#gherkin — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #gherkin, aggregated by home.social.
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Exclusive: Sydney Opera House and Gherkin designer Arup loses finance chief
Wednesday 05 August 2026 2:40 pm Arup was the design firm behind the Sydney Opera House The design…
#NewsBeep #News #Artsanddesign #Arts #ArtsAndDesign #Business #CFO #consultancy #Consulting #Design #Engineering #Entertainment #gherkin #millenniumbridge #profservices #ProfessionalServices #UK #UnitedKingdom
https://www.newsbeep.com/uk/728936/ -
https://www.europesays.com/uk/1132774/ Exclusive: Sydney Opera House and Gherkin designer Arup loses finance chief #Arts #ArtsAndDesign #Business #CFO #consultancy #Consulting #Design #engineering #Entertainment #gherkin #MillenniumBridge #News #ProfServices #ProfessionalServices #UK #UnitedKingdom
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How many more years before the #Gherkin is obscured from all sides by taller buildings?
This is the view from Lloyd’s Avenue.
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How many more years before the #Gherkin is obscured from all sides by taller buildings?
This is the view from Lloyd’s Avenue.
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How many more years before the #Gherkin is obscured from all sides by taller buildings?
This is the view from Lloyd’s Avenue.
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How many more years before the #Gherkin is obscured from all sides by taller buildings?
This is the view from Lloyd’s Avenue.
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How many more years before the #Gherkin is obscured from all sides by taller buildings?
This is the view from Lloyd’s Avenue.
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@dillyd It’s quite hard to get inside; there’s a restaurant at the top. Here are three pictures of it from 2008. #london #gherkin #30stmaryaxe
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@dillyd It’s quite hard to get inside; there’s a restaurant at the top. Here are three pictures of it from 2008. #london #gherkin #30stmaryaxe
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@dillyd It’s quite hard to get inside; there’s a restaurant at the top. Here are three pictures of it from 2008. #london #gherkin #30stmaryaxe
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@dillyd It’s quite hard to get inside; there’s a restaurant at the top. Here are three pictures of it from 2008. #london #gherkin #30stmaryaxe
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@dillyd It’s quite hard to get inside; there’s a restaurant at the top. Here are three pictures of it from 2008. #london #gherkin #30stmaryaxe
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It's not a gherkin. Built like an apple corer to extract the City's dark heart, all that selfish greed, yet leave #London's thousand thousand loves, tales and nations, flowing down the Thames.
Never reached the heart, bounced off an impenetrable shield of privilege. So they put offices in, and called it a #gherkin
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It's not a gherkin. Built like an apple corer to extract the City's dark heart, all that selfish greed, yet leave #London's thousand thousand loves, tales and nations, flowing down the Thames.
Never reached the heart, bounced off an impenetrable shield of privilege. So they put offices in, and called it a #gherkin
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It's not a gherkin. Built like an apple corer to extract the City's dark heart, all that selfish greed, yet leave #London's thousand thousand loves, tales and nations, flowing down the Thames.
Never reached the heart, bounced off an impenetrable shield of privilege. So they put offices in, and called it a #gherkin
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It's not a gherkin. Built like an apple corer to extract the City's dark heart, all that selfish greed, yet leave #London's thousand thousand loves, tales and nations, flowing down the Thames.
Never reached the heart, bounced off an impenetrable shield of privilege. So they put offices in, and called it a #gherkin
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It's not a gherkin. Built like an apple corer to extract the City's dark heart, all that selfish greed, yet leave #London's thousand thousand loves, tales and nations, flowing down the Thames.
