#end to end testing

[zelkams-art]

in all timelines in all possibilities only you can show me this

[yethiconsulting]

Unlocking Productivity with Robotic Process Automation

In an era where efficiency is critical, Robotic Process Automation (RPA) has emerged as a game-changer for businesses aiming to unlock new levels of productivity. RPA allows organizations to automate repetitive, rule-based tasks by deploying software bots that work around the clock with speed and precision. This not only accelerates processes but also reduces operational costs and minimizes human error.

By taking over tasks such as data extraction, report generation, invoice processing, and customer onboarding, Robotic Process Automation frees employees from mundane workloads. This enables teams to shift their focus to strategic, high-value activities like innovation, decision-making, and customer engagement. As a result, businesses experience higher output, improved accuracy, and faster service delivery.

One of RPA's strongest benefits is its ability to scale—bots can be quickly deployed across departments without requiring major changes to existing IT infrastructure. This makes implementation fast, cost-effective, and low-risk.

From finance and HR to supply chain and customer service, RPA is transforming how work gets done. Organizations that adopt RPA early are not just improving productivity—they’re gaining a competitive edge. Unlocking productivity with RPA isn't just about doing things faster—it's about working smarter and laying the foundation for digital transformation.

[biggest-gaudiest-patronuses]

hero/villain showdown but one of them has a spontaneous medical emergency and the battle gets put on hold while their archnemesis drives them to Urgent Care

[pujacontrol]

Understanding the Difference between System Testing and End-to-End Testing 

In the realm of software development, testing plays a crucial role in ensuring the quality and reliability of the final product. Among the various types of testing methodologies, two terms often encountered are System Testing and End-to-End Testing. But what sets them apart? Let’s dive in and explore the disparities between these two testing approaches.    Introduction  Before delving into the nuances, let’s start with the basics. System Testing and End-to-End Testing are both integral parts of software testing, each serving distinct purposes in ensuring the functionality and reliability of a software system.    System Testing  System Testing involves evaluating the system as a whole to ensure that all components work together seamlessly. It focuses on testing the entire software application, including its interfaces with external systems. Think of it as examining the car’s engine, transmission, and other components to ensure they function together effectively.    End-to-End Testing  End-to-End Testing, on the other hand, is a comprehensive testing approach that examines the entire software application flow from start to finish. It simulates real-world scenarios to validate the system’s functionality across different modules and systems. Picture it as taking a road trip from point A to point B, testing every aspect of the journey to ensure a smooth ride.    Key Differences  Scope  1) System Testing primarily focuses on individual components or modules within the software system. It ensures that each component performs its intended functions correctly.    2) End-to-End Testing, however, encompasses the entire application flow, including all interconnected components and systems. It verifies the system’s behavior from the user’s perspective, covering multiple modules and interfaces.    Complexity  1) System Testing tends to be less complex compared to End-to-End Testing since it deals with testing individual components in isolation.    2) End-to-End Testing is inherently more complex as it involves testing the entire system in a real-world environment, including various interactions and dependencies between different modules.    Dependency  1) In System Testing, dependencies on external systems or components are often mocked or simulated to isolate the testing scope.    2) End-to-End Testing relies on real-world environments and interactions between different systems, making it dependent on the availability and stability of external dependencies.    Time and Resources  1) System Testing generally requires fewer resources and can be executed relatively quickly since it focuses on specific components or modules.    2) End-to-End Testing demands more time and resources due to its comprehensive nature, involving testing across multiple modules and systems.    Stakeholder Involvement  1) System Testing primarily involves developers and testers who are responsible for ensuring the functionality of individual components.    2) End-to-End Testing often requires involvement from various stakeholders, including developers, testers, business analysts, and end-users, to validate the system’s behavior in real-world scenarios.    Risks and Benefits  1) System Testing helps identify and mitigate risks associated with individual components, ensuring they meet specified requirements.    2) End-to-End Testing provides a more holistic view of the system’s behavior, uncovering potential issues related to integration, data flow, and user interactions.    Challenges  Both System Testing and End-to-End Testing come with their own set of challenges. System Testing may overlook integration issues, while End-to-End Testing can be time-consuming and complex to implement.    Conclusion  In conclusion, while both System Testing and End-to-End Testing are essential components of software testing, they serve different purposes and have distinct scopes. Understanding these differences is crucial for ensuring thorough testing and delivering high-quality software products.

Also read: Integrating ICT Circuit for Enhanced SCADA Control Systems

[qualityrain]

[carolchung-eng]

Playwright Testing (Initial Thoughts)

These are my initial thoughts of the Playwright automated testing tool (end-to-end) - generally positive. I have admittedly only skimmed the surface of its capabilities as it was included in the boilerplate on a template I've been using (epic stack by Kent C. Dodds - todo add link to repo). Here is a summary of this post:

What is Playwright?

What does it replace or compare to?

What does Playwright do well?

What are weaknesses of Playwright?

