Technical Discussion

We’ve almost made it to the end of 2024!What are your predictions for 2025?If you could response in the format:Title: a thought provoking titleExcerpt: (summarise it in 1 sentence)Description: (1-3 paragraph description)

People always make trends posts about 2024 2025 etc and they all have the same trends on them. AI Automation Performance etc …So my questions towards you is what are you seeing right now as a trend? What’s popped up more often?For me it would be A11Y - Accessibility testing, I see more and more people investing into it, many posts of it online. It might just be due to me not having much experience in it compared to other things.What are you spotting? 

1. Which approach in Generative AI is most effective for reducing false positives in automated test results?A. Supervised learning with predefined labels B. Reinforcement learning with continuous feedback loops C. Rule-based automation integrated with AI D. Traditional statistical analysis2. When leveraging Generative AI for code suggestions in a CI/CD pipeline, what is the key risk associated with hallucinations in Large Language Models (LLMs)?A. Excessive computational overhead B. Generation of incorrect or insecure code snippets C. Increased test execution time D. Lack of cross-platform compatibility 3. In the context of DevTestOps, what makes synthetic data generation using Generative AI superior to traditional data augmentation?A. Ability to mimic real-world scenarios without bias B. Faster generation time with minimal resources C. Elimination of manual effort in dataset creation D. Enhanced visualization for data analysis 4. Which is the most significant barrier to scaling Genera

As test suites grow, maintaining automated tests and handling script breakages can become challenging, especially with frequent application updates. I've read about AI-based tools that automate test maintenance and implement self-healing capabilities, which adapt scripts to changes in the UI or functionality.Could you share your experiences using these AI-driven solutions for automating test maintenance? Specifically, I'm curious about:How effective they’ve been in reducing manual intervention for script fixes Any free tools or open-source alternatives you've tried and their limitations How these tools integrate with existing automation frameworksI’d love to hear about any success stories or challenges you’ve faced while using them!

How do you setup up a test automation project? Do you have a template that you use? Do you google each time you want to start. Do you reach for the documentation? I am curios what is your approach. Also, here is a link to a new resource I found on the topic that might help organize the test project creation, especially if you are just starting out  

You're testing a payment gateway API responsible for handling financial transactions. Its primary function is to ensure that funds are transferred only when the account balance of the user is sufficient. In the test cycle, the following scenario was observed.Two simultaneous requests from two different devices for the same transaction-drawing money, for example, ₹10,000-an API processes both requests, deducting ₹20,000 from the account while it holds only ₹15,000.

What do you believe is the most significant factor contributing to faster and higher-quality software releases? Please select the option that you consider most important.

It sparked various questions about the process behind what to do with critical production bugs. I’m curious to know: What steps do you take when you discover a critical bug in production?Who owns what and who does what?Who is kept in the loop?What announcements are made?What official documentation supports the process?What’s your experience contributing to disaster recovery processes and documents?What did you learn from the critical bug in production? What did you do differently for the next one? (if indeed there was “a next one”)

Task: Add automated tests to your project's CI pipeline and ensure they run automatically with each code change.  Capture a screenshot of your CI tool running automated tests. 

Task: Explore strategies for managing test data effectively in a DevOps environment. Implement one such strategy in your project.  Capture: A screenshot or description of your test data management approach. 

What is the most important thing that ‘Good’ software has and ‘Bad’ software lacks?

We are building a stand-alone web and mobile application that, when finished, will require one of our order modules to have as one of its features an editable PDF. Since the third-party PDF editor we could find already supports a strong ability to edit-the specifics being Adobe Acrobat-we are challenged with how we will ensure that changes the user saves will be written into our application database rather than into the third-party editor system.Our development team is facing an impasse in the effort to implement this functionality. Do you have suggested approaches or tools allowing PDF editing with direct data saving to our database? Thank you in advance for any suggestions or best practices you could share.

I Learned the Course of QA Automation Testing using Selenium about a year ago but still I didn‘t get a Job. Please assist me to Start Career as a Fresher. of Automation Tester.

Which test automation tool has the most weekly downloads according to npmtrends? A) Cypress B) Playwright C) Puppeteer

I’m curious to know what’s the one QA tool that has saved you the most time during your testing process? Whether it’s for test automation, bug tracking, performance testing, or something else, I’d love to hear what tool you can’t live without and why it stands out to you.

