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How to Optimize Automated Testing with Everyone's Favorite Butler

Viktor Clerc, Product Manager & Jenkins Fan, XebiaLabs

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Agenda

• The World of Testing is Changing• Testing = Automation• Test Automation and CD: Execution and Analysis• Focus on the Basics• Best Practices for Test Execution using Jenkins• Supporting Test Analysis

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But first…a bit about me

• Product Manager XL TestView for XebiaLabs• Traversed through all phases of the software

development lifecycle• Supported major organization in setting up a

test strategy and test automation strategy• Is eager to flip the way (most) organizations do

testing

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…and about XebiaLabs

• We build tools to solve problems around DevOps and Continuous Delivery at scale

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The World of Testing is Changing

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Introducing Test Automation For Real

SPECIFY DESIGN BUILD TEST INTEGRATE REGRESSIONUSER

ACCEPTANCERELEASE

Acceptance Driven Testing

Development = TestTest = Development

Automate ALL

User Acceptance

Test effort

INTEGRATE REGRESSIONUSER

ACCEPTANCE

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Testing = Automation

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Testing = Automation: Implications

• Developers are becoming testers– Maintain test code as source code

• Need to set up on-demand pipelines and environments

• Infrastructure as code– X-browser tests, Selenium grids, dedicated

performance environments, mobile etc.

• Hosted services

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Testing = Automation: Challenges

• Many test tools for each of the test levels, but no single place to answer “Good enough to go live?”

• Requirements coverageis not available– “Did we test enough?”– Minimize the mean time to repair– Support for failure analysis

JUnit, FitNesse, JMeter, YSlow, Vanity Check, WireShark, SOAP-UI, Jasmine, Karma, Speedtrace,

Selenium, WebScarab, TTA, DynaTrace, HP Diagnostics, ALM stack AppDynamics, Code Tester

for Oracle, Arachnid, Fortify, Sonar, …

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Testing = Automation: Challenges

• Thousands of tests makes test sets hard to manage:– “Where is my subset?”– “What tests add most value, what tests are superfluous?”– “When to run what tests?”

• Running all tests all the time takes too long, feedback is too late

• Quality control of the tests themselves and maintenance of testware

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Testing = Automation: Challenges

• Tooling overstretch

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Testing = Automation: Challenges

• Tooling overstretch• Poor butler!

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Test Automation and CD: Execution and Analysis

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The Two Faces of CD

• A lot of focus right now is on pipeline execution• …but there’s no point delivering at light speed if

everything starts breaking• Testing (= quality/risk) needs to be a first-class

citizen of your CD initiative!

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The Two Faces of CD

• CD = Execution + Analysis

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The Two Faces of CD

• CD = Execution + Analysis• = Speed + Quality

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The Two Faces of CD

• CD = Execution + Analysis• = Speed + Quality• = Pipeline orchestration + ..?

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Focus on the Basics

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Quick Review

1. Cohn’s pyramid– Unit tests– Service tests (under the GUI)– (graphical) User Interface tests

2. And even further downstream– Integration Tests– Performance Tests

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“Modern Testing” 101

1. Testers are developers

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“Modern Testing” 101

1. Testers are developers

2. Test code equals production code– Conway’s Law– Measure quality

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“Modern Testing” 101

1. Testers are developers

2. Test code equals production code– Conway’s Law– Measure quality

3. Linking tests to use cases

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“Modern Testing” 101

1. Testers are developers

2. Test code equals production code– Conway’s Law– Measure quality

3. Linking tests to use cases

4. Slice and dice– Labeling

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“Modern Testing” 101

1. Testers are developers

2. Test code equals production code– Conway’s Law– Measure quality

3. Linking tests to use cases

4. Slice and dice– Labeling

5. Radical parallelization

Fail FASTer!

“Kill the nightlies”

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Dealing With Growing Tests

• Conway’s Law for test code– Let the test code mimic the production code– Organize tests under the project/system under test

• Suite.App.UseCase.TestCase• Cut the suite at UseCase: now you have

independent chunks which you can run massively in parallel

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Dealing With Growing Tests

• Tests should not depend on other tests– Setup and tear down of test data done within each test– Share test components (as you would do with ‘real’

production code)– Trade-off between:

• No code duplication yet somewhat more complex fixtures

• Easy-to-grab simple fixtures but a lot of them (and duplication)

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Keep It Manageable

• Focus on functional coverage, not technical coverage• Say 40 user stories, 400 tests

– Do I have relatively more tests for the more important user stories?– How do I link tests to user stories/features/fixes?

