SlideShare ist ein Scribd-Unternehmen logo
Sebastian Bauer | inovex GmbH
Dominik Jungowski | inovex GmbH

Mythen und Fakten über
Behavior Driven Development
@litervollmilch
 Scrum Coach bei inovex GmbH

       Spielt mit Autos

       passiondriving.de
@djungowski
Scrum Coach bei inovex GmbH

      Spielt mit Platten

        niknovo.com
Von TDD zu BDD




           © flickr / krss
Warum
verhaltensgetrieben?


                   © flickr / Kaptain Kobold
Gherkin




          © flickr / Mothlike
Annahme /
 Umwelt         Given


       Aktion             When




Erwartetes      Then
 Ergebnis
                        © flickr / calsidyrose
// Negativtest
Scenario: Did-you-mean for search without
results
   Given A user is on the English Wikipedia
   When he searches for „wurstschnecke“
   Then there should be no results
   And there should be a Did-you-mean
	

 suggestion for „fürsteneck“
// Positivtest
Scenario: Search results for successful search
 Given A user is on the English Wikipedia
 When he searches for „german brewery“
 Then he should find „Deutsches
Brauereimuseum“
 And he should find „Beer in Germany“
Live Demo mit
     Behat

                © flickr / skinner08
© flickr / Sebastian Bergmann
BDD als Agile
Dokumentation


                 © flickr / Guillaume Brialon
Warum in agilen Teams?
© flickr / inf3ktion
                       Wo macht es Sinn?
Wo macht BDD keinen
       Sinn?
Live Demo Code:
https://github.com/sebauer/IPC-BDD-Demo



Bitte bewertet die Session:
        http://joind.in/talk/view/7335
                                         © flickr / skinner08
@litervollmilch   @djungowski

Weitere ähnliche Inhalte

Mehr von inovex GmbH

Interpretable Machine Learning
Interpretable Machine LearningInterpretable Machine Learning
Interpretable Machine Learning
inovex GmbH
 
Deep Learning for Recommender Systems
Deep Learning for Recommender SystemsDeep Learning for Recommender Systems
Deep Learning for Recommender Systems
inovex GmbH
 
Representation Learning von Zeitreihen
Representation Learning von ZeitreihenRepresentation Learning von Zeitreihen
Representation Learning von Zeitreihen
inovex GmbH
 
Performance evaluation of GANs in a semisupervised OCR use case
Performance evaluation of GANs in a semisupervised OCR use casePerformance evaluation of GANs in a semisupervised OCR use case
Performance evaluation of GANs in a semisupervised OCR use case
inovex GmbH
 

Mehr von inovex GmbH (20)

lldb – Debugger auf Abwegen
lldb – Debugger auf Abwegenlldb – Debugger auf Abwegen
lldb – Debugger auf Abwegen
 
Are you sure about that?! Uncertainty Quantification in AI
Are you sure about that?! Uncertainty Quantification in AIAre you sure about that?! Uncertainty Quantification in AI
Are you sure about that?! Uncertainty Quantification in AI
 
Why natural language is next step in the AI evolution
Why natural language is next step in the AI evolutionWhy natural language is next step in the AI evolution
Why natural language is next step in the AI evolution
 
WWDC 2019 Recap
WWDC 2019 RecapWWDC 2019 Recap
WWDC 2019 Recap
 
Network Policies
Network PoliciesNetwork Policies
Network Policies
 
Interpretable Machine Learning
Interpretable Machine LearningInterpretable Machine Learning
Interpretable Machine Learning
 
Jenkins X – CI/CD in wolkigen Umgebungen
Jenkins X – CI/CD in wolkigen UmgebungenJenkins X – CI/CD in wolkigen Umgebungen
Jenkins X – CI/CD in wolkigen Umgebungen
 
AI auf Edge-Geraeten
AI auf Edge-GeraetenAI auf Edge-Geraeten
AI auf Edge-Geraeten
 
Prometheus on Kubernetes
Prometheus on KubernetesPrometheus on Kubernetes
Prometheus on Kubernetes
 
Deep Learning for Recommender Systems
Deep Learning for Recommender SystemsDeep Learning for Recommender Systems
Deep Learning for Recommender Systems
 
Azure IoT Edge
Azure IoT EdgeAzure IoT Edge
Azure IoT Edge
 
Representation Learning von Zeitreihen
Representation Learning von ZeitreihenRepresentation Learning von Zeitreihen
Representation Learning von Zeitreihen
 
Talk to me – Chatbots und digitale Assistenten
Talk to me – Chatbots und digitale AssistentenTalk to me – Chatbots und digitale Assistenten
Talk to me – Chatbots und digitale Assistenten
 
Künstlich intelligent?
Künstlich intelligent?Künstlich intelligent?
Künstlich intelligent?
 
Dev + Ops = Go
Dev + Ops = GoDev + Ops = Go
Dev + Ops = Go
 
Das Android Open Source Project
Das Android Open Source ProjectDas Android Open Source Project
Das Android Open Source Project
 
Machine Learning Interpretability
Machine Learning InterpretabilityMachine Learning Interpretability
Machine Learning Interpretability
 
Performance evaluation of GANs in a semisupervised OCR use case
Performance evaluation of GANs in a semisupervised OCR use casePerformance evaluation of GANs in a semisupervised OCR use case
Performance evaluation of GANs in a semisupervised OCR use case
 
People & Products – Lessons learned from the daily IT madness
People & Products – Lessons learned from the daily IT madnessPeople & Products – Lessons learned from the daily IT madness
People & Products – Lessons learned from the daily IT madness
 
Infrastructure as (real) Code – Manage your K8s resources with Pulumi
Infrastructure as (real) Code – Manage your K8s resources with PulumiInfrastructure as (real) Code – Manage your K8s resources with Pulumi
Infrastructure as (real) Code – Manage your K8s resources with Pulumi
 

Mythen und Fakten über Behavior Driven Development