Creating and Using Models for Mobile and Rich Internet Applications

所谓的“富互联网应用程序”（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，并与服务器异步交互。实际上，RIA是客户端-服务器应用程序，随着HTML5的广泛适应，RIA将越来越独立。自动推断模型（也称为对于诸如内容索引、安全测试、基于模型的测试等的任务来说，这些RIA的“爬行”（crawling）是必要的。在该领域中的大部分最近的研究是基于基于有限状态机（FSM）的模型，其中每个状态表示应用的一个可能的“文档对象模型”（DOM），并且每个转换表示一个JavaScript事件的执行。然而，这些模型无法扩展到大多数真实的RIA的大小。* 在这项研究中，我们希望改进RIA和移动的应用程序的模型推理技术，以便能够处理大型复杂的RIA，然后在自动化正式应用程序测试的背景下使用这些模型。* 第一个轴是建立在我们的新模型上，我们称之为“基于代理的”。目标是自动将每个DOM分解为一组独立的组件，然后彼此独立地建模。与基于DOM的模型相比，这大大减少了模型的大小，因为它避免了这些模型固有的许多不必要的重复。我们的初步评估表明，大多数现代复杂的RIA都有许多这样的组件，使这个模型非常适用。我们将特别致力于正式定义这个新模型及其属性。我们还将专注于自动组件检测和高效建模算法。*我们的第二个轴心是基于执行日志的自动用户会话重建。这提供了使用常见日志文件恢复用户离线操作的能力。这带来了几个好处，包括产生更好的模型（输入值、可能的行动顺序等），自动生成进一步自动化所需的信息（例如，推断完整登录序列以进行自动测试的能力），并自动再现故障以进行调试。*我们的最后一个研究轴是在正式的基于模型的测试的背景下使用这些模型。我们特别感兴趣的是在这种情况下生成检查序列（一个序列，证明我们的模型的实现一致性，在给定的故障模型）。* 本研究的结果将引起研究人员和从业人员的兴趣。这将使我们能够在一个已经成功的研究项目上投入资金，使我们有机会在这个领域中研究普遍感兴趣的主题，同时继续与IBM进行短期合作。加拿大是区域一体化安排领域的研究领导者，这一研究方案将加强这一地位。

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.**