CM-Builder: A Natural Language-Based CASE Tool for Object-Oriented Analysis

Graphical CASE (Computer Aided Software Engineering) tools provide considerable help in documenting the output of the Analysis and Design stages of software development and can assist in detecting incompleteness and inconsistency in an analysis. However, these tools do not contribute to the initial, difficult stage of the analysis process, that of identifying the object classes, attributes and relationships used to model the problem domain. This paper describes an NL-Based CASE tool called Class Model Builder (CM-Builder) which aims at supporting this aspect of the Analysis stage of software development in an Object-Oriented framework. CM-Builder uses robust Natural Language Processing techniques to analyse software requirements texts written in English and constructs, either automatically or interactively with an analyst, an initial UML Class Model representing the object classes mentioned in the text and the relationships among them. The initial model can be directly input to a graphical CASE tool for further refinement by a human analyst. CM-Builder has been quantitatively evaluated in blind trials against a collection of unseen software requirements texts and we present the results of this evaluation, together with the evaluation method. The results are very encouraging and demonstrate that tools such as CM-Builder have the potential to play an important role in the software development process.     

AbstFinder, A Prototype Natural Language Text Abstraction Finder for Use in Requirements Elicitation

Abstraction identification is named as a key problem in requirements analysis. Typically, the abstrac-tions must be found among the large mass of natural language text collected from the clients and users. This paper motivates and describes a new approach, based on traditional signal processing methods. for finding abstractions in natural language text and offers a new tool, AbstFinder as an implementation of this approach. The advantages and disadvantages of the approach and the design of the tool are discussed in detail. Various scenarios for use of the tool are offered. Some of these scenarios were used in case study of the effectiveness of rhe tool on an industrial-strength example of finding abstractions in a request for proposals.     

A Model to Disambiguate Natural Language Parses on the Basis of User Language Proficiency: Design and Evaluation

This paper discusses the design and evaluation of an implemented user model in ICICLE, an instruction system for users writing in a second language. We show that in the task of disambiguating natural language parses, a blended model combining overlay techniques with user stereotyping representing typical linguistic acquisition sequences captures user individuality while supplementing incomplete information with stereotypic reasoning     

智能需求获取与建模研究综述

需求获取和建模是指从需求文本或记录中获取显式和隐式的需求,并通过表格化、图形化、形式化等方法构建相应模型的过程,是软件开发过程中极为关键的一步,为后续系统设计与实现铺平道路,提高软件开发效率和质量,提升软件系统稳定性和可行性.研究者们在需求获取与建模方面获得了一系列研究成果,根据其关注阶段不同,可以将它们分为需求知识提...     

基于企业流程的需求分析方法的图形描述机制

企业流程是指为完成企业战略目标而进行的一系列逻辑相关的活动的有序集合,是企业经营活动的表现形式,也是现代信息系统建立的基础。然而传统的需求分析技术并没有体现出企业流程这一概念。论文在分析企业流程特点的基础上,建立了基于企业流程的需求分析方法的图形描述机制,重点叙述了企业流程建模的方法。     

Using Sequence Package Analysis to Improve Natural Language Understanding

Developers of dialogue systems must confront the complexities of natural language. The purpose of this paper is to demonstrate how sequence package analysis, as a novel approach, can help to improve natural language understanding. Such an approach would go beyond the standard grammatical formalisms represented in most dialogue systems, to include context-dependent utterance sequences that are shaped by the unfolding talk. What is then comprised in a sequence package is a series of related turn construction units and turns that make up either single or multiple episodes of talk, and sometimes an entire conversation. The author examines help-related dialogue to show how reports of troubles that often appear ambiguous and vague can be better understood by looking at the sequential design of speakers' turn constructions. Subtle features found in troubles-related talk that are important, but often overlooked, may be identified by mapping out the sequence package arrangement of the talk. For example, a caller's need for vital empathic support, before he or she can be ready to receive help, might be hard to detect if the caller only provides hidden, and possibly contradictory, signs of emotional distress. Or a patient might be unclear and somewhat inconsistent when trying to describe his or her chief complaint in the course of a medical interview. Thus, an analysis of sequence packages can potentially uncover crucial information often buried in the talk. In designing dialogue systems that model spontaneous speech, a sequence package analysis might serve as a basic component of natural language systems.     

自然语言水印鲁棒性分析与评估

自然语言与图像、音频信号的性质截然不同,图像水印等的鲁棒性分析方法不适用于自然语言水印,但是直到目前还没有专门针对自然语言水印鲁棒性的研究和评估工作.文中针对自然语言的特点,提出适合自然语言水印的敌手模型.然后将现有的自然语言水印分类,并总结各类的一般算法模型.利用文本提出的敌手模型分析自然语言水印编码算法的鲁棒性,并通过实验验证鲁棒性的理论模型.本项工作为对比、评估自然语言水印算法的鲁棒性提供了理论依据.     

