Creating and Using Models for Mobile and Rich Internet Applications
为移动和富互联网应用程序创建和使用模型
基本信息
- 批准号:RGPIN-2015-05744
- 负责人:
- 金额:$ 1.31万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The so-called "Rich Internet Applications" (RIAs) are increasingly used for modern applications. They have the ability to update the client-side programmatically and to interact with the server asynchronously. In effect, RIAs are client-server applications, and with wider adaption of HTML5, RIAs will be increasingly stand-alone.
Automatically inferring a model (a.k.a. "crawling") for these RIAs is necessary for tasks such as content indexing, security testing, model-based testing etc. The bulk of the recent research in this domain is based on Finite State Machines (FSM)-based models, where each state represents one possible "Document Object Model" (DOM) of the application, and each transition represents the execution of one JavaScript event. However, these models are unable to scale up to the size of most real RIAs.
In this research, we want to improve model-inference techniques for RIAs and Mobile applications to be able to handle large, complex RIAs and then use these models in the context of automated formal application testing.
The first axis is to build upon our new model, which we have called "Component-Based". The goal is to automatically break down each DOM into a set of independent components, which are then modelled independently from one another. This dramatically reduces the size of the model when compared to the DOM-based model, since it avoids much of the unnecessary duplication inherent to these models. Our initial evaluations have shown that most modern complex RIAs have many of these components, making this model highly applicable. We will in particular work on formally defining this new model and its properties. We will also focus on automatic component detection and efficient modelling algorithms.
Our second axis is automatic user-session reconstructions based on execution logs. This provides the ability to recover the actions of user's offline using common log files. This presents several benefits, including the production of better models (input values, possible sequences of actions etc.), the automatic production of necessary information for further automation (e.g. the ability to infer complete login sequences for automatic testing) and automatic reproduction of faults for debugging purposes.
Our last research axis is to use these models in the context of formal Model-Based Testing. We are particularly interested in the generation of checking sequences in this context (a sequence that proves the conformance of the implementation to our model, under a given fault model).
The results of this research will be of interest to researchers and practitioners alike. It will allow us to expend on an already successful research program, giving us the opportunity to work on topics of general interest in this domain while continuing our shorter-term work with IBM in parallel. Canada is a research leader in the domain of RIAs, and this research program will strengthen that position.
所谓的“富Internet应用程序”(ria)越来越多地用于现代应用程序。它们能够以编程方式更新客户端,并与服务器进行异步交互。实际上,ria是客户机-服务器应用程序,随着HTML5的广泛应用,ria将越来越独立。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Jourdan, GuyVincent其他文献
Jourdan, GuyVincent的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Jourdan, GuyVincent', 18)}}的其他基金
Cyberattacks Countermeasures and Prevention
网络攻击对策与预防
- 批准号:
539938-2019 - 财政年份:2021
- 资助金额:
$ 1.31万 - 项目类别:
Collaborative Research and Development Grants
Creating and Using Models for Mobile and Rich Internet Applications
为移动和富互联网应用程序创建和使用模型
- 批准号:
RGPIN-2015-05744 - 财政年份:2021
- 资助金额:
$ 1.31万 - 项目类别:
Discovery Grants Program - Individual
Cyberattacks Countermeasures and Prevention
网络攻击对策与预防
- 批准号:
539938-2019 - 财政年份:2020
- 资助金额:
