UML顺序图的结构化操作语义研究

UML顺序图侧重于展示对象之间的消息交互过程,但其动态语义缺乏形式化的描述,不利于对顺序图模型的准确理解和基于该模型的测试用例生成。为此,依据UML1. 5规范,采用BN定义顺序图的形式化语法,提出了活动点的概念;在此基础上,讨论并给出了单个对象执行消息动作的结构化操作语义以及顺序图模型的整体结构化操作语义,为模型检验和基于顺序图的测试用例生成提供了前提。     

UML活动图的形式语义及分析

UML活动图缺乏精确的动态语义,不利于对其所描述的系统进行形式化的分析、验证和确认。为此,论文结合Petri网给出了包含对象流状态描述的UML活动图的形式语义,并据此对UML活动图的典型流程和其所描述的动态系统的正确性进行了分析。该形式语义覆盖了UML活动图的绝大部分特征,为精确描述工作流程并对其进行分析奠定了基础。     

UML活动图描述工作流模型的执行语义

UML是软件工程中广泛应用的建模语言,但其主要问题是缺少严格的形式化语义,因而描述的模型容易产生歧义.根据UML活动图的语法和工作流系统的特点,为UML活动图定义了一种执行语义.基于时间转变系统模型,将工作流系统的执行描述为时间转变和数据转变两个交替进行的过程.时间转变描述时间的前进,数据转变修改工作流案例的状态,这种语义比层次状态图具有更强的描述并行的能力,比Petri网和进程代数更适合描述工作流模型.     

UML状态机的形式语义

许多大型系统在进行分析和设计时,均采用UML作为需求描述语言,尤其是一些对安全性要求较高的系统,更是广泛采用UML的动态行为描述机制--状态机来描述协议及控制机制.但是,由于UML没有形式化的动态语义,不利于对其所描述的需求进行形式化验证和证明.为了解决这一问题,采用以下方法为UML状态机构建形式语义.把UML状态机中的状态映射到一种项代数上,用归纳的状态项表示状态机的状态.然后,把状态项映射到一种加标记的变迁系统LTS上,LTS-状态是状态机的状态项,LTS-变迁是UML状态机的微步.最后,用Plotk     

UML Statechart图的操作语义

面向对象标准建模语言UML(unified modeling language)缺乏精确的动态语义.根据UML1.1语义文档,提出描述对象状态机的UML Statechart图的形式化操作语义.该语义覆盖了UML Statechart图的绝大部分特征,为UML Statechart图的代码产生、模拟和测试用例生成奠定了基础.根据上述语义,基于Rose98完成了UML Statechart图的测试用例生成和测试过程的模拟.     

关于UML顺序图的结构化操作语义描述的研究

UML规范本身因为描述语言的限制,所以在语义方面有其模糊和难以把握的地方。本文使用结构化操作语义,对其顺序图做了形式化的描述。     

UML活动图的时序逻辑语义

UML活动图可以表示不同抽象级的控制流,很适合用于对系统的行为建模．但是缺乏精确的语义使得难以对它所表示的系统行为进行分析．XYZ／E是一可执行线性时序逻辑语言,既可描述系统的动态行为又可表示程序性质,用它对活动图形式化后,就可在统一的逻辑框架下分析活动图的性质．定义了一个有向图结构用以表示UML活动图,再给出其XYZ／E语义,并用一个例子说明活动图到XYZ／E的语义转换,为进一步的分析提供形式化基础．     

UML顺序图形式化语义的研究综述

为UML顺序图构建形式化语义,不仅有利于精确描述软件系统的动态交互过程,而且有利于进行基于UML模型的分析和验证,是有效提高软件系统可靠性的重要保障。结合近年来国内外对UML顺序图形式化语义的研究工作,分类阐述了各种方法,综合分析和比较了不同方法的工作机制和优缺点,指出了定义UML顺序图语义时需重点关注的问题。最后,对未来的研究工作与研究思路进行了梳理与展望。     

UML实时活动图的形式化分析

统一建模语言(UML)自从成为OMG规范后,应用越来越广泛．但UML没有精确的、形式化的语义阻碍了它的进一步发展．该文基于Petri网,给出带时间约束的UML活动图的形式化描述．与Petri网不同的是,Petri网的时间约束是在跃迁(transition)上,而作者将UML活动图的时间约束放在活动状态上,在此基础上,用整型时间的验证技术对实时活动图的时间性质加以分析,为实时系统的建模打下了基础.     

