A fuzzy theoretical approach to case-based representation and inference in CISG

In a legal expert system based on CBR (Case-Based Reasoning), legal statute rules are interpreted on the basis of precedents. This interpretation, because of its vagueness and uncertainty of the interpretation cannot be handled with the means used for crisp cases. In our legal expert system, on the basis of the facts of precedents, the statute rule is interpreted as a form of case rule, the application of which involves the concepts of membership and vagueness. The case rule is stored in a data base by means of fuzzy frames. The inference based on a case rule is made by fuzzy YES and fuzzy NO, and the degree of similarity of cases. The system proposed here will be used for legal education; its main area of application is contract, especially in relation to the United Nations Convention on Contracts for the International Sale of Goods (CISG).     

A case-based reasoning approach for building a decision model

A methodology based on case-based reasoning is proposed to build a topological-level influence diagram. It is then applied to a project proposal review process. The formulation of decision problems requires much time and effort, and the resulting model, such as an influence diagram, is applicable only to one specific problem. However, some prior knowledge from the experience in modeling influence diagrams can be utilized to resolve other similar decision problems. The basic idea of case-based reasoning is that humans reuse the problem-solving experience to solve new problems.
In this paper, we suggest case-based decision class analysis (CB-DCA), a methodology based on case-based reasoning, to build an influence diagram. CB-DCA is composed of a case retrieval procedure and an adaptation procedure. Two measures are suggested for the retrieval procedure, one a fitting ratio and the other a garbage ratio. The adaptation procedure is based on decision-analytic knowledge and decision participants' domain-specific knowledge. Our proposed methodology has been applied to an environmental review process in which decision-makers need decision models to decide whether a project proposal is accepted or not. Experimental results show that our methodology for decision class analysis provides decision-makers with robust knowledge-based support.     

Analogy-based domain analysis approach to software reuse

Domain analysis is an expansion of conventional requirements analysis. Domain analysis can support effective software reuse. However, domain analysis is time consuming and is limited to a particular application area. Analogical approaches to software reuse, on the other hand, often occur across domains. Analogical problem solving is a process of transferring knowledge from a well-understood base domain to a new target problem area. Analogy can facilitate software reuse for poorly understood problems or new application areas. Analogy shares similar concepts with reuse and some analogy theories have been applied to software reuse. However, current research on software analogy often overlooks the importance of analysis for the base domain and does not consider some critical aspects of analogy concepts. Reuse must be based on high quality artifacts, especially reuse across domains. This paper presents an approach to integrate domain analysis and analogy methods. In our view, domain analysis and software analogy have complementary roles. Domain analysis is regarded as a process to identify and supply necessary information for analogical transfer. Software analogy can provide the analyst with similar problems and solutions to reuse previous domain analysis knowledge or artifacts for a new domain. This paper presents case studies to demonstrate the increase of efficiency in applying the approach. Evaluation of the approach from various perspectives is also reported.     

Dual programming approach to software testing

The testing phase of the software development process consumes about one-half of the development time and resources. This paper addresses the automation of the analysis stage of testing. Dual programming is introduced as one approach to implement this automation. It uses a higher level language to duplicate the functionality of the software under test. We contend that a higher level language (HLL) uses fewer lines of code than a lower level language (LLL) to achieve the same functionality, so testing the HLL program will require less effort than testing the LLL equivalent. The HLL program becomes the oracle for the LLL version. This paper describes experiments carried out using different categories of applications, and it identifies those most likely to profit from this approach. A metric is used to quantify savings realized. The results of the research are: (a) that dual programming can be used to automate the analysis stage of software testing; (b) that substantial savings of the cost of this testing phase can be realized when the appropriate pairing of primal and dual languages is made, and (c) that it is now possible to build a totally automated testing system. Recommendations are made regarding the applicability of the method to specific classes of applications.     

A Model-Based Approach to Object-Oriented Software Metrics

The need to improve software productivity and software quality has put forward the research on software metrics technology and the development of software metrics tool to support related activities.To support object-oriented software metrics practice efectively,a model-absed approach to object-oriented software metrics is proposed in this paper.This approach guides the metrics users to adopt the quality metrics model to measure the object-oriented software products .The development of the model can be achieved by using a top-down approach.This approach explicitly proposes the conception of absolute normalization computation and relative normalization computation for a metrics model.Moreover,a generic software metrics tool-Jade Bird Object-Oriented Metrics Tool(JBOOMT)is designed to implement this approach.The parser-based approach adopted by the tool makes the information of the source program accurate and complete for measurement.It supports various customizable hierarchical metrics models and provides a flexible user interface for users to manipulate the models.It also supports absolute and relative normalization mechanisms in different situations.     

