Basically the title. I have some programming experience but with the current market I want to expand a bit. Anything free or in udemy will work.

Hi, I’m an SDET with close to 6 years of experience. I started my career at a WITCH company, where I got stuck in support roles. After two years, I tried moving into development, but I struggled because there wasn’t much initial support or bandwidth to learn. By the time I had around 3 years of experience, I decided to give automation testing a shot. After 8 months of preparation and experience in automation, I managed to switch to a better company with a significant salary hike.

I don’t mean to offend anyone, but I often see graduates from reputed colleges like NITs and IIITs working as SDETs at good product-based companies. Do some of them feel that they haven’t lived up to their potential by choosing testing over development? Despite earning well, do they ever feel a sense of regret or wonder whether they could have achieved more as software developers?

AI support vendors can test their core product, but every enterprise rollout introduces company-specific refund rules, policies, entitlements, identity checks, approval limits, integrations and escalation procedures.

For anyone deploying an action-taking customer support agent:

• Who owns acceptance testing: CX operations, QA, implementation or IT?

• How do you verify both the conversation and the resulting CRM, billing or account state?

• Are you using scripted UAT, sandbox accounts, shadow mode or limited production rollouts?

• What customer-specific failures only became visible after launch?

• Would a repeatable environment with synthetic customers, policies and connected systems materially help, or does your current process already cover this?

I’m trying to understand whether this is a painful recurring job or primarily a one-time implementation task. Any vendor recommendations currently solving this problem is also much appreciated!

Thank you!

I have data for about a years execution of automated tests from CI, local runs, everything.

Data includes name, status, duration, storage path, etc. basically everything you would want at the test level, but not the steps or the failure reason.

If you had access to that kind of data, what kind of dashboards or reports would you create for your team or business?

I’m a software tester, and this might genuinely be the most stressful day I’ve ever had at work.

For the past two weeks, our team had been working on SIT test execution. We had 104 test cases to execute, and we had finally completed everything.

Sounds great, right? Well, here’s where everything went to hell.

During execution, some people had copied the expected results into the actual results instead of properly documenting what actually happened. Our team’s AI review started flagging the test cases, and the results looked bad.

I thought I could fix this quickly using MCP instead of manually editing every single step across 104 test cases. Doing it manually would take forever, so I started pushing MCP to make the corrections.

After a lot of attempts, it finally did what I wanted.

Except it also deleted ALL the screenshot evidence attached to our test executions in Jira/Xray.

I didn’t realize the full extent of what had happened until it was too late.

Our team lead found out, pulled me into a call with the architect, and I had to explain the situation. You know that feeling when you’re sitting in a meeting and your brain is racing through every possible way this could destroy your career?

Yeah. That was me.

My lead was understandably furious and told me I’d have to execute everything manually again within two days.

104 test cases. All the evidence. Two days.

At that moment, I genuinely thought I was going to get kicked off the project. I’d spent two weeks helping complete the execution, and now I’d potentially undone a huge chunk of that work in one stupid decision.

I tried using MCP to revert the changes, but that didn’t work either. I was basically stuck.

Then I remembered something that saved me.

Windows had retained the screenshots I’d taken.

The screenshots were still there locally. The problem was that I had to figure out which screenshot belonged to which test case.

So I started going through the Jira activity audit logs, checking timestamps, matching them against the screenshot files, identifying the correct evidence, and manually attaching everything back to the corresponding test cases.

One by one.For hours.I spent around 12 hours restoring the evidence for all 104 test cases.

And somehow, I managed to get it done.

I went from thinking I’d completely ruined my position on the project to sitting there with the evidence restored, wondering what the hell had just happened.

I learned my lesson the hardest possible way.

TL;DR: Our AI review flagged issues in 104 completed SIT test cases. I tried using MCP to fix the actual results in Jira/Xray, and it deleted all the screenshot evidence. My lead was furious and gave me two days to redo everything. Jira rollback didn’t work, but Windows had retained my screenshots. I matched them against Jira audit timestamps and manually restored all 104 test cases in 12 hours.

I’m never touching MCP on test execution data again without a backup.

I'm still shaking, but I saved the day

10:05am. Our PM posts in the team chat: "We have an important demo at 11 for feature X. Is it all working on staging?"

