generate nicer nunit/specflow test reports using this new XSLT template

Hacker News

Recently I was setting up the reporting for our acceptance tests that I noticed two issues.<p>(1) it's terribly simple in style! (2) it's missing some info such as namespaces (for when you have many folders in which you have tests) and categories.<p>So I edited the existing XSLT and rectified those two issues for me by adding twitter bootstrap style, prismJs syntax highlighting and adding the missing information to the output.<p>I hope this could be helpful for you too.<p>P.S. in case you have your own special-purpose report XSLT why not share it with others in the project?

Visit product View on Hacker NewsNov 10, 2013

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

15%15% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

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