Playwright is a tool for automated end-to-end web application testing. It was developed by Microsoft and initially released in 2020. Playwright is comparable to earlier testing tools like Cypress or Selenium. In my experience, using the Python client for Selenium was pretty complicated because the documentation was not very clear and I felt like I had to set up tests in a trial-and-error manner. I have not used Cypress personally and so cannot speak to how they compare but have read that Cypress can take some time to set up.

These are some highlights or features that make Playwright a stand-out tool:

Provides CodeGen functionality or a UI recording feature which converts user actions to code necessary to create a test

Flexible definition of HTML element locators

Support for testing in a headless browser (results in better testing performance)

Support for running tests in parallel

Cross browser testing support (chromium, firefox, webkit)

Support for running tests in UI mode (provides an interface and access to review events for debugging faulty tests)

Right now I don't have any complaints about using Playwright but have not delved deeply into writing complex tests with it. I used it mainly through a boilerplate template, which made it easy to try out with little overhead and then captured another test using CodeGen.

[illusioncanthurtme--art]

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I'm honestly embarrassed by the amount of effort I'm putting into this. But in my opinion, we're down to the ultimate battle, and I gotta pull out the big guns. (Kinda like ford here)

A lot of young fords ramblings were inspired by stuff people said in discord. I paraphrased a lot of it from @curiouscatastrophe

So far, Ford has been in the dark as to who the Father would be. He's going to confront bill in the next one.

Cipher says: VOTE FORD - YOUR LIFE DEPENDS ON IT.

[van1lla-cake]

drew some drones that do the murder

the full lineup:

[lucabyte]

even dogs pass the mirror test

[kayatoastkkat]

hello tumblr isat fandom. pushes this in front of you and runs away

[charcarts]

In another life, I would have really liked just frolicking with you 🐴🦄

[homosexualslug]

the difference between these scenes is killing meeeeee

[yethiconsulting]

Common Pitfalls in App Test Automation and How to Avoid Them

App test automation can unlock faster releases and better quality—but only if done right. Many teams jump in with good intentions, only to hit common pitfalls that slow progress or waste resources. This blog highlights frequent mistakes and how to sidestep them.

Automating Everything:

Not all tests need automation. Trying to automate UI-heavy or rarely-used scenarios can increase maintenance. Focus on high-value, repeatable tests like regressions and smoke tests.

Poor Tool Selection:

Choosing a tool that doesn’t align with your app’s platform, tech stack, or team skills leads to frustration. Evaluate tools based on compatibility, learning curve, and integration capabilities.

Lack of Test Design Strategy:

Writing flaky, unstructured tests results in unreliable outcomes. Implement a solid test design pattern (e.g., Page Object Model) and follow naming conventions.

Ignoring Maintenance:

Automated tests need regular updates. If ignored, they become outdated and produce false positives or failures.

Skipping CI/CD Integration:

Running tests manually defeats the purpose. Integrate automation into your CI/CD pipeline to ensure continuous, consistent testing.

By avoiding these pitfalls, teams can create a sustainable and scalable automation strategy that supports rapid, high-quality app development.

[journey-to-the-attic]

"karasu search how 2 cheer human up"

"karasu search difference between sad human and zoning out human"

"karasu search how long is it safe for humans to zone out for?"

(+ a longer look at each scene:)

[webomates]

End-to-End Testing vs Regression Testing

Software testing is a crucial step in ensuring an application’s reliability and functionality. As you increase test coverage, the quality of your application testing will increase. Regression testing and end-to-end testing focus on several testing facets to guarantee complete end-user satisfaction.

While End-to-End Testing focuses on the testing of the entire user flow and integrated components, Regression Testing targets specific functionalities and validates the impact of code changes. You need to understand their differences to implement an effective testing strategy.

Key Differences

When do you need End-to-End Testing?

Pro Tip: Webomates offers code coverage as an optional add-on to AI test automation. Follow these 8 best practices to master end-to-end testing to ensure a seamless user experience and better product quality.

When do you need Regression Testing?

Regression testing is more like a time traveler — traversing across different versions of the application, ensuring that the previous application functionalities are still preserved today even after new changes.

Pro Tip: The process of regression testing includes selecting the right test cases, and determining the testing frequency and types of regression required to be carried out. Webomates helps you scale up by getting build checks done via its 3 types of regression testing services that provide the maximum quality.

How can Webomates Help?

Regression testing and end-to-end testing both play crucial roles in assuring a seamless and error-free user experience, all while protecting your application against potential vulnerabilities.

As a cutting-edge cloud-based Testing as a Service platform, Webomates uses AI to reimagine the testing process. The patented tool like AI Test Strategy and Creator tool help you in devising a well-rounded test strategy for the software. By creating and automating the appropriate test cases, their AI Modeller engine can help you cut the human work required to write or maintain the test suite by more than 50%.

To find out more about what Webomates Intelligent Testing services can do for your business, get In touch with us today. Please click here and schedule a demo, or reach out to us at info@webomates.com

[poorly-drawn-mdzs]

Vibes based grading system.

(for @epistemologys, who wanted some post-canon, teacher WWX)