• Metrics– Number of tests– Number of tests that have not passed in <time>– Flaky tests– Duration

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Slice and Dice

• Use appropriate labels in your test code– Responsible team– Topic– Functional area– Flaky– Known issue– etc.

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Best Practices for Test Execution in Jenkins

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Jenkins Testing Basics

• Tilt the pyramid …

• … and use this as the guiding principle to set up your Jenkins test jobs “left to right”

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Organizing Test Jobs in Jenkins

1. Create unique artifacts and fingerprints to monitor what you are pushing across your pipeline

2. Treat different platforms (e.g. browsers) as different tests, handled by different jobs

3. Well-known plugins:– Multi-job– Copy Artifact– Workflow

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Organizing Test Jobs in Jenkins

4. Keep Jenkins jobs sane and simple– Ergo: execute shell scripts from your Jenkins jobs

5. Shell scripts are parameterized

6. Parameters are fed to individual test tools– FitNesse labels, Cucumber labels, etc. etc.

7. Shell scripts placed under version control– Managed by the team as any other source code

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Example Job Distribution

Build Deploy Int. Tests Test Test Test Perf. Tests

Build Deploy Int. Tests Test

Test

Test

Perf. Tests

Beware of scattered result qualification

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Distributing Tests Across Jobs

• Radical parallelization using cheap andcheerful throw-away environments– Especially when environments (e.g. containers)

lie at your fingertips

• Jobs should not depend on other jobs• Test jobs are your “eyes and ears” – optimize for

them!

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Example Job Distribution

Build Deploy

Int. Tests

Test

Test

Test

Perf. Tests

?

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Challenge: Scattered Results

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Supporting Test Analysis

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Making Sense of Test Results

• Real go/no go decisions are non-trivial– No failing tests– 5 % of failing tests– No regression (tests that currently fail but passed previously)– List of tests-that-should-not-fail

• Need historical context• One integrated view• Data to guide improvement

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Making Sense of Test Results

Executing tests from Jenkins is great, but…• Different testing jobs have their share of Jenkins

plugins• Historic view merely available per job, not across

jobs• Pass/Unstable/Fail is too coarse

– How to do “Passed, but with known failures”?

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Making Sense of Test Results

• Ultimate analysis question (“are we good to go live?”) is difficult to answer

• No obvious solution for now, unless all your tests are running through one service

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Example Case Study

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• Started with 1 project containing all tests• Sharing knowledge• Structured the same as our use cases, i.e.

• WebshopSuite.BusinessAccountSuite.UseCase1500• Nightly runs from the beginning• Indication by labels (“nightly”)• First sequential per application

• WebshopSuite• Later parallel, split by functional area

• WebshopSuite.BusinessAccountSuite.*

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FitNesse Implementation

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Check-inStep

Tools

Environment git-server

Build Unit tests Build EAR Deploy

Jenkins-server

Smoke Test

Dedicated Team Server

Build Deploy

Code review

Example Pipeline

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System TestStep

Tools

Production Acc. Test

Deploy to Chain

Chain Test

Security TestStep

Tools

Environment Jenkins server and Sonar server

Remarks

Source Code Quality TestStep

Tools

Dedicated Team Server

Chain {1-5} Chain {1-5}

Testing

Environment

Dedicated Team ServerEnvironment

End to End Testing

Smoke Test

Chain {1-5}

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Test Analysis: Homebrew

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Test Analysis: Custom Reporting

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Test Analysis: Custom Reporting

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Summary

• Testing = Automation– Testers are developers

• Structure and annotate tests– Conway’s Law for Tests– Link to functions/features/use cases

• Radical parallelization– Throwaway environments

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Summary

• Keep Jenkins jobs simple• Keep Jenkins jobs independent• Track SUT with fingerprints• Invoke test tools via plugins or version-controlled

scripts• Parameterization!• Parallelize & optimize

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Summary

• CD = Speed + Quality = Execution + Analysis• Making sense of scattered test results is still a

challenge• Need to figure out how to address real world go/no

go decisions

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What’s Next?

• Visit http://tiny.cc/webinar-xebialabs for a webinar by CloudBees and XebiaLabs demonstrating the key value of CD and go-live decisions

• Read more on the testing challenges in CD– http://tiny.cc/ta-and-cd

• Try XebiaLabs’ XL TestView solution to bringquality into the heart of your CD initiative– http://tiny.cc/xl-testview

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