基于模式匹配的自然语言识别

在自然语言识别过程中,为了提高识别的准确性,我们引入了模式匹配。不仅仅局限于传统的语法-语义分析,而是在语法分析的基础上,结合工程应用来定义最适合自然语言识别的语言模式,然后把模式存入到知识库当中。当需要对自然语言识别时,根据已有模式来匹配句子,从中检索出所需要的信息。文章完整地阐述了这种基于模式匹配的自然语言识别的全过程,并对模式的定义、分析及提取给出了详尽的剖析。最后以一个实验系统证明了此方法的可行性和准确性。     

Aggregation in Natural Language Generation

The content of real‐world databases, knowledge bases, database models, and formal specifications is often highly redundant and needs to be aggregated before these representations can be successfully paraphrased into natural language. To generate natural language from these representations, a number of processes must be carried out, one of which is sentence planning where the task of aggregation is carried out. Aggregation, which has been called ellipsis or coordination in Linguistics, is the process that removes redundancies during generation of a natural language discourse, without losing any information.
The article describes a set of corpus studies that focus on aggregation, provides a set of aggregation rules, and finally, shows how these rules are implemented in a couple of prototype systems. We develop further the concept of aggregation and discuss it in connection with the growing literature on the subject. This work offers a new tool for the sentence planning phase of natural language generation systems.     

复杂软件需求开发方法研究

软件需求开发方法研究是当前复杂软件系统开发中最重要的问题之一。本文首先基于软件开发生命周期模型,对软件需求开发工作进行了介绍。进而总结了软件需求所必须包含的内容,分析了软件需求的特性。基于迭代改进的开发方法,本文将需求开发工作分解为需求捕获、需求分析、需求编写和需求确认四部分活动,并对每部分工作的详细活动和目的进行了分析和总结。软件开发工程实践证明,科学的软件需求开发方法是提高软件开发效率,提高软件开发质量的重要手段。     

A Feasibility Study of Automated Natural Language Requirements Analysis in Market-Driven Development

In market-driven software development there is a strong need for support to handle congestion in the requirements engineering process, which may occur as the demand for short time-to-market is combined with a rapid arrival of new requirements from many different sources. Automated analysis of the continuous flow of incoming requirements provides an opportunity to increase the efficiency of the requirements engineering process. This paper presents empirical evaluations of the benefit of automated similarity analysis of textual requirements, where existing information retrieval techniques are used to statistically measure requirements similarity. The results show that automated analysis of similarity among textual requirements is a promising technique that may provide effective support in identifying relationships between requirements.     

Learning to Parse Natural Language with Maximum Entropy Models

This paper presents a machine learning system for parsing natural language that learns from manually parsed example sentences, and parses unseen data at state-of-the-art accuracies. Its machine learning technology, based on the maximum entropy framework, is highly reusable and not specific to the parsing problem, while the linguistic hints that it uses to learn can be specified concisely. It therefore requires a minimal amount of human effort and linguistic knowledge for its construction. In practice, the running time of the parser on a test sentence is linear with respect to the sentence length. We also demonstrate that the parser can train from other domains without modification to the modeling framework or the linguistic hints it uses to learn. Furthermore, this paper shows that research into rescoring the top 20 parses returned by the parser might yield accuracies dramatically higher than the state-of-the-art.     

需求分析导引

各种需求分析方法各具特点,如果仅使用某种方法在项目实践中往往会困难重重,怎样结合各种需求分析方法之长为项目实践建立一种需求分析参考标准成为一个迫切需要解决的问题。通过对面向问题域、面向对象、模型驱动等分析方法的研究,并结合在项目实践中应用,以面向问题域分析为核心规定需求分析的根本目的与基本活动,结合面向对象的分析与模型驱动分析说明有效建模的技术要点,初步形成一个适合于实际项目活动的需求分析标准的框架。     

一种软件需求描述语言的设计与实现

提出了一种面向软件行为的需求建模方法和需求描述语言BDL,介绍了需求描述语言的设计和实现方法。利用此需求建模可以根据用户的需求信息寻找出目标系统的有效行为,建立目标系统的行为模型。该行为模型可以帮助用户和开发人员正确认识和理解目标系统的行为,而且能为以后自动检测系统的各种特性提供良好的基础。     

面向软件行为和多视点的需求建模方法

提出一种面向软件行为和多视点的需求建模方法,包括建模步骤和建模语言.其中目标系统根据问题域以及视点源被划分成视点.视点在需求模型中以实体的方式存在,每个视点通过从需求规格说明中提取的场景来描述,作为需求模型基本组成单位的场景模型则通过基本的行为复合而成.分析了基于行为和多视点的需求建模过程,讨论了需求建模语言:行为描述语言的语法和语义,并给出相关实例分析以及所实现的建模工具简介.     

音乐专业搜索引擎中的自然语言标引研究

主要是研究如何利用音乐专有名词和专业术语在搜索引擎数据库中进行规范化标引,从而提高网络环境下用户检索的查全率和查准率。     

基于领域需求结构化描述的自动分析建模方法

软件需求描述和需求分析建模一直以来是需求工程的重要工作;且存在紧密的关联;自动化需求分析建模与验证需要以规范的需求描述为基础。提出基于领域需求的结构化描述的自动分析建模方法;通过对系统整体按照一定的组织结构进行描述;描述句式采用富含语义的句型和普通句型相结合的方式;运用自然语言处理相关技术;通过预定义的转换规则对结构化描述下的需求文本进行建模元素识别;实现自动化的建模;最终生成UML图形化分析结果。