Test-Driven Development (TDD) and Behavior-Driven Development (BDD) are two popular approaches to software development that prioritize testing and quality assurance. TDD focuses on writing tests before writing codeBDD focuses on defining the behavior of the system before writing code. Which one do you use? Do you use either, or a third one?

In the world of testing, oh what a sight,There are development methodologies left and right!Waterfall, Agile, DevOps, and more,Each with its own unique score. Waterfall's like a river, flowing down,Each phase completed before the next comes 'round.Design, coding, testing, all in a row,In the end, a product that's good to go. Agile's more like a jungle, wild and free,With sprints and stand-ups, and lots of team camaraderie.Iterations and feedback, they all do their part,To create a product that's work of art. DevOps is like a machine, moving fast,Continuous integration, deployment, and testing that lasts.Automation's the key, with pipelines in play,To deliver software every single day. But which one's the best, you may ask,Well, that depends on the testing task.Each has its own strengths and flaws,So pick the one that suits your cause. In the world of testing, there's no one size fits all,So experiment and find the right call.And when you've found the right way to test,Your product will

Hi Team,Can you please help me how i can automate any desktop or window-based application using TSOCA commander ? 

 In this video, Kshitij Nigan (happy) , a Senior Product Security Engineer at Tricentis with 11 years of experience, discusses the power of DevSecOps in software development. He highlights its cultural impact, emphasizing security as a shared responsibility. @nigamelastic also covers key practices like vulnerability detection, compliance, and proactive security. This video is a must-watch for those interested in integrating security into the development process. 

 Are you ready to supercharge your coding journey? @IOan brought a great opportunity.  From Ioan:  I am excited to share a fantastic opportunity for the Shiftsync community to enhance their skills and master the art of GitHub through a series of FREE courses.These courses are designed to empower you with the knowledge and expertise needed to make the most out of GitHub for your projects.  Unlock the Power of GitHub with These Free Courses:1. GitHub Essentials for Beginners:Dive into the basics of GitHub with this beginner-friendly course. Learn how to create repositories, manage branches, and collaborate effectively with other developers. Perfect for those new to version control or looking to solidify their understanding.2. Mastering Pull Requests and Code Reviews:Pull requests are at the heart of collaboration on GitHub. This course will guide you through the ins and outs of creating pull requests, handling code reviews, and ensuring your contributions align with best practices. Take

Hey ShiftSyncers,Quick one: Anyone doing Advent of Code by Eric Wastl? For those who might be unfamiliar, Advent of Code is an annual coding event that involves solving a series of programming puzzles throughout December, each becoming progressively more challenging. For those already diving into the Advent of Code, I wish you the best of luck! Feel free to keep us posted on your progress, share interesting puzzles, or ask for help if needed. 

When faced with testing large, complex tickets at the last minute, it’s easy to miss important edge cases, which can lead to undetected issues. How do you make sure you thoroughly cover all possible scenarios, including edge cases, given the limited time? What strategies or tools do you use to track these cases, and how do you prioritize the most critical ones to ensure comprehensive testing under pressure?

I’m currently facing significant challenges with our e-delivery process that seem to impact the reliability and speed of our software releases. Despite thorough testing and successful build completions, we often encounter issues during deployment that lead to delays and frustration among team members and stakeholders.Here are some specific challenges we're experiencing:Inconsistent Build Artifacts: Different environments sometimes deploy artifacts that don't match what was tested, causing discrepancies in behavior. Communication Gaps: There seems to be a disconnect between the development and QA teams regarding the status and readiness of builds for delivery. Deployment Failures: We often see unexpected failures during e-delivery that weren't caught during testing, which leads to rollbacks and increased downtime. Dependency Management: Handling external dependencies (like APIs and libraries) can be tricky, and changes in those can break our deployments unexpectedly.I would love to hear

We recently deployed a feature that passed all tests in our Acceptance environment (functional tests, regression, smoke tests), but after deployment to Production, we encountered issues such as broken functionality, unexpected errors, and performance slowdowns.Here’s the setup:Acceptance and Production environments are as close to identical as possible (same configurations, database versions, and server setups). Automated and manual tests ran successfully in Acceptance. The feature in question interacts with both third-party APIs and a legacy system.However, after deployment to Production, users are facing:API timeouts and failed calls to third-party services. Slower performance in certain areas of the application. Data inconsistencies when interacting with the legacy system.Has anyone experienced a similar issue where everything works fine in Acceptance, but things fall apart in Production? What are some potential causes or overlooked areas that could explain this discrepancy?I’m part

What conferences are you attending this Year?Tell the community so that we may see each other there.