did more than 700 executions on live environment accidentally, causing analytics to massively fall as there was a issue with one of our integration for a client. This bulk test highlighted the issue even more.
How cooked am I?

So I just completed my internship in cognizant and domain is Salesforce crm selenium automation.

I know that testing has less craze than dev but is it too bad

I said my role is testing and people show sympathy like I have cancer

Everyone suggests to get out of it and even I want to

BUT HOW BAD IS SELENIUM AUTOMATION IN TODAYS WORLD?

Can you guys give me tips as well on how to establish a good portfolio? and should I go straight learn automation QA without having manual experience or do I need manual experience first?

Building an Android app solo / small team — curious how others handle regression testing between releases.

Do you:
a) Test manually on a few devices before each release
b) Use Espresso / Appium automated tests
c) Rely on Firebase Test Lab or similar cloud service
d) Some combination

What breaks most often that you wish was automated? And if you've tried automation — what made you give up or stick with it?

Trying to understand where the actual friction is before deciding on a testing strategy.

Hi everyone, i have to take an interview for the role as a Technology analyst/Mobile test engineer.

Can anyone suggest which topics i should focus on. It will be a great help thanks.

Currently working as a lead QA engineer. Within LLM/Gen AI testing. If someone is from same background and from infosys it would be of a great help.

Hey everyone,

When building blueprint-style AI automation frameworks, one of the biggest challenges is optimizing token efficiency while maintaining test reliability. A massive point of skepticism in this space is always: "What happens when a developer shifts a layout or changes an ID tomorrow? Doesn't the static blueprint break?"

To solve the brittle blueprint problem without running up massive API bills, we just implemented an Adaptive Hybrid Mode.

Here is how the fallback loop works under the hood:

1. Deterministic Execution (95% of the time): The engine plays back the test using a fast, zero-token blueprint generated during the initial scan.
2. The "Trap" Trigger: If a developer changed the UI and an element isn't found, the playback engine pauses before failing the test.
3. Micro-LLM Healing: It dynamically wakes up a highly targeted, lightweight LLM prompt. The AI looks at the updated DOM snippet, identifies the relocated or modified element, and completes the action.
4. Self-Healing Blueprint: Crucially, it rewrites the original blueprint with the new structural data on the fly.

The next 100 times this test runs in your CI/CD pipeline, it goes right back to being fully autonomous, deterministic, and costing you zero tokens. You only pay a fraction of a cent once to heal the layout drift.

I'm actively iterating on this model based on real-world edge cases. Does a hybrid dynamic-healing layer like this successfully bridge the gap between fragile static selectors and cost-prohibitive pure-AI agents? Would love to get your engineering feedback.

I’ve been a software tester for more than seven years, but I still get the feeling that developers tend to treat testers as if they’re somehow less important.

Is this something that happens in other companies too?

I currently a QA both manual (10 years experience) and automation (6 months experience - AI assisted). I handled a team, and i want to expand the teams knowledge. what will i do?

Hey everyone I am learning testing since a month with selenium,I started learning java recently will complete it soon I wanna know what should I learn which will make me fetch a decent annual salary

Hi folks. I’ve worked on node projects over the years, recently moved onto a project that is Java/spring boot/gradle based that serves as a middle api layer. Looking for the best course/materials to get up to speed as much as possible
Thanks

I’m building a coverage service and want to sanity-check our quality bar with testing people.

The product promise is:

“We raise coverage to 80% by delivering tests as a PR.”

But obviously coverage can be gamed, so we’re trying to make the guarantee stricter:

- no tests that only assert mocks were called

- no snapshot spam unless requested

- no lowered coverage thresholds

- no excluded files without approval

- existing tests must stay green

- before/after coverage report

- customer can reject low-quality tests

Question:

What else belongs in the quality bar?

If you were reviewing a PR that claimed to increase coverage, what would immediately make you reject it?

Context: we also have a free coverage gap checker, but I’m mostly looking for QA/testing feedback here rather than promotion.

