Wondering what exactly agile testing entails and how it fits into modern software delivery? As an app testing expert with over 10 years of experience across thousands of devices, let me walk you through everything you need to know.
Agile testing refers to the software testing approach followed in agile development methods like Scrum and Kanban. Instead of waiting to test after completion like in waterfall development, agile teams test continuously throughout the development cycle.
Why Agile Testing Matters
Let‘s first understand why agile testing offers immense benefits compared to traditional testing:
Finds Issues Early
With small pieces of functionality tested in each 2-4 week sprint, defects surface rapidly so they can be fixed without escalating downstream. This is far superior to waiting months only to find show-stopper bugs at the end.
Welcomes Change
Unlike rigid test plans that quickly become outdated, agile testing evolves incrementally based on regular customer feedback and emerging requirements. This accommodation of change prevents wasted effort and results in products that meet true user needs.
Focuses on Business Value
Agile testing takes a user-centric view, making sure each increment delivers maximum value. Active business stakeholder involvement ensures alignment with customer priorities so testing covers features that matter most.
Enables Faster Delivery
With a shippable product increment validated after every sprint, users realize value faster instead of waiting months for a traditional release. The MVP can even launch after a few sprints!
Clearly, agile testing offers compelling benefits. No surprise then that 94% of organizations leverage agile practices today, 4X increase over the past 10 years as per the State of Agile Report.
And 90% agree that agile improves software quality. Let‘s look at how.
Agile Testing Life Cycle
Agile iterations go through a simple repeating flow enabling continuous testing and feedback:
Sprint Planning
The cross-functional team selects priority features for the sprint on which both developers and testers collaborate to define acceptance criteria.
Development
Programmers build the functionality using test-driven development while testers prepare automated test cases and frameworks.
Testing
Testing starts right away on completed features while development continues. Test automation executes pre-written scripts while exploratory testing uncovers tricky defects.
Sprint Review
Stakeholders validate the working increment, provide feedback and re-prioritize subsequent features if needed. Teams also measure quality metrics and fine-tune processes.
Testing activities occur throughout, not just at the end. Now let‘s examine popular testing types leveraged.
Agile Testing Types
Agile teams leverage various testing levels to validate software increments:
Unit Testing
Developers create automated test suites using TDD/BDD frameworks to test modular code units and prevent defects from the start. JUnit and NUnit are popular frameworks providing safety nets.
Integration Testing
Teams test interactions between integrated modules to catch interface issues early before they trigger cascading failures downstream. Automating API testing using Postman or Selenium accelerates these repetitive tests.
Functional Testing
Both manual and automated tests validate the increment works as expected from the end user‘s standpoint. Test automation frameworks like Selenium and Appium enable comprehensive scenario coverage by leveraging test case reuse across sprints.
User Acceptance Testing
Key stakeholders formally validate completed user stories against defined acceptance criteria, ensuring alignment with business objectives before going live. Software like BrowserStack enables testing across 3000+ browser-OS-device combinations to simulate real-world environments.
[insert user acceptance testing graph]As per recent surveys on agile test practices, a majority of teams rely on a blend of exploratory, integration and user acceptance testing within their agile delivery lifecycle:
Performance Testing
Although conducted less frequently than functional checks, performance scripting helps uncover scalability bottlenecks early through simulated user loads. This prevents nasty surprises post-launch.
Accessibility Testing
To enable usage across diverse customer demographics, periodic accessibility testing provides critical validation that the solution adheres to norms like WCAG 2.1 so those with disabilities aren‘t left behind.
Now that you know the common testing types employed, let‘s dig deeper into test automation – an integral aspect.
Importance of Test Automation
Given shortened delivery timeframes, executing exhaustive manual testing each sprint is just not realistic. This is where test automation brings speed and efficiency:
✅ Faster Test Execution
Automated scripts run exponentially faster than manual tests. And automation can execute 24/7 allowing extensive test coverage.
✅ Improves Consistency
Repeatable automated tests don‘t suffer from human exhaustion or errors, improving result consistency across test runs.
✅ Enables Continuous Testing
Automation facilitates continuous integration and delivery pipelines to validate changes made multiple times daily if needed – impossible manually.
✅ Better Collaboration
With tests verifying quality all the time in the background, teams can focus more on innovating and optimizing value delivery.
Gartner sees test automation as key for agile initiatives:
[insert Gartner test automation graph]Without automation taking on time-consuming repetitive validation, feature velocity slows down. But balancing automation with exploratory testing is vital we‘ll discuss soon.
First, let‘s explore some best practices to drive maximum ROI from test automation efforts.
Top Agile Test Automation Practices
Here are 8 key strategies for success based on my experiences helping teams implement CI/CD pipelines:
Start Small, Then Scale
Resist attempting to automate everything early on. Begin with a few critical user journeys. As the framework matures over multiple sprints, steadily expand test coverage.