$ 1.31万 - 项目类别:
Collaborative Research and Development Grants
Creating and Using Models for Mobile and Rich Internet Applications
为移动和富互联网应用程序创建和使用模型
- 批准号:
RGPIN-2015-05744 - 财政年份:2019
- 资助金额:
$ 1.31万 - 项目类别:
Discovery Grants Program - Individual
Cyberattacks Countermeasures and Prevention
网络攻击对策与预防
- 批准号:
539938-2019 - 财政年份:2019
- 资助金额:
$ 1.31万 - 项目类别:
Collaborative Research and Development Grants
Creating and Using Models for Mobile and Rich Internet Applications
为移动和富互联网应用程序创建和使用模型
- 批准号:
RGPIN-2015-05744 - 财政年份:2018
- 资助金额:
$ 1.31万 - 项目类别:
Discovery Grants Program - Individual
Recovering information from RIAs users access logs
从 RIA 用户访问日志中恢复信息
- 批准号:
490512-2015 - 财政年份:2018
- 资助金额:
$ 1.31万 - 项目类别:
Collaborative Research and Development Grants
Recovering information from RIAs users access logs
从 RIA 用户访问日志中恢复信息
- 批准号:
490512-2015 - 财政年份:2017
- 资助金额:
$ 1.31万 - 项目类别:
Collaborative Research and Development Grants
Creating and Using Models for Mobile and Rich Internet Applications
为移动和富互联网应用程序创建和使用模型
- 批准号:
RGPIN-2015-05744 - 财政年份:2017
- 资助金额:
$ 1.31万 - 项目类别:
Discovery Grants Program - Individual
Recovering information from RIAs users access logs
从 RIA 用户访问日志中恢复信息
- 批准号:
490512-2015 - 财政年份:2016
- 资助金额:
$ 1.31万 - 项目类别:
Collaborative Research and Development Grants
相似国自然基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
- 批准号:31070748
- 批准年份:2010
- 资助金额:34.0 万元
- 项目类别:面上项目
相似海外基金
Collaborative Research: NSFGEO-NERC: Using population genetic models to resolve and predict dispersal kernels of marine larvae
合作研究:NSFGEO-NERC:利用群体遗传模型解析和预测海洋幼虫的扩散内核
- 批准号:
2334798 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Standard Grant
I-Corps: Using neural radiance fields (NeRF) and photogrammetry algorithms for creating 3D models
I-Corps:使用神经辐射场 (NeRF) 和摄影测量算法创建 3D 模型
- 批准号:
2412147 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Standard Grant
Collaborative Research: NSFGEO-NERC: Using population genetic models to resolve and predict dispersal kernels of marine larvae
合作研究:NSFGEO-NERC:利用群体遗传模型解析和预测海洋幼虫的扩散内核
- 批准号:
2334797 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Standard Grant
MCA Pilot PUI: Proxy-model comparison using carbon isotopes from annually banded marine calcifiers and ocean circulation inverse models to evaluate coastal carbon cycle processes
MCA Pilot PUI:使用年度带状海洋钙化物的碳同位素和海洋环流反演模型进行代理模型比较,以评估沿海碳循环过程
- 批准号:
2322042 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Standard Grant
Exploring Tipping Points and Their Impacts Using Earth System Models (TipESM)
使用地球系统模型探索临界点及其影响 (TipESM)
- 批准号:
10090271 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
EU-Funded
Discovering How Stress Induced Histomorphogenesis Effects the Long-term Leaching from an Implanted Medical Device using Phase Field Models
使用相场模型发现应力诱导的组织形态发生如何影响植入医疗器械的长期浸出
- 批准号:
2309538 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Standard Grant
NSFGEO-NERC: Collaborative Research: Exploring AMOC controls on the North Atlantic carbon sink using novel inverse and data-constrained models (EXPLANATIONS)
NSFGEO-NERC:合作研究:使用新颖的逆向模型和数据约束模型探索 AMOC 对北大西洋碳汇的控制(解释)
- 批准号:
2347992 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Standard Grant
NSFGEO-NERC: Collaborative Research: Exploring AMOC controls on the North Atlantic carbon sink using novel inverse and data-constrained models (EXPLANATIONS)
NSFGEO-NERC:合作研究:使用新颖的逆向模型和数据约束模型探索 AMOC 对北大西洋碳汇的控制(解释)
- 批准号:
2347991 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Standard Grant
Unlocking the helminth ‘early infection gap’ using 3D cell culture models
使用 3D 细胞培养模型解锁蠕虫“早期感染间隙”
- 批准号:
DE240100295 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Discovery Early Career Researcher Award
Using cognitive models to understand memorability of real world images
使用认知模型来理解现实世界图像的可记忆性
- 批准号:
DP240101264 - 财政年份:2024
- 资助金额:
$ 1.31万 - 项目类别:
Discovery Projects