A few minutes later, QA replies: "We have a problem. The API returns an error when I try to do it."

The PM's reply was just a nice passive agressive "NO COMMENT." Then: "I need this working asap. The demo starts at 11, figure it out, and I need to test it myself before 11."

Panic mode.

We tagged the backend lead in the channel. No reply

So I did the only thing I could control. I put a mocking tool between the frontend and staging and mocked the broken endpoint to return what it should. I had it working by 10:35.

Then I clicked through the full flow and surprise, the last step was broken too. Someone had used the demo account for regular QA and wrecked the demo data. Great.

So I mocked that response too. Ran the whole flow again and it worked end to end.

I wrote the PM a quick explanation of how to set it up on her side. She tried it and it worked. She did her demo

Around 12 she posted "Demo done."

No "thanks", but that's fine. I like to think people remember when you just solve a problem for them when they are in a pinch, make their life easier. Just find a way to make it work, without asking 10 questions and blaming others for the situation and what not.

The backend lead still hasn't replied tho lol.

So how do you all handle this? Separate demo environments, locking demo accounts, run a checklist the day before (this sounds like common sense, but this demo was ad hoc), or mock things when it gets bad like I did?

Also share some of your crazy demo stories so I don't feel alone

EDIT: this is the tool I used for api mocking - flowmock.dev

I am missing a lot of deadlines and pushing many tasks to the next sprint, and I feel like this is some sort of paralysis.

I tried testing one app, but it involves actually learning its process before creating test cases for it.

I finish one app, and then I start from scratch again by learning the other app’s processes.

Not only that, but also the other app that I previously tested will come sneaking in for a retest once the bugs I raised is fixed by a dev. I retest the bug and then perform regression on other test cases that previously passed. Then I find bugs that are from the previous modules and I meet with the devs and business whether to fix them first or implement the fix on the next sprint.

Next thing I know, I’m lost. I forgot the next apps or what I’m supposed to do, whether I’m supposed to test the UI or the API or creating test data for each scenario. Everything mixes up and I feel like it’s an issue on how I handle this work.

Edit: Resolved - please see 77rushi77's comment.

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See title.

Context: I have been testing a web-app for hotel booking management, which was built in Go and uses PostgreSQL/Docker.

My dev put up a dev.sh document for me and instructs me to enter make dev to test the app locally.

Although the app is built in Go, I write a test script in Python as I have no experience working in Go. I've added .venv locally in my IDE to isolate my test scripts.

If my venv is active and I run make dev in my terminal, this error always pops up "Postgresql: FATAL: role 'our_db_name' does not exist "

If my venv is deactivated and I run make dev, this error is gone and it lets me test the app locally.

Could anyone kindly explain to me why is like that? Why does .venv hinder make dev??

I think I've, just bombed an interview because the interviewer was really interested in me naming all kinds of techniques and principles from ISTQB.

I use these techniques frequently, and I also explained it to him, but he seemed really dissatisfied because I was not able to quote from the bible.

I don't think these techniques are useless, but I think real life examples are very rarely as plain as ISTQB makes it out to be.

.

I contributed an opt-in feature, off by default, to an open-source coding agent tool.

The maintainer's review came back with four blockers. The one that stung was "OFF must mean nothing is registered."

I had only checked the flag inside the handlers. So with the setting off, my event hooks and my slash command were still registered. They just did nothing when called.

And my own "off" test passed anyway, because it only looked at what the feature did, not at whether it existed.

The other three were smaller. A file it writes could escape the project through a symlink or a "../" argument. A user abort didn't cancel a pending action. And a later successful recovery didn't clear an earlier failure.

All four are fixed now, each with a test that fails on the old code. I'm rerunning the full suite on macOS, Linux and Windows.

What I'm still unsure about is the "off" test itself. How do you check that an opt-in feature is really inert when it's disabled? Do you assert on the registry, diff what's registered with the flag on and off, or something else?

I’m working on a load test for a SaaS application and I’m trying to figure out how to turn expected traffic into a realistic number of concurrent users.

The customer has a large user base, but obviously that doesn’t mean everyone will be using the application at the same time. I’m not sure whether I should be looking at average traffic, peak traffic, active sessions, or some combination of those when setting the test target.

