VREST NG v1.0.0 Release

Hacker News

We are very glad to announce our first stable version of vREST NG. It will take your API Testing experience to next level. With this release, It makes your swagger based testing and Data driven testing more easier. So contact us with your enterprise needs and stay tuned with us. * New Features - Now record your test cases quickly and replay them. [[https://ng.vrest.io/docs/app/tc-recording/][Learn More]] - Swagger Import has now an option to generate data driven tests. * Bug Fixes - After deleting test cases, the count issue fixed in Run button. - Bug fixed related to request body read from the excel sheet. - Deleting the schema was not rendering the previous schemas. - Light Theme indicator issue when we change project. - Loop issue when there are no iterations. * Improvements - Now you may see the iteration summary in Results tab written in CSV files with iterationSummary column. - Reload Test Cases functionality added in vREST NG application.

Visit product View on Hacker NewsDec 19, 2019

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

21%21% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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