and the ability to view a system from multiple stakeholder perspectives (User, Developer, Business).

Junior to Mid-Level Testers: Looking to move into Senior or Lead Test Analyst roles.

Business Analysts: Who want to understand how to validate the requirements they write.

Subject Matter Experts (SMEs): Transitioning into technical roles who need a structured approach to User Acceptance Testing (UAT).

Quality Engineers: Focused on "manual" or "exploratory" testing who want to add formal test design techniques to their toolkit.

Course objectivesCourse outlines

Course objectives

After completing this course, students will be able to:

    • Perform Risk-Based Testing: Identify and prioritize test cases based on technical and business risks to optimize the testing schedule.
    • Apply Advanced Design Techniques: Master techniques like Boundary Value Analysis, Decision Tables, State Transition Testing, and Orthogonal Arrays.
    • Influence Requirements: Conduct effective reviews of User Stories and Specifications to "test" them before a single line of code is written.
    • Manage Defect Life Cycles: Not just report bugs, but perform Root Cause Analysis (RCA) to help prevent future occurrences.
    • Utilize AI Tools: Use Generative AI to create diverse test data sets and suggest edge-case scenarios that human analysts might miss.
    • Deliver Stakeholder Value: Create clear, metric-driven reports that help Project Managers make confident "Go/No-Go" release decisions.


Course outlines

    • Phase 1: The Analytical Process
      • The Test Analyst’s Role in Agile/DevOps: Integrating into the "Three Amigos" (Dev, QA, BA) discussion.
      • Test Analysis vs. Test Design: Learning where the thinking stops and the documentation begins.
      • Requirement Smells: Identifying vague or untestable requirements early.
    • Phase 2: Mastering Test Design Techniques
      • Specification-Based (Black-Box):
        • Equivalence Partitioning & BVA: The bread and butter of input testing.
        • Decision Tables: Handling complex business logic and combinations.
        • Classification Trees: Visually mapping out test data requirements.
      • Structure-Based (White-Box) Basics: Understanding Code Coverage (Statement, Decision) to better collaborate with developers.
      • Experience-Based: Advanced Exploratory Testing and Error Guessing strategies.
    • Phase 3: Testing Quality Characteristics (Non-Functional)
      • Usability & Accessibility: Testing for the "Human" element (WCAG 2.2 standards).
      • Interoperability: Ensuring the system works across different browsers, OS, and hardware.
      • Portability & Installability: Validating how the software moves between environments.
    • Phase 4: Defect Management & Tools
      • The Perfect Bug Report: Writing reports that developers can't ignore.
      • Defect Classification: Categorizing by severity, priority, and root cause.
      • Tool Support: Introduction to Test Management tools (Jira/Xray/Zephyr) and AI-augmented testing assistants.
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