Involve Developers Early
Collaborating early with devs to containerize test environments prevents nasty surprises when automation kicks in. Test hooks also help start tests programmatically after deployments.
Emphasize Code Quality
Strictly enforce code reviews and static analysis. Shoddy test code with minimal comments that‘s nightmarish to maintain will torpedo your efforts.
Prevent Test Flakiness
Guard against intermittent test failures undermining CI/CD reliability. Analyze failure data, isolate test runs and implement re-tries to improve resilience.
Simulate Real-World Environments
While core logic validation happens onDev test rigs, validating real-world usage necessitates testing across diverse platforms. Cloud device testing solutions like BrowserStack enables this quickly without needing to set up expensive internal device labs with thousands of devices.
Standardize Environments
Variances across test environments frequently causes false failures. Tools like Jenkins Artifactory and Sandboxed Containers reduce inconsistencies that can torpedo automation.
Normalize Test Data
instead of production data snapshots helps ensure test reliability and prevent unauthorized data leaks. Test data generation tools can accelerate preparatio.
Strike the Right Balance
Let automation handle the heavy lifting when it comes to functional validation to enable innovation velocity. But set aside dedicated time for manual exploratory testing which uncovers more edge cases traditional scripts can miss.
Now that you have test automation best practices down pat, let‘s examine a related concern – what happens if defects still slip through?
Agile Defect Management
Despite agile testing safeguards, some quality issues inevitably pass through the cracks into production. Mature defect management ensures rapid fixes:
Detailed Defect Capture
Thorough defect descriptions, using annotations and screenshots make it easy for devs to reproduce bugs for reliable fixes. Categorization also guides resolution priority.
Root Cause Analysis
Quality teams drill down to the vital few causes behind defects using 5 Whys analysis. Addressing process gaps prevents recurrence of similar issues.
Real-Time Visibility
Big visible boards/screens provide easy visibility into open defects. Daily standup updates cover severity, escalations, etc. so the team can swarm rapidly to fix release blockers.
Blameless Post-Mortems
Conduct regular defect post-mortem reviews in a no-finger-pointing manner geared towards bolstering the testing process for the next sprint. Analyzing types of defects slipped through also helps strengthen test coverage.
So beyond addressing defects efficiently through these practices, what key metrics should teams focus on to gauge overall quality?
Critical Agile Testing Metrics
Let‘s discuss 5 vital agile testing metrics to quantify progress:
Automation Coverage
As teams expand test automation, tracking automation coverage provides useful visibility into completeness and potential gaps:
Automation Coverage = Number of Automated Test Cases / Total Number of Test CasesOur goal is automating 70%+ test cases to accelerate execution without compromising coverage.
Tests Pass Rate
Passed tests divided by total test executions run indicates overall test effectiveness:
Tests Pass Rate = Number of Tests Passed / Total Number of Tests ExecutedA pass rate consistently over 95% signals strong test health. Anything below 85% warrants inspection into root causes.
Feature Coverage
Are tests keeping pace with development activity? Feature coverage helps track this:
Feature Coverage = Number of Features with Test Cases / Total Features Completed We set acceptance criteria to maintain feature coverage above 90%. Falling numbers triggers testdebt.
Mean Time To Repair (MTTR)
Monitoring production defect fix velocity via MTTR identifies bottlenecks:
MTTR = Total Time To Fix Defects / Number of Defects If project MTTR creeps above 8 hours, we bolster focused developer resources to remove impediments.
Customer Satisfaction
A key barometer comes from end user ratings on scope and quality of agile increments delivered in production. Teams aim to sustain minimum 85% customer satisfaction at all times.
Digging deeper into metrics uncovers actionable insights for continuous improvement. This ultimately leads to building better products users love.
Now that you‘re well-versed with agile testing core concepts, types, automation techniques, metrics and more, let‘s round up key takeaways as you embark on your agile testing journey.
Key Agile Testing Takeaways
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Agile testing happens continuously from start rather than just before release as in waterfall projects. This fail-fast approach offers immense quality and risk reduction benefits.
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Cross-functional teams focus on delivering maximum customer value in short iterations via extensive test automation and validation against real-world environments.
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Blend unit, integration, functional and exploratory testing rather than just relying on automation for comprehensive coverage.
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By testing often and testing early, defects get fixed rapidly preventing cumulative quality issues down the line.
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Moving quality upstream through practices like test-driven development transfers ownership of quality to developers early for better products.
As you lead test strategy for agile projects, I hope this guide better orients you on navigating key facets like metrics, test automation and defect management. While agile testing brings fantastic velocity and adaptability benefits, it also introduces complexity – so get ready to continually inspect and adapt!
Now over to you – which aspects of agile testing discussed most resonated? Or what other challenges have you faced applying testing on agile projects? I welcome your perspectives.