UML活动图支持的工作流建模分析

首先分析了工作流管理系统的特性，给出了一种工作流执行系统的体系结构。在此基础上，形式化定义了为工作流过程建模的UML活动图结构以及建模规则；通过一个具体的实例描述了建模过程并对模型的执行做了分析。     

基于进程代数的UML序列图的形式语义

UML序列图用于建模实例间动态交互过程．但UML规范并没有给出其形式化的动态语义,这不利于对模型进行形式化验证和证明。本文把序列图中的事件动作及其执行序列映射为进程代数中的进程表达式,利用进程代数语义框架来构建UML序列图的形式语义。首先,建立了序列图到进程代数的语义映射规则;然后用Plotkin风格的结构化操作语义给出并证明务件组合算子演绎规则;最后,归纳定义了算子次序约束条件并证明了其可终止性。     

Event-Based Semantics of UML 2.X Concurrent Sequence Diagrams for Formal Verification

UML 2.X sequence diagrams(SD)are among privileged scenarios-based approaches dealing with the complexity of modeling the behaviors of some current systems.However,there are several issues related to the standard semantics of UML 2.X SD proposed by the Object Management Group(OMG).They mainly concern ambiguities of the interpretation of SDs,and the computation of causal relations between events which is not specifically laid out.Moreover,SD is a semi-formal language,and it does not support the verification of the modeled system.This justifies the considerable number of research studies intending to define formal semantics of UML SDs.We proposed in our previous work semantics covering the most popular combined fragments(CF)of control-flow ALT,OPT,LOOP and SEQ,allowing to model alternative,optional,iterative and sequential behaviors respectively.The proposed semantics is based on partial order theory relations that permit the computation of the precedence relations between the events of an SD with nested CFs.We also addressed the issue of the evaluation of the interaction constraint(guard)for guarded CFs,and the related synchronization issue.In this paper,we first extend our semantics,proposed in our previous work;indeed,we propose new rules for the computation of causal relations for SD with PAR and STRICT CFs(dedicated to modeling concurrent and strict behaviors respectively)as well as their nesting.Then,we propose a transformational semantics in Event-B.Our modeling approach emphasizes computation of causal relations,guard handling and transformational semantics into Event-B.The transformation of UML 2.X SD into the formal method Event-B allows us to perform several kinds of verification including simulation,trace acceptance,verification of properties,and verification of refinement relation between SDs.     

An Operational Semantics for Shared Messaging Communication

Shared Messaging Communication (SMC) has been introduced in [Satya Kiran M.N.V., Jayram M.N., Pradeep Rao, and S.K. Nandy. A complexity effective communication model for behavioral modeling of signal processing applications. In Proceedings of 40th Design Automation Conference, 2003] as a model of communication which reduces communication costs (both in terms of communication latency and memory usage) by allowing tasks to communicate data through special shared memory regions. Sending a reference to an otherwise inaccessible memory regions rather than the data itself, the model combines the advantages of message passing and shared memories. Experimental results have shown that SMC in case of large data payloads clearly outperforms the classical message passing.In this paper we give a formal operational semantics to SMC exhibiting unambiguously the effect of executing an SMC command on local and shared memories. Based on this semantics we show that any program using message passing can be proved to be weakly bisimilar to one based on SMC and that with respect to communication costs the latter is amortised cheaper, [A. Kiehn and S. Arun-Kumar. Amortised bisimulations. In Proceedings of FORTE 2005, number 3731 in Lecture Notes in Computer Science, pages 320–334. Springer-Verlag, 2005].     

An Unboxed Operational Semantics for ML Polymorphism

We present an unboxed operational semantics for an ML-style polymorphic language. Different from the conventional formalisms, the proposed semantics accounts for actual representations of run-time objects of various types, and supports a refined notion of polymorphism that allows polymorphic functions to be applied directly to values of various different representations. In particular, polymorphic functions can receive multi-word constants such as floating-point numbers without requiring them to be boxed (i.e., heap allocated.) This semantics will serve as an alternative basis for implementing polymorphic languages. The development of the semantics is based on the technique of the type-inference-based compilation for polymorphic record operations [20]. We first develop a lower-level calculus, called a polymorphic unboxed calculus, that accounts for direct manipulation of unboxed values in a polymorphic language. This unboxed calculus supports efficient value binding through integer representation of variables. Different from de Bruijn indexes, our integer representation of a variable corresponds to the actual offset to the value in a run-time environment consisting of objects of various sizes. Polymorphism is supported through an abstraction mechanism over argument sizes. We then develop an algorithm that translates ML into the polymorphic unboxed calculus by using type information obtained through type inference. At the time of polymorphic let binding, the necessary size abstractions are inserted so that a polymorphic function is translated into a function that is polymorphic not only in the type of the argument but also in its size. The ML type system is shown to be sound with respect to the operational semantics realized by the translation.