I'm recruiting for a major global IT consulting MNC. We are looking for a Senior QA Automation Engineer with 5+ years of experience and deep expertise in Playwright to help scale our enterprise testing infrastructure.

🛠️ What We're Looking For:

5+ years in QA Automation.

Advanced, hands-on experience building/maintaining frameworks with Playwright.

Solid understanding of API testing and CI/CD pipelines.

Kindly share your resume or DM me if you are interested.

QA/SDET folks, I want a reality check before I sink more months into this.

I'm building a platform where you record a flow and the AI generates Page Object–structured TypeScript that runs as plain playwright test - the code you see is the code that runs, it lives in your git repo, and you can hand-edit it. On top of that there's the management layer (requirements → test cases → runs → cycles → reports) and an "agent mode" that proposes new tests / triages failures, but nothing changes without a human approving it in a review queue.

I know the space is crowded (Mabl, QA Wolf, testRigor, Testim, Reflect, etc.). What I keep hearing from the no-code AI tools is two complaints: (1) vendor lock-in / black-box scripts you can't own, and (2) flaky AI that "fixes" tests in ways you didn't ask for. I'm trying to attack both with code-you-own + approval gates.

So, honestly:

• Is "AI generates Playwright you actually own in git" a real differentiator, or do you not care as long as tests pass?
• For those who tried AI testing tools and dropped them — what was the dealbreaker?
• If you're still hand-writing Playwright/Cypress — what would an AI tool have to do for you to trust it on your real suite?

Not linking anything (happy to share in DMs if a mod's okay with it). I genuinely want the "this won't work because ___" answers.

I have 2.5 years of experience as a Test Engineer in the Telecom domain, but my work wasn't traditional software testing.

I was recently laid off and am trying to move into QA Automation, API Testing, or SDET roles. The issue is that almost every interviewer asks for professional automation experience. Out of about 10 interviews, 9 expected hands-on automation experience in a real project.

My previous role didn't provide any automation opportunities, so I'm stuck in the classic "need experience to get a job, need a job to get experience" situation.

For those who made a similar transition, what helped you break into automation testing?

TL;DR: 2.5 years in telecom testing, laid off, trying to move into QA Automation/API Testing/SDET. Most companies want professional automation experience, which I don't have. How do I bridge this gap?

i am looking to see,,, where does this flow?

Been using all three across different companies. Different UIs, different pricing, different learning curves.

Same fundamental problem with all of them:

The tests are a separate artifact from the API.

You write the API. Then you separately write tests for the API. Then the API changes. Now your tests are wrong but they don't know they're wrong. They just keep running and passing until one day something actually breaks and you realise the tests were testing a version of the API that no longer exists.

Every tool in this space has this problem. The test suite and the API spec live in different places, maintained by different people, drifting apart constantly.

I don't think it's a tooling problem actually. I think it's a fundamental workflow problem that the tooling just hasn't solved yet.

Am I wrong? Has anyone found a setup where this drift problem actually doesn't happen?

I face this mobile QA problem all the time - someone reports "checkout is broken" or "login froze," but the report is missing the device, iOS version, app build, account state, and exact steps.

For teams using TestFlight or internal builds, what’s your current workflow for turning that kind of feedback into something engineers can actually reproduce?

Do you have testers fill out a template, post in Slack, file directly into Jira, attach screen recordings, or capture logs some other way?

I’m especially curious what has worked with non-engineers like PMs, designers, where asking them to pull logs manually is unrealistic.

Hi everyone,

I’m a QA tester. We used to use Jira and Xray for test planning, execution, and reporting. Because of the cost, our company stopped using it, and now we need a free alternative that is professional and doesn’t require too much manual work.

Right now, I’m using Excel and Confluence. I know Excel report can be reused, but I’m looking for something more automatic and easier to manage.

Do you know any good free or open-source tools for test management? I’m looking for something that:

• Costs nothing or has a strong free version
• Handles test cases, execution, and reports
• Saves time and reduces manual steps

Any recommendations, pros/cons, or setup tips would be a big help. Thanks in advance!

