LambdaTest Webinar Home / Video /

Clean Coding Practices for Test Automation: Part 2 | Voices Of Community:Ep VII | LambdaTest Webinar

Clean Coding Practices for Test Automation: Part 2 | Voices Of Community:Ep VII | LambdaTest Webinar

...Playlist

...

About The Video

In this high-impact session, 𝑺𝒂𝒊 𝑲𝒓𝒊𝒔𝒉𝒏𝒂, Lead Consultant, ThoughtWorks, and 𝑺𝒓𝒊𝒏𝒊𝒗𝒂𝒔𝒂𝒏 𝑺𝒆𝒌𝒂𝒓, Lead Consultant, ThoughtWorks with host 𝑴𝒂𝒏𝒐𝒋 𝑲𝒖𝒎𝒂𝒓, VP-Developer Relations at LambdaTest, look at real-world examples to present clean coding practices for test automation. By the end of this webinar, you'll have the competence to analyze prevailing test automation code, detecting indications of flawed code and correcting them accordingly.

Video Chapters

00:00:00 Introduction

00:05:20 Clean Coding Practices

01:18:36 QnA

01:30:06 Closing Words

Key Topics Covered

Introduction to LambdaTest for Screenshots: The video starts with an overview of Lambda Test's ability to take screenshots of web pages, highlighting its utility in testing and development.

Taking Visible Portion Screenshots: It explains how to capture screenshots of the visible portion of a webpage using Lambda Test.

Full Page Screenshots: The tutorial progresses to demonstrate how to take full page screenshots, capturing the entire content of a webpage beyond what is immediately visible.

Element-specific Screenshots: The video discusses how to target and capture screenshots of specific elements or regions within a webpage, using web element locators.

Masking Sensitive Information: A unique feature covered is the ability to mask sensitive information in screenshots, such as user credentials on a login page, to protect privacy during presentations or client demos.

Hiding the Caret Symbol: Lastly, the video shows a trick to hide the caret symbol in screenshots for a cleaner presentation.

Related Blogs & Hubs

Clean Coding Practices for Test Automation

17 Benefits of Automation Testing for a Successful Release

30 Top Automation Testing Tools In 2022

More Videos from LambdaTest Webinar