BrowserStack Reviews

GitHub Reviews

1. Reinhard

   · Boss at CLOUD Meister · over 5 years ago
   perfect 4 open Source

BrowserStack mentions (8)

• Show HN: Quell – AI QA Agent Working Across Linear, Vercel, Jira, Netlify, Figma

  This is pretty cool - the Jira/Linear integration could save a ton of manual work. How do you handle test data setup and teardown? That's usually where these workflows get messy. For alternatives in this space, there's qawolf (https://qawolf.com) for similar automated testing workflows, or I'm actually building bug0 (https://bug0.com) which also does AI-powered test automation, still in beta. For the more... - Source: Hacker News / about 1 year ago

• 🛑 Stop resizing your browser: improve testing for responsiveness

  Platforms like Browserstack or SauceLabs offer virtual instances of real devices and browsers for manual and end-to-end testing. Caveat: subscriptions cost money and are on a per-seat basis. - Source: dev.to / about 2 years ago

• Unsupported country

  If you go to browserstack.com (a website to test other websites) you can probably to the chatgpt url and sign up there. Source: over 3 years ago

• Windows vs Mac?

  For testing on Mac or iOS, use browserstack.com, you'll spend considerably less using that than you would buying the actual hardware. Source: over 3 years ago

• Free methods for testing websites/apps across devices?

  I've seen subscription services such as browserstack.com and lambdatest.com but I believe they cost to get the full range of mac browsers and devices. Source: over 3 years ago

GitHub mentions (2474)

• I audited a 5.5 GB AI training dataset by downloading 0.8% of it

  Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 4 days ago

• Superlogical – Mitchell Hashimoto

  Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:

          Host *.

  - Source: Hacker News / 11 days ago

• Your Agent's Confidence Score Is Not a Probability

  All of this assumes you can actually inspect what the agent did — the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 11 days ago

• Foreman 101: agentic coding as Kubernetes resources

  # git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$GITHUB_TOKEN" -n foreman-system Kubectl create secret generic foreman-git-credentials \ --from-literal=token="$GITHUB_TOKEN" -n foreman-system Helm upgrade foreman llmkube/foreman -n foreman-system --reuse-values \ --set agent.githubToken.secretName=foreman-github \ ... - Source: dev.to / 12 days ago

• Stop Judging Every Run: Eval Sampling Is a Budget Decision, Not a Coverage One

  This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output — the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 21 days ago