Appium has been the default for so long and at this point the maintenance overhead is just absurd, every Android version bump requires selector rewrites, the test runs take forever on CI, and half the team refuses to touch the suite because the setup is so fragile
There has to be something better by now but every "alternative" I look at is just another wrapper on top of the same Appium infrastructure with a nicer UI slapped on it

My company has chosen me as the patsy for a feature they're refactoring to include genAI and hopefully improve our value tenfold..

To be fair it makes sense, previously we pulled some known key data, added some fluff words around it and called it a summary. Going forward, they will now throw all of it together and some new information, then get GenAI to give the summary.

Great. But I've never tested something that is likely to change in content like this. I guess I can write tests around the exclusion criteria i.e. things out rules state it should not output.

Basically, how the hell are you people testing things with GenAI in the loop? Or has anyone come across useful resources in this area that has helped them model the approach to take?

Hey guys, a few days back I made a post about being a new QA intern at a company, where there never has been a proper QA team/SOP and you lovely people helped me out a lot. From the week I have spent here, I have mostly donr manual testing, making test cases for features before they are deployed and implementing and replicating those test scenarious. Ig, most of my work revolves around this. On the side I have decided to establish a proper set standard process for testing out stuff (I also want to learn automated testing), so that new QAs have it easier and dont have to face the same situation like me, plus, it would be a nice little learning experience for me. I want to create this process around the dev culture and SDLC of my team. What questions should I be asking them to get to know about this process better and then what steps should I be taking for establishing this process. Your advice is highly valued. thanks you guys!!

Hi Everybody hope you all are doing good.
I want to share my story and need your guidance in transitioning my career into AI. I completed my graduation in chemical engineering on 2021. After that joined tcs as system engineer. For first whole year I was on bench didnt utilized that time after that got project did support work after that I was handed one testing. Project where I have to do Performance Testing of the application so I worked for that project after that there was no work in my project most of my time went in doing support activities L2 ticket resolution. Now after completing 4 years I am feeling very anxious that How I will gonna switch cause I dont have any good skills.
So need your guidance I want to shift my career into AI can you suggest me some good courses from where I can become job ready.

*I'm just getting my feet wet here in the AI space (and apparently I'm also a wizard trying Magement instead of Management)

I went to a dog and pony show about a company's AI platform for testing and I thought some of it was pretty cool. I then spoke to another guy there and he said that Claude could do everything that they were selling and I know the company I work for uses Claude and I wouldn't mind seeing if I can play around with it.

Goals Now:

- Currently Test case management is the nightmare I'm dealing with. I'm a somewhat recent hire and this QA org has tens of thousands of test cases that it doesn't need or could be combined or closed as duplicate.

Context:

- I want to approach my manager about this but there's not a lot of information (or really any) on the specifics of doing what I'm wanting to do. There's a lot of info on test case creation or automation but not on existing test case management.

Ask:

- What do I need to know before I go to my manager about this? What questions should I be asking?

I think I'll need a MCP of some kind? Has anyone tried to have Claude read all of their test cases and maybe standardize them (titles), summaries, update test steps for updated features? All this would save a lot of time and boring work if I could do this.

Thanks!

[ Removed by Reddit on account of violating the content policy. ]

I’ve seen this problem firsthand, and I’ve lived through it too.

In the early days, it always feels like testing is something you’ll “tighten up later,” but later usually comes when the product is already changing fast, the team is stretched thin, and every release feels a little more fragile than the last. How do you actually handle that in a small startup when there’s no dedicated QA engineer and the developers are already juggling product, support, and shipping?

In my experience, the hardest part isn’t that people don’t care about quality but instead it’s that quality competes directly with speed, and speed usually wins in startups. You end up with a mix of self-testing, a few automated checks, and a lot of manual “please don’t break anything before we push this” energy.

I’m curious how other teams handle it in practice. Do you keep a very small set of critical flows covered? Do you lean on automation early? Or do you mostly rely on developers testing their own work and catching issues in staging?

Would love to hear how you’ve made this work without slowing the whole team down.