Never reached the heart, bounced off an impenetrable shield of privilege. So they put offices in, and called it a #gherkin
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@Natasha_Jay often it's not a #bigDill too :awesome: #pickle #gherkin :blobcat_smilehappyeyes: :ablobwavereverse:
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@Natasha_Jay often it's not a #bigDill too :awesome: #pickle #gherkin :blobcat_smilehappyeyes: :ablobwavereverse:
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@Natasha_Jay often it's not a #bigDill too :awesome: #pickle #gherkin :blobcat_smilehappyeyes: :ablobwavereverse:
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@Natasha_Jay often it's not a #bigDill too :awesome: #pickle #gherkin :blobcat_smilehappyeyes: :ablobwavereverse:
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@Natasha_Jay often it's not a #bigDill too :awesome: #pickle #gherkin :blobcat_smilehappyeyes: :ablobwavereverse:
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Been messing about in using #gherkin with #golang. Found a generator for tests called #gherkingen.
Not too complex. 😎 Helps create tests based on the feature. With ai #agents everywhere, makes hallucinations at least grounded. 🫠
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Been messing about in using #gherkin with #golang. Found a generator for tests called #gherkingen.
Not too complex. 😎 Helps create tests based on the feature. With ai #agents everywhere, makes hallucinations at least grounded. 🫠
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Been messing about in using #gherkin with #golang. Found a generator for tests called #gherkingen.
Not too complex. 😎 Helps create tests based on the feature. With ai #agents everywhere, makes hallucinations at least grounded. 🫠
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Been messing about in using #gherkin with #golang. Found a generator for tests called #gherkingen.
Not too complex. 😎 Helps create tests based on the feature. With ai #agents everywhere, makes hallucinations at least grounded. 🫠
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Been messing about in using #gherkin with #golang. Found a generator for tests called #gherkingen.
Not too complex. 😎 Helps create tests based on the feature. With ai #agents everywhere, makes hallucinations at least grounded. 🫠
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We have published a new major version of the #Gherkin #Linter: https://www.npmjs.com/package/@gherlint/gherlint
Now you can validate your #Cucumber feature files even better and make sure:
- every feature has a When and a Then step
- every Then step contains a 'should'
- the text does not contain any major grammar mistakes
- no step contains any unwanted wordsIf you have ideas for more rules, contribute here: https://github.com/gherlint/gherlint
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We have published a new major version of the #Gherkin #Linter: https://www.npmjs.com/package/@gherlint/gherlint
Now you can validate your #Cucumber feature files even better and make sure:
- every feature has a When and a Then step
- every Then step contains a 'should'
- the text does not contain any major grammar mistakes
- no step contains any unwanted wordsIf you have ideas for more rules, contribute here: https://github.com/gherlint/gherlint
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We have published a new major version of the #Gherkin #Linter: https://www.npmjs.com/package/@gherlint/gherlint
Now you can validate your #Cucumber feature files even better and make sure:
- every feature has a When and a Then step
- every Then step contains a 'should'
- the text does not contain any major grammar mistakes
- no step contains any unwanted wordsIf you have ideas for more rules, contribute here: https://github.com/gherlint/gherlint
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We have published a new major version of the #Gherkin #Linter: https://www.npmjs.com/package/@gherlint/gherlint
Now you can validate your #Cucumber feature files even better and make sure:
- every feature has a When and a Then step
- every Then step contains a 'should'
- the text does not contain any major grammar mistakes
- no step contains any unwanted wordsIf you have ideas for more rules, contribute here: https://github.com/gherlint/gherlint
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We have published a new major version of the #Gherkin #Linter: https://www.npmjs.com/package/@gherlint/gherlint
Now you can validate your #Cucumber feature files even better and make sure:
- every feature has a When and a Then step
- every Then step contains a 'should'
- the text does not contain any major grammar mistakes