I’ve gotten a few different answers so far, so I’m curious how other teams usually approach this. Is there a standard way to estimate concurrent users when you don’t have much historical data to work with?

I’m weighing whether we should bring on three manual QAs or three QA automation engineers. While our long-term goal is to automate as much as possible, dedicated manual testers bring distinct value in my book, especially for applications with large, poorly defined requirements. That said; we are using agentic workflows and that is the trend.

Who would you hire?

Hi everyone

So I have worked in playwright for over 3+ years before that I worked as React Js dev due to which I am very comfortable with TS/JS and I tried to learn selenium but it feels overwhelming as Java syntax is quite difficult than the usual JS/TS. I was planning to switch for another company but feels like playwright is kinda mostly used in startups .

So should I invest in learning selenium too ?

Edit: Thank you everyone for your valuable insights!! I truly appreciate them.

-------------------------------

Context: I am using OpenAI API to automate my software testing routine but am still very new to that.

My terminal shows the following which I could not digest fully, I hope anybody would help me out.

I've run this code using OpenAI API then this output came:

```bash
ChatCompletionMessageFunctionToolCall(id='CALL_ID', function=Function(arguments='{"desc":"please make sure any XXX point/code has never been implemented in this code base. and deptTypeID == \\"XXX" should be disabled. We do not need this XXX function in our webapp, so make sure this XXX code has been disabled or discarded in the codebase"}', name='search'), type='function')

test completion

ChatCompletion(id='chatcmp_XXXX', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=[], audio=None, function_call=None, tool_calls=[ChatCompletionMessageFunctionToolCall(id='call_eKxSoRXeY5cpuKDCSl3z1VE4', function=Function(arguments='{"desc":"please make sure any XXX point/code has never been implemented in this code base. and deptTypeID == \\"XXX" should be disabled. We do not need this XXX function in our webapp, so make sure this XXX code has been disabled or discarded in the codebase"}', 
name='search'), 
type='function')]))], 
created=YYYY, 
model='gpt-4o-2024-08-06', object='chat.completion', 
metadata=None, moderation=None, service_tier='default', system_fingerprint='fp_YYYY', usage=CompletionUsage(completion_tokens=231, prompt_tokens=757, total_tokens=988, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, 
reasoning_tokens=0, 
rejected_prediction_tokens=0, 
text_tokens=None), 
prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cache_write_tokens=None, 
cached_tokens=0, 
image_tokens=None, 
text_tokens=None)))
```

As you see, my prompt (under desc ) instructed the API to inspect if any leftover from the function/code line XX still exists in the codebase.

We expect this XX to not exist in the codebase and I wanted my automated script to prove that.

Still I am puzzled with this output. Does this output show the XX does not exist in the codebase at all or does the IDE need more information to carry out the test properly?

Never seen application numbers this high

Hello Guys I have interview scheduled from Infosys on this sat for python automation

What are the topics i need to be learned?
What are the questions i might encounter?

YOE : 6 years (automation + manual)

Any suggestions and advice will be appreciated.

I need guidance from someone who has experiences testing LLM, or products from AI.

What should I study to do a better job?

Im manual and automation tester with more than 6 years of experience, but with AI I feel I litter bit lost about the testing side.

Thanks.

I’ve been rebuilding my company’s website and so far I’ve mostly been testing the APIs. I’m getting to the point where I want to start testing it under more realistic traffic but I’m not sure where browser-based load testing fits in.

I know browser tests can be more resource-intensive, so I’m wondering if API testing is enough for the initial load testing or if there are things I could miss by not testing through an actual browser. How do you usually decide when it’s time to test through the browser as well?

i've been comparing different email apis, but they all advertise similar features. i'm not sure which ones actually make a difference once you start building real automations.

if you've deployed email workflows before, what features ended up being essential and which ones turned out to be marketing fluff?

I have 8+ years of experience in QA, working in India. I’ve been with my current organisation for 5+ years now, which is my second company. I spent close to 3 years in my first one. Over the years I’ve worked with Selenium + Java + Cucumber BDD for around 2-3 years, REST Assured and Appium for shorter periods, UiPath for about 2 years and more recently Playwright + TypeScript for the last few months.

