m

db/sql/docs/books.txt

@@ -1,3 +1,6 @@
+2024
+TaylorBlum - 2024 - SQL All-in-One For Dummies 4th ed
+    317D36A82E28CE96E9DFBB9CCEDAA1E4
 2023
 Wade - Mastering SQL Joins
     649006BE60C1184DDD53823D80A2956C

nontech/politics/countries/by/shpakovskiy.txt

@@ -0,0 +1,3 @@
+2024
+MamikinsTV - Shpakovskiy - Strong BY of 40:50
+    https://www.youtube.com/watch?v=ha8tZeQXKxw

nontech/politics/people/gennady-m.txt

@@ -10,6 +10,10 @@ Soros - Crisis of the World Capitalism (later renounciated it)
 MichaelTellbot - Golographics Universe
 
 2024
+GennadyM - TON and NOT Secrets of 1:26:41
+    https://www.youtube.com/watch?v=L0m-ukggvRw
+USLawAndOrder - Dudnik - GennadyM - 06.30 of 1:01:01
+    https://www.youtube.com/watch?v=BoafKAKkUac
 GennadyM - MosStockExchange of 1:38:30
     https://www.youtube.com/watch?v=4cUnX8JaWIQ
     ! 4 mos-excange private brokers-speculants

pl/cross/io/fileformats/json/jq.txt

@@ -6,6 +6,8 @@ https://github.com/fiatjaf/jiq
 tui stuff
 https://github.com/noahgorstein/jqp
 
+2024
+https://medium.com/@buczynski.rafal/exploring-jq-a-guide-to-essential-techniques-and-tools-for-professionals-b9df9db490de
 2022
 https://ente.io/blog/tech/jq-diff/
 2021

pl/cross/tools/quality/test/bdd/gherkin/docs/articles.txt

@@ -0,0 +1,11 @@
+2024
+https://medium.com/@buczynski.rafal/gherkin-in-testing-a-beginners-guide-f2e179d5e2df
+https://selleo.com/blog/how-to-start-writing-gherkin-test-scenarios
+https://hapy.co/journal/gherkin-language/
+2023
+https://foxminded.ua/ru/gherkin-chto-eto/
+https://support.smartbear.com/cucumberstudio/docs/bdd/write-gherkin-scenarios.html
+2020
+https://www.software-testing.ru/library/testing/testing-tools/3245-writing-good-gherkin-enables-good-test-automation
+2016
+    https://habr.com/ru/articles/275013/

pl/cross/tools/quality/test/bdd/gherkin/docs/presentations.txt

@@ -0,0 +1,7 @@
+2023
+SQAAnalystTechwriterDays - Povelov - Quick Start in Gherkin for Manual QA 0:00 of 40:28
+    https://www.youtube.com/watch?v=w4CrhyWWwzk
+2022
+LitheSpeed - Better Gherkin: Common pitfalls and how to overcome them 0:00 of 38:04
+    https://www.youtube.com/watch?v=ci578UHQsIs
+https://smartiqa.ru/blog/bdd_gherkin_cucumber

pl/cross/tools/quality/test/bdd/gherkin/gherkin.txt

@@ -0,0 +1,13 @@
+https://github.com/cucumber/gherkin
+https://github.com/cucumber/gherkin/tree/main/java
+
+at vpn
+https://cucumber.io/docs/gherkin/
+https://cucumber.io/docs/gherkin/reference/
+
+https://www.gherkinuft.com/gherkin/
+https://wellbehaved.readthedocs.io/Gherkin.html
+https://specflow.org/learn/gherkin/
+https://behat.org/en/latest/user_guide/gherkin.html
+https://www.spekframework.org/gherkin/
+https://jignect.tech/understanding-the-bdd-gherkin-language-main-rules-for-bdd-ui-scenarios/

pl/cross/tools/quality/test/bdd/gherkin/integration/idea-gherkin.txt

@@ -0,0 +1 @@
+https://plugins.jetbrains.com/plugin/9164-gherkin

pl/cross/tools/quality/test/contract/specmatic.txt

@@ -0,0 +1,8 @@
+https://specmatic.in/
+https://specmatic.in/pricing/
+
+https://github.com/znsio/specmatic
+
+https://specmatic.in/getting_started.html
+https://specmatic.in/documentation/contract_tests.html
+https://specmatic.in/documentation/language.html

pl/java/libfws/spring/boot/docs/whatsnew.txt

@@ -3,6 +3,15 @@ runtime("org.springframework.boot:spring-boot-properties-migrator")
 3.x
 [VDBUH2024] - Josh Long - Bootiful Spring Boot 3.x 20:00 of 58:09
     https://www.youtube.com/watch?v=3SiYK0BWr0M
+    @SpringBootApplication
+    public class ServiceApplication {
+      ...
+      @Bean
+      RouterFunction<ServerResponse> routerFunction() {
+        return route().GET("customers", null)
+            .build();
+      }
+    }
 JavaTechie - Spring Boot 3.2 With Virtual Threads Explained 0:00 of 22:22
     https://www.youtube.com/watch?v=9dUPPHREF7w
 Lviv JavaClub - [Event 302] Spring boot news by Ihor Didyk 0:00 of 47:37

pl/kt/tools/quality/test/spek.txt

@@ -5,6 +5,8 @@ https://github.com/JetBrains/spek
 
 https://bintray.com/jetbrains/spek/spek
 
+https://www.spekframework.org/gherkin/
+
 articles
 2021
 https://www.baeldung.com/kotlin/spek

science/ai/prompt/parameters.txt

@@ -0,0 +1,33 @@
+Employing advanced prompt parameters enables prompt engineers to achieve, among others, several objectives:
+  Control response length and stop sequence
+  Define the underlying model
+  Manage the Creativity Level
+  Control frequency and presence penalties
+  Inject start and restart text
+
+The "temperature [0 to 1]" is a parameter that controls the creativity and randomness of the model's output. 
+A higher temperature (e.g., 1.0) makes the output more diverse and creative, while a lower temperature (e.g., 0.1) makes the output more focused and deterministic.
+
+
+The "top_p [0-1]" (also known as nucleus sampling) dictates the scope of randomness for the language model. 
+It determines how many random results the model should consider based on the temperature setting.
+
+The "stop_sequences [list of strings]" is a list of strings or tokens that, when encountered by the model, will cause it to stop generating further text. 
+This helps control the length and structure of the generated content, preventing the model from producing unwanted text beyond the specified stopping point.
+
+The "frequency_penalty [-2 to 2]" parameter reduces the likelihood of the model repeating the same line verbatim by assigning a penalty to more frequent tokens. 
+A positive frequency penalty (e.g., 1.0) discourages the model from repeating tokens that appear frequently in the input, while a negative frequency penalty (e.g., -1.0) 
+encourages the model to repeat such tokens.
+
+The "presence_penalty [-2 to 2]" parameter increases the chances of the model discussing new topics by penalizing tokens already present in the input. 
+A positive presence penalty (e.g., 1.0) discourages the model from using tokens already appearing in the input. 
+In contrast, a negative presence penalty (e.g., -1.0) encourages the model to reuse tokens from the input.
+
+The "best_of [positive integer]" allows you to specify the number of completions (n) that the model should generate, 
+and it returns the best completion according to the model's internal evaluation. 
+This is useful when obtaining the highest quality completion from different possible results. 
+(n) can be an integer in the range from 1 to 20.
+
+[
+{"role": "user", "content": "Write a user story for the login process.", "settings": {"temperature": 0.8, " frequency_penalty": -1}}
+]