Markup Template Engine is a new feature of Groovy, that is a kind of Embedded DSL which is implemented using Groovy 2.x features like:
- Custom Type Checker(Type Check Extension)
- Compiler Configuration
You can generate HTML/XML using full brown programming language features:
- modularity
- abstraction
- type system
- flow structure
- variable, OOP, etc, etc..
The document discusses features and enhancements in Groovy 1.8.0, including improved AST processing, new logging capabilities using the @Log annotation, support for method locks with @WithReadLock and @WithWriteLock, interruptible loops, memoization of recursive functions, and integration with JSON parsing. Slides provide code examples and diagrams to illustrate these Groovy language and library improvements.
Let's go Developer 2011 sendai Let's go Java Developer (Programming Language ...Uehara Junji
The document compares Java and Groovy implementations of a word counting program. The Java version uses HashMaps and file input/output to count word frequencies, while the Groovy version uses a default map with integer values and sorts the entries by value before outputting. Both programs take a file, split the contents on whitespace, count each word, and output the results.
The document describes code for making an HTTP request to a server using sockets in Groovy. It defines a SocketAccess class with a main method that creates a socket connected to groovy.codehaus.org on port 80. The socket's input and output streams are used to send the HTTP request and read the response line by line, printing each line.
Easy Going Groovy 2nd season on DevLOVEUehara Junji
The document appears to be a slide presentation about Groovy programming. It includes slides with code samples and descriptions of Groovy features like Grails, Griffon, Spock testing, and integrating Ant tasks. Later slides demonstrate using Groovy with HtmlUnit to programmatically upload a file to a wiki site.
Slides for JJUG(Japan Java User Group) 2009 Fall BOF.
Talking about groovy history, new features in Groovy 1.6,1.7.
Especially focused on AST Transformations.
This document appears to be slides from a presentation about Groovy and Grails. The slides cover topics like: the history of Groovy; Groovy's integration with Java; Groovy's syntax including closures, collections, and meta-programming; and Grails' use of Groovy for web application development. Later slides discuss how Groovy is implemented and distributed, and some Groovy features like Grape for dependencies and Power Assert for assertions.
LispBuilder is lisp interpreter and parser implemented as Groovy’s Builder. LispBuilder accepts Lisp like expression, and can be evaluated on groovy.
http://wiki.github.com/uehaj/LispBuilder
The document discusses using the Grails framework to build web applications on Google App Engine for Java (GAE/J). It mentions that Grails scaffolding and GORM work well with GAE/J's data storage options like BigTable and Memcache. While some Grails features need modification for GAE/J like replacing JSP with GSP and handling cookies differently, Grails is overall a good fit for developing on GAE/J due to similarities with Java EE.
This document discusses the web application framework Grails. It begins by asking what Grails is, then explains that Grails is a web application framework similar to Ruby on Rails but uses the Groovy programming language instead of Ruby. Some key features of Grails mentioned include using Java EE as the base, allowing war file generation, and incorporating tools like Spring Framework, Hibernate, and SiteMesh through the use of Groovy's domain-specific language for development.
This study aims to develop an interactive idea-generation support system that enables users to consider the potential side effects of realizing new ideas.
In idea generation, confirmation bias often leads to an excessive focus on ``convenience,'' which can result in the oversight of unintended consequences, referred to as the ``side effects of convenience.''
To address this, we explored methods to alleviate user biases and expand perspectives through system-supported dialogue, facilitating a broader consideration of potential side effects.
The proposed system employs a stepwise idea-generation process supported by large language models (LLMs), enabling users to refine their ideas interactively.
By dividing the ideation process into distinct stages, the system mitigates biases at each stage while promoting ideas' concretization and identifying side effects through visually supported dialogues.
Preliminary evaluation suggests that engaging with the proposed system fosters awareness of diverse perspectives on potential side effects and facilitates the generation of ideas that proactively address these issues.
論文紹介:「Amodal Completion via Progressive Mixed Context Diffusion」「Amodal Insta...Toru Tamaki
Katherine Xu, Lingzhi Zhang, Jianbo Shi; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, "Amodal Completion via Progressive Mixed Context Diffusion"CVPR2024
https://openaccess.thecvf.com/content/CVPR2024/html/Xu_Amodal_Completion_via_Progressive_Mixed_Context_Diffusion_CVPR_2024_paper.html
Minh Tran, Khoa Vo, Tri Nguyen, and Ngan Le,"Amodal Instance Segmentation with Diffusion Shape Prior Estimation"ACCV 2024
https://uark-aicv.github.io/AISDiff/
7. XML/HTMLを生成するDSL
html {
head {
title "タイトル"
}
body {
h1 "タイトル"
ul {
(1..10).each {
li it
}
}
}
}
<html>
<head>
<title>タイトル</title>
</head><body>
<h1>タイトル</h1><ul>
<li>1</li><li>2</li><li>3</
li><li>4</li><li>5</li><li>6</li><li>7</
li><li>8</li><li>9</li><li>10</li>
</ul>
</body>
</html>