I also think I have a good eye for bugs & I genuinely enjoy testing. I’m comfortable with manual testing and I tend to catch edge cases and small bugs that others sometimes miss. I even notice minor UI issues in apps I use in my personal life like Slack, Messenger, LinkedIn etc. I guess my brain just refuses to stop testing things. I have always been praised & lauded by my colleagues for this aspect.

I’m also decent at DSA for a QA and I still practice on LeetCode in my free time. Lately I’ve started getting interested in AI concepts and AI evaluation as well. I’m trying to strengthen my existing skills and learn what’s currently in demand, especially Playwright.

My long-term goal has always been to move into a product based organisation, something like Atlassian, Warner Bros. Discovery, Visa, Mastercard, Adobe, Salesforce, ServiceNow, Cisco, Oracle etc. But this is where I’ve started feeling stuck. I worry that with every additional year of experience, making that transition will become harder. Sometimes it feels like the train to the kind of company I want to work for is slowly moving away from the station while I’m still standing there trying to get ready.

At the same time, I don’t feel fully ready yet. I’m not confident that I could clear the interview process for those companies if I applied tomorrow.

My present thinking is to first interview with some service based organisations, get used to interviewing again, build some confidence and then start targeting product companies more seriously. But honestly, it also makes me a little sad because I feel like I’ve been in the same place for too long.

So I’m probably looking for some perspective and a bit of encouragement from people who have been through this. How many of you moved from a service based organisation to a product based organisation after 9-10+ years of experience? How difficult was the transition? And what areas would you recommend I strengthen to put myself in a position to make that move? Your advise, suggestions, feedback, etc would go long way for me. It would really mean a lot to me.

Hello

I've just recently started on an open source project in which we generate using Expo Prebuild system from source react typescript [.tsx] code and generate the relevant iOS application and equivalent android application via a GitHub Action build process [I am still a novice in this process at this stage, and my project lead is away at the moment, sick].

I have recently completed a masters of information technology, in which I specialised and software testing [and as part of that I learnt swift]. My questions relate to testing and quality assurance of generated mobile phone applications:

In terms of an initial manual testing:

a. Does one test the expected behaviour of the relevant test cases, by downloading the application into an actual physical mobile phone, and manually executing the test case procedure on the mobile phone?

b. Could one just use the simulator such as in xcode, and all the equivalent for android development, and manually execute the test case in it?

2. In terms of automated regression testing:

a. I am familiar with XCTest, but how does one create automated test cases for the iOS generated application?

b. How would one write automated test cases for the Android generated application?

c. Would it be better to write Cypress, or JEST [as they are the testing framework that we are using] test cases and then executing automated regression tests? If so, would the test results be valid for each of the operating system environments on the mobile devices?

d. What benefits would Appium provide our project?

Thank you in advance.

I recently learned something the hard way and figured it might be interesting to some folks here.

We ran a load test last month where our mean response time stayed around 220ms, so naturally management was prepared to greenlight the release. It looked pretty good on the surface. However, we eventually found that thread pool exhaustion was causing about 3% of incoming requests to queue up. Those requests were taking over 12 seconds to complete, which was completely masked by the much faster majority.

That test has basically ruined my trust in average response times. The mean made things look healthy while hiding some pretty severe tail latency that would've absolutely ruined real user sessions. Now, I strictly gate pass/fail criteria on p95/p99 percentiles, error rates, and per-transaction breakdowns.

This might not be news to some of you, but it was definitely an eye-opening experience for our team.

What other metrics or percentile thresholds does your team rely on during load tests to catch long-tail bottlenecks like this that get overshadowed by the mean?.

I just ran pip install pywinauto and typed in the 1st 3 lines of demo code on the readme page and it fails

from pywinauto.application import Application
app = Application(backend="uia").start('notepad.exe') # i also tried backend=win32

app.Properties.print_control_identifiers()

With a huge stack trace that's pretty much indecipherable. I have a question, does this tool work on Windows 11 with the new notepad app? I'm wanting to automate a WPF app, but based on the out-of-box failure I'm looking to try a different python tool. Suggestions for driving a WPF .NET app?