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    Qa Metrics & Kpis: Testing, Defect Tracking & Automation

    Posted By: ELK1nG
    Qa Metrics & Kpis: Testing, Defect Tracking & Automation

    Qa Metrics & Kpis: Testing, Defect Tracking & Automation
    Published 5/2025
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.44 GB | Duration: 4h 49m

    Master QA & QC metrics, test planning, bug tracking, test automation KPIs, and QA reporting techniques

    What you'll learn

    How to define meaningful QA metrics and KPIs

    Test case execution tracking and analysis

    Measuring test coverage and test effectiveness

    Calculating defect density and leakage rates

    Understanding severity vs. priority in defects

    How to assess test automation ROI

    Tracking and reducing test flakiness

    Using metrics in retrospectives and process reviews

    Identifying and addressing QA bottlenecks

    Metrics for evaluating sprint test readiness

    Prioritizing tests with risk-based approaches

    Leveraging defect trends to optimize coverage

    Calculating mean time to detect and fix defects

    Evaluating automation coverage and execution time

    Requirements

    Basic understanding of software testing concepts

    Familiarity with QA processes (manual or automated)

    Experience with defect tracking tools (e.g., Jira, Bugzilla)

    Some exposure to test case management tools (e.g., TestRail, Zephyr)

    Interest in data-driven QA and continuous improvement

    No advanced programming or statistics knowledge required

    Description

    Deliver Better Software Through Measurable Quality – Learn to Track, Analyze, and Optimize QA PerformanceIn today’s fast-paced development world, delivering high-quality software isn’t enough—you need to prove it with metrics. That’s where this course comes in.QA Metrics Workshop: Testing, Defect Tracking & Automation is a practical, in-depth course designed to help QA professionals leverage data and key performance indicators (KPIs) to improve testing efficiency, reduce risk, and boost software quality. Whether you work in a manual testing, automation, or agile QA environment, this course will help you transform your testing process into a measurable, strategic asset.What This Course OffersYou’ll learn not just what metrics to track, but why they matter, how to calculate them, and when to apply them. We’ll cover all key areas of modern QA work:Test Metrics: Test case pass/fail rates, execution progress, test coverage, defect detection effectiveness, and moreDefect Metrics: Defect density, leakage rate, mean time to detect/fix, severity/priority distributionTest Automation KPIs: Automation coverage, stability, ROI, execution time, flakiness rateReporting & Dashboards: learn metrics tha will help you to build stakeholder-facing reports using tools like Jira, TestRail, Excel, and custom dashboardsQA Process Improvement: Use metrics to drive retrospectives, quality gates, and team performance evaluationsAgile QA Metrics: Story-level quality, velocity-to-bug ratio, sprint test readiness, continuous testing indicatorsRisk-Based Testing: Prioritize efforts based on impact, past defect trends, and test effectivenessYou’ll also get templates, formulas, KPI scorecards, and visual dashboard examples that you can adapt directly into your projects.Who This Course Is ForManual Testers who want to better demonstrate their impact through test resultsAutomation Engineers who need to show ROI and stability of their frameworksQA Leads & Managers looking to implement measurable quality processes and KPIsAgile QA Practitioners who need to align quality metrics with fast delivery cyclesBusiness Analysts & Product Owners who want to understand what QA metrics actually say about product healthWhat You’ll GainBy the end of this course, you will:Be able to define, collect, and report on metrics that matter to your projectKnow how to communicate test status and quality to developers, PMs, and execsBe confident in using data to drive continuous QA process improvementsHave practical tools and ready-to-use templates that make metrics actionableThis isn’t a theoretical course. It’s a practical QA toolkit packed with examples, industry best practices, and data you can start applying immediately to improve your QA outcomes and career.Enroll now and make your testing efforts visible, valuable, and impactful through the power of metrics.

    Overview

    Section 1: Introduction

    Lecture 1 Communication plan

    Lecture 2 Tips to Improve Your Course Taking Experience

    Section 2: Defect Management Metrics & KPIs

    Lecture 3 Defect Management Metrics & KPIs: Number of Open Defects & Defect Leakage

    Lecture 4 Defect Management Metrics & KPIs: Defects per Severity/Priority/Env/Root cause

    Lecture 5 Defect Management Metrics & KPIs: Defect Density, Non-Resolved Blockers & Others

    Lecture 6 Defect Management Metrics & KPIs: Quality Debt Index, Bug Fixing Projection

    Lecture 7 Defect Reopen, Defect Rejection, Open Defects Change Rate, Removal Efficiency

    Lecture 8 Defect Resolution Time, Defect Age, Detection to Resolution Ratio

    Section 3: Testing Metrics & KPIs

    Lecture 9 Test execution coverage, Cost of Quality & Test Design Coverage

    Lecture 10 Testing Metrics & KPIs: Regression Time, Verified Issues Rate, Pass Rate

    Section 4: Test Automation Metrics & KPIs

    Lecture 11 % of Poduct, Automation, System Issues & Execution Frequency

    Lecture 12 Execution Time, Test Success Ratio & % of Results Analyzed

    Lecture 13 Regression Effectiveness, Percentage of Automated Tests & Auto Savings

    Section 5: Bonus Section

    Lecture 14 Bonus Lesson

    Manual testers wanting to show the value of their work with data,Automation test engineers needing to demonstrate ROI and reliability,QA leads and managers aiming to implement metric-driven processes,Agile QA professionals aligning testing with fast-paced delivery,Business analysts and product owners seeking insights into product quality through QA metrics,Software developers who want to understand QA impact and feedback loops,Project managers looking to track quality and delivery risk,Delivery managers focused on release readiness and defect trends,Engineering managers aiming to improve team performance through data,Product managers who need to align quality signals with product goals,Software architects interested in the relationship between system design and defect patterns