- no step contains any unwanted wordsIf you have ideas for more rules, contribute here: https://github.com/gherlint/gherlint
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I ate the most aesthetically pleasing pickle last night 🥒
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I ate the most aesthetically pleasing pickle last night 🥒
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I ate the most aesthetically pleasing pickle last night 🥒
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I ate the most aesthetically pleasing pickle last night 🥒
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I ate the most aesthetically pleasing pickle last night 🥒
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Une extension asciidoc pour faire "joliment" apparaître les scénarios Gherkin https://github.com/domgold/asciidoctor-gherkin-extension #asciidoc #extension #bdd #gherkin #test #opensource
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Une extension asciidoc pour faire "joliment" apparaître les scénarios Gherkin https://github.com/domgold/asciidoctor-gherkin-extension #asciidoc #extension #bdd #gherkin #test #opensource
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Une extension asciidoc pour faire "joliment" apparaître les scénarios Gherkin https://github.com/domgold/asciidoctor-gherkin-extension #asciidoc #extension #bdd #gherkin #test #opensource
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Une extension asciidoc pour faire "joliment" apparaître les scénarios Gherkin https://github.com/domgold/asciidoctor-gherkin-extension #asciidoc #extension #bdd #gherkin #test #opensource
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How many slices of gherkins is the perfect amount of slices of gherkins on a cheeseburger? 🍔
#Gherkin #Pickle #Burger #Cheeseburger #Food #Scran #Scranodon
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How many slices of gherkins is the perfect amount of slices of gherkins on a cheeseburger? 🍔
#Gherkin #Pickle #Burger #Cheeseburger #Food #Scran #Scranodon
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How many slices of gherkins is the perfect amount of slices of gherkins on a cheeseburger? 🍔
#Gherkin #Pickle #Burger #Cheeseburger #Food #Scran #Scranodon
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How many slices of gherkins is the perfect amount of slices of gherkins on a cheeseburger? 🍔
#Gherkin #Pickle #Burger #Cheeseburger #Food #Scran #Scranodon
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How many slices of gherkins is the perfect amount of slices of gherkins on a cheeseburger? 🍔
#Gherkin #Pickle #Burger #Cheeseburger #Food #Scran #Scranodon
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Как мы автоматизировали анализ упавших тестов с помощью AI: от хаоса к структуре
Представьте: каждый день ваши автотесты генерируют десятки отчетов об ошибках, QA команда тратит часы на анализ падений, а разработчики получают невразумительные описания в духе "test.feature упал на строке 410". Знакомо? Мы решили эту проблему, интегрировав AI в процесс анализа тестов, и хотим поделиться опытом.
https://habr.com/ru/articles/948980/
#искусственный_интеллект #автоматизация_тестирования #cicd #devops #qa #sourcegraph #prompt_engineering #cucumber #ruby_on_rails #gherkin
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Как мы автоматизировали анализ упавших тестов с помощью AI: от хаоса к структуре
Представьте: каждый день ваши автотесты генерируют десятки отчетов об ошибках, QA команда тратит часы на анализ падений, а разработчики получают невразумительные описания в духе "test.feature упал на строке 410". Знакомо? Мы решили эту проблему, интегрировав AI в процесс анализа тестов, и хотим поделиться опытом.
https://habr.com/ru/articles/948980/
#искусственный_интеллект #автоматизация_тестирования #cicd #devops #qa #sourcegraph #prompt_engineering #cucumber #ruby_on_rails #gherkin
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Как мы автоматизировали анализ упавших тестов с помощью AI: от хаоса к структуре
Представьте: каждый день ваши автотесты генерируют десятки отчетов об ошибках, QA команда тратит часы на анализ падений, а разработчики получают невразумительные описания в духе "test.feature упал на строке 410". Знакомо? Мы решили эту проблему, интегрировав AI в процесс анализа тестов, и хотим поделиться опытом.
https://habr.com/ru/articles/948980/
#искусственный_интеллект #автоматизация_тестирования #cicd #devops #qa #sourcegraph #prompt_engineering #cucumber #ruby_on_rails #gherkin
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I’m still seeing people sharing #LLM prompts like “You are an expert programmer. Write tests for this code, considering all edges cases…”.
This strikes me as a little bit delusional. This is not how LLMs work.
