Role-Based Programme
RB0913

Amazon Q Developer for Quality Management

AI-Assisted Testing, Code Quality & Software Assurance

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Build foundational proficiency in using Amazon Q Developer to support software quality assurance, testing, defect analysis, and technical review activities.
  • Apply AI-assisted techniques to understand code, generate test scenarios, identify defects, and improve test coverage.
  • Use Amazon Q Developer to support security review, troubleshooting, documentation, and quality-focused developer collaboration.
  • Create reusable workflows for requirement review, test design, defect investigation, and release-readiness checks.
  • Apply appropriate validation, traceability, security, and human quality judgement when using AI-generated technical outputs.

Tools covered

Amazon Q DeveloperIDE ChatCode ExplanationCode ReviewUnit Test GenerationDebugging AssistanceSecurity ScanningAWS Technical Guidance

Who should attend

  • Quality Assurance Professionals
  • Software Quality Engineers
  • QA Engineers
  • Software Test Engineers
  • Quality Managers
  • Test Analysts
  • Automation Test Engineers
  • Application Quality Professionals
  • DevOps Quality Professionals
  • Technical Quality Leads
  • Software Validation Professionals
  • Quality Engineering Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of software testing or quality-assurance activities
  • Familiarity with functional requirements, defects, test cases, or software-development workflows
  • Basic awareness of programming concepts is helpful
  • Familiarity with IDEs or development environments is beneficial
  • No advanced programming expertise required
  • No previous Amazon Q Developer experience required

TOC Modules

Concepts
  • Understanding Amazon Q Developer and its role in software-development and quality workflows
  • Identifying applications across testing, code review, debugging, security, and documentation
  • Understanding the relationship between developer assistance and independent quality validation
  • Recognising limitations of AI-generated technical recommendations
Practical activities
  • Exploring Amazon Q Developer in a supported development environment
  • Reviewing a sample application from a quality perspective
  • Asking quality-focused questions about application behaviour and code

Scenarios

Feature Requirement to Quality Validation

Business Requirement → Acceptance Criteria → AI-Generated Test Cases → Code Review → Defect Identification → Fix Validation → Release Recommendation

Participants use Amazon Q Developer to support an end-to-end software-quality review, from requirement interpretation through testing and release-readiness assessment.

Production Defect to Corrective Action

Reported Defect → Error Evidence → Amazon Q Analysis → Root-Cause Hypothesis → Code Review → Proposed Fix → Retesting → Quality Closure

Participants analyse a software defect, investigate likely causes, review proposed technical changes, and create structured validation and closure documentation.

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