Integral: Petri-net approach to distributed software development

As the architecture of modern software systems continues to evolve in a distributed fashion, the development of such systems becomes increasingly complex, which requires the integration of more sophisticated specification techniques, tools, and procedures into the conventional methodology. An essential capability of an integrated software development environment is a formal specification method to capture effectively the system's functional requirements as well as its performance requirements. A validation and verification (V&V) system based on a formal specification method is of paramount importance to the development and maintenance of distributed systems.

There has been recent interest in integrating software techniques and tools at the specification level. It is also noted that an effective way of achieving such integration is by using wide-spectrum specification techniques. In view of these points, an integrated V&V system, called Integral, is presented that provides comprehensive and homogeneous analysis capabilities to both specification and testing phases of the life-cycle of distributed software systems. The underlying software model that supports various V&V activities in Integral is primarily based on Petri nets and is intended to be wide spectrum. The ultimate goal of this research is to demonstrate to the software industry, domestic or foreign, the availability and applicability of a new Petri-net-based software development paradigm. Integral is a prototype V&V system to support such a paradigm.     

基于程序分析的通信软件模型驱动测试研究

针对通信软件的模型驱动测试框架中出现的测试生成问题,对MSC测试模型的测试生成方法进行改进,获得有效的系统测试集。采用符号执行和程序分析相结合的方法,收集生成的约束、测试脚本变量与被测系统变量之间的映射关系,据此生成测试模型,进一步进行模型验证和测试生成。这种方法可以对原有的测试集合进行半自动的扩展,对关心的程序路径进行测试覆盖,从而提高测试集合的有效性和完备性。     

基于约束的软件失效域识别与特征分析

随机测试是实践中广泛采用的一种黑盒测试方法.近年来提出的适应性随机测试方法改进了随机测试的不足,仿真实验结果表明,改进效果取决于软件失效域的特征.提出以测试约束刻画软件失效域在输入域上的分布,探讨了基于现有的程序分析技术构造测试约束的过程,讨论了基于测试约束的软件失效域的特征分析方法.以一个实例软件验证所提出的测试约束构造过程及其软件失效域特征分析方法.测试约束揭示了软件故障的触发与传播的内在机制,基于测试约束的软件失效域的特征分析方法有助于改进测试用例的设计质量以及评价适应性随机测试方法的适用性.     

扩展AL log挖掘日志本体的ILP方法*

为发现Web使用记录中所蕴涵的用户访问模式,在深入分析日志本体中事件间的抽象关系后,提出适用于原子事件和复合事件间整分关系推理的ALC传播规则扩展已有的推理模式,并在此基础上提出一种挖掘日志本体的ILP方法。该方法结合描述逻辑和Horn规则在知识表示和推理过程中互补的特点,采用ALlog混合系统构建知识库,利用约束SLD反驳消解和扩展ALC传播规则从日志本体中学习用户访问模式,达到站点商业智能和个性化的目的。最后给出验证该方法的实例,实验结果表明了该方法的可行性和有效性。     

A linear programming approach to reasoning about probabilities

We continue our study, initiated in [9], of the following computational problem proposed by Nilsson: Several clauses (Boolean functions of several variables) are given, and for each clause the probability that the clause is true is specified. We are asked whether these probabilities are consistent. They are if there is a probability distribution on the truth assignments such that the probability of each clause is the measure of its satisfying set of assignments. Since this is a generalization of the satisfiability problem of predicate calculus, it is immediately NP-hard. In [9] we showed certain restricted cases of the problem to be NP-complete, and used the Ellipsoid Algorithm to show that a certain special case is in P. In this paper we use the Simplex method, column generation techniques, and variable-depth local search to derive an effective heuristic for the general problem. Experiments show that our heuristic performs successfully on instances with many dozens of variables and clauses. We also prove several interesting complexity results that answer open questions in [9] and motivate our approach.