“You are an expert programmer” doesn’t change the output. People have cargo-culted that in from prose output prompts, where it _did_ matter: saying “write this essay as if you were an ancient Sumerian” produces qualitatively different output. But at no point did the LLM actually start believing it was an ancient Sumerian, because they don’t believe anything. Similarly, if you _don’t_ put “you are an expert programmer” at the front, it doesn’t suddenly start thinking “oh, my code can be rubbish, then,” (because it doesn’t think.)
“Considering all edge cases” doesn’t change the output, prove me wrong. Because all it does is pattern match your code. If similar-enough code with decent test coverage existed somewhere in its training set, then there is a good chance you’ll get half-decent tests out of it.
And I think this because I’ve been running experiments. And what I’ve discovered is that they are generally very bad at writing exhaustive tests, in the style that you want. I find it very worrying when I see people say things like “I asked it to write tests for the code, and 95% of them passed”. Yes, but what about the tests that it _missed_?
I don’t know whether it’s a context window problem, or that the “exhaustive” and “write like this” prompts are pulling the output in different directions.
However, I have discovered you get markedly better output if you first ask it to describe the tests in the #Gherkin #BDD language, and then ask it to convert the Gherkin to code, which does support the “pulling in different directions” hypothesis.
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I’m still seeing people sharing #LLM prompts like “You are an expert programmer. Write tests for this code, considering all edges cases…”.
This strikes me as a little bit delusional. This is not how LLMs work.
“You are an expert programmer” doesn’t change the output. People have cargo-culted that in from prose output prompts, where it _did_ matter: saying “write this essay as if you were an ancient Sumerian” produces qualitatively different output. But at no point did the LLM actually start believing it was an ancient Sumerian, because they don’t believe anything. Similarly, if you _don’t_ put “you are an expert programmer” at the front, it doesn’t suddenly start thinking “oh, my code can be rubbish, then,” (because it doesn’t think.)
“Considering all edge cases” doesn’t change the output, prove me wrong. Because all it does is pattern match your code. If similar-enough code with decent test coverage existed somewhere in its training set, then there is a good chance you’ll get half-decent tests out of it.
And I think this because I’ve been running experiments. And what I’ve discovered is that they are generally very bad at writing exhaustive tests, in the style that you want. I find it very worrying when I see people say things like “I asked it to write tests for the code, and 95% of them passed”. Yes, but what about the tests that it _missed_?
I don’t know whether it’s a context window problem, or that the “exhaustive” and “write like this” prompts are pulling the output in different directions.
However, I have discovered you get markedly better output if you first ask it to describe the tests in the #Gherkin #BDD language, and then ask it to convert the Gherkin to code, which does support the “pulling in different directions” hypothesis.
-
I’m still seeing people sharing #LLM prompts like “You are an expert programmer. Write tests for this code, considering all edges cases…”.
This strikes me as a little bit delusional. This is not how LLMs work.
“You are an expert programmer” doesn’t change the output. People have cargo-culted that in from prose output prompts, where it _did_ matter: saying “write this essay as if you were an ancient Sumerian” produces qualitatively different output. But at no point did the LLM actually start believing it was an ancient Sumerian, because they don’t believe anything. Similarly, if you _don’t_ put “you are an expert programmer” at the front, it doesn’t suddenly start thinking “oh, my code can be rubbish, then,” (because it doesn’t think.)
“Considering all edge cases” doesn’t change the output, prove me wrong. Because all it does is pattern match your code. If similar-enough code with decent test coverage existed somewhere in its training set, then there is a good chance you’ll get half-decent tests out of it.
And I think this because I’ve been running experiments. And what I’ve discovered is that they are generally very bad at writing exhaustive tests, in the style that you want. I find it very worrying when I see people say things like “I asked it to write tests for the code, and 95% of them passed”. Yes, but what about the tests that it _missed_?
I don’t know whether it’s a context window problem, or that the “exhaustive” and “write like this” prompts are pulling the output in different directions.
However, I have discovered you get markedly better output if you first ask it to describe the tests in the #Gherkin #BDD language, and then ask it to convert the Gherkin to code, which does support the “pulling in different directions” hypothesis.
-
I’m still seeing people sharing #LLM prompts like “You are an expert programmer. Write tests for this code, considering all edges cases…”.
This strikes me as a little bit delusional. This is not how LLMs work.
“You are an expert programmer” doesn’t change the output. People have cargo-culted that in from prose output prompts, where it _did_ matter: saying “write this essay as if you were an ancient Sumerian” produces qualitatively different output. But at no point did the LLM actually start believing it was an ancient Sumerian, because they don’t believe anything. Similarly, if you _don’t_ put “you are an expert programmer” at the front, it doesn’t suddenly start thinking “oh, my code can be rubbish, then,” (because it doesn’t think.)
“Considering all edge cases” doesn’t change the output, prove me wrong. Because all it does is pattern match your code. If similar-enough code with decent test coverage existed somewhere in its training set, then there is a good chance you’ll get half-decent tests out of it.
And I think this because I’ve been running experiments. And what I’ve discovered is that they are generally very bad at writing exhaustive tests, in the style that you want. I find it very worrying when I see people say things like “I asked it to write tests for the code, and 95% of them passed”. Yes, but what about the tests that it _missed_?
I don’t know whether it’s a context window problem, or that the “exhaustive” and “write like this” prompts are pulling the output in different directions.
However, I have discovered you get markedly better output if you first ask it to describe the tests in the #Gherkin #BDD language, and then ask it to convert the Gherkin to code, which does support the “pulling in different directions” hypothesis.
-
I’m still seeing people sharing #LLM prompts like “You are an expert programmer. Write tests for this code, considering all edges cases…”.
This strikes me as a little bit delusional. This is not how LLMs work.
“You are an expert programmer” doesn’t change the output. People have cargo-culted that in from prose output prompts, where it _did_ matter: saying “write this essay as if you were an ancient Sumerian” produces qualitatively different output. But at no point did the LLM actually start believing it was an ancient Sumerian, because they don’t believe anything. Similarly, if you _don’t_ put “you are an expert programmer” at the front, it doesn’t suddenly start thinking “oh, my code can be rubbish, then,” (because it doesn’t think.)
“Considering all edge cases” doesn’t change the output, prove me wrong. Because all it does is pattern match your code. If similar-enough code with decent test coverage existed somewhere in its training set, then there is a good chance you’ll get half-decent tests out of it.
And I think this because I’ve been running experiments. And what I’ve discovered is that they are generally very bad at writing exhaustive tests, in the style that you want. I find it very worrying when I see people say things like “I asked it to write tests for the code, and 95% of them passed”. Yes, but what about the tests that it _missed_?
I don’t know whether it’s a context window problem, or that the “exhaustive” and “write like this” prompts are pulling the output in different directions.
However, I have discovered you get markedly better output if you first ask it to describe the tests in the #Gherkin #BDD language, and then ask it to convert the Gherkin to code, which does support the “pulling in different directions” hypothesis.
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🧩 Join Michigan Python: Make Testing Fun Again with Gherkin & Python!
Learn how to create human-readable test scenarios that your whole team will understand! Robson Luan do Nascimento de Sousa will demonstrate how Gherkin + Python can transform your testing approach using an exciting chess game example.
WHEN: 2025-03-06 at 7pm ET
WHERE: Washtenaw Community College or Online👉 Details & RSVP: https://www.meetup.com/michigan-python/events/305384913/
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🧩 Join Michigan Python: Make Testing Fun Again with Gherkin & Python!
Learn how to create human-readable test scenarios that your whole team will understand! Robson Luan do Nascimento de Sousa will demonstrate how Gherkin + Python can transform your testing approach using an exciting chess game example.
WHEN: 2025-03-06 at 7pm ET
WHERE: Washtenaw Community College or Online👉 Details & RSVP: https://www.meetup.com/michigan-python/events/305384913/