CHARMY: A Framework for Designing and Verifying Architectural Specifications

Introduced in the early stages of software development, the Charmy framework assists the software architect in making and evaluating architectural choices. Rarely, the software architecture of a system can be established once and forever. Most likely poorly defined and understood architectural constraints and requirements force the software architect to accept ambiguities and move forward to the construction of a suboptimal software architecture. Charmy aims to provide an easy and practical tool for supporting the iterative modeling and evaluation of software architectures. From an UML-based architectural design, an executable prototype is automatically created. Charmy simulation and model checking features help in understanding the functioning of the system and discovering potential inconsistencies of the design. When a satisfactory and stable software architecture is reached, Java code conforming to structural software architecture constraints is automatically generated through suitable transformations. The overall approach is tool supported.     

A survey on search-based software design

This survey investigates search-based approaches to software design. The basics of the most popular meta-heuristic algorithms are presented as background to the search-based viewpoint. Software design is considered from a wide viewpoint, including topics that can also be categorized as software maintenance or re-engineering. Search-based approaches have been used in research from the high architecture design level to software clustering and finally software refactoring. Enhancing and predicting software quality with search-based methods is also taken into account as a part of the design process. The background for the underlying software engineering problems is discussed, after which search-based approaches are presented. Summarizing remarks and tables collecting the fundamental issues of approaches for each type of problem are given. The choices regarding critical decisions, such as representation and fitness function, when used in meta-heuristic search algorithms, are emphasized and discussed in detail. Ideas for future research directions are also given.     

基于自学习控制算法优化软件测试用例的研究

研究了软件参数变化条件下,在回归测试中以最快速度修复软件缺陷为目标的软件优化问题,将软件测试过程转化为一个时变系统控制过程,给出了软件测试状态转移矩阵模型。运用学习控制方法,通过二维变因子自学习策略获得软件测试最优测试用例,优化软件测试。仿真结果表明,给出的学习策略优于随机测试和马尔可夫控制策略,对应地检测与排除同样软件缺陷,该控制策略能显著减少回归测试次数,降低测试成本。     

Task construction for model-based design of embedded control software

Constructing runtime tasks, or operating system-level processes/threads, from the components of software design models is crucial to the model-based development of embedded control software. A better method should explore more design choices and reduce the overheads of the runtime system to meet the timing and resource constraints of embedded control software. This paper presents a novel, two-step method for systematic and automatic construction of runtime tasks from software design models. It uses graph transformation to construct a task set meeting system-level end-to-end (e2e) timing constraints. Its first step decomposes the system-level e2e timing constraints into the components' timing constraints, which form a necessary condition for any valid and feasible schedule. The second step iteratively merges the components into tasks and sequences their executions. A thus-constructed task set is proven to meet both intercomponent precedence and system-level e2e timing constraints and to minimize runtime overheads by minimizing the total number of resultant tasks. Our evaluation results based on randomly generated software models have shown that the proposed method outperforms commonly used methods and is also scalable.     

一种并行工程约束分解方法

在并行工程产品开发过程中,往往按照问题的结构特点将较大规模的问题分解成一些子问题,并希望通过求解子问题来获得原问题的解。实际中,分解得到的子问题之间往往不是完全独立的,一般的简单分解方法只能有限地降低求解难度和简化问题规模。如何进一步分解各个子问题间的关系,使各个子问题的设计结果不但满足原问题的总体要求而且还能由此获得优化的总体设计结果是一个重要问题。该文给出了分解的意义,提出了基于约束的优化分解方法。     

基于支持向量机的汉语歧义切分算法

针对于解决交集型伪歧义字段的切分,提出了一种应用支持向量机的汉语歧义切分方法.歧义切分问题可看为一个模式分类问题,为提高字段处理能力,应用支持向量机方法建立分类模型.先对歧义字段进行特征提取,采用互信息来表示歧义字段.求解过程是一个有教师学习过程,从歧义字段中挑选出一些高频伪歧义字段,人工将其正确切分作为训练样本并代入SVM训练得到一个分类模型.在分类阶段将SVM和KNN相结合构造一个新的分类器,对于待识别歧义字段代入分类器即可得到切分结果.实验证明不仅具有一定的识别准确率,而且可以提高歧义切分速度.     

Algorithms for the structural diagnosis and decomposition of sparse,underconstrained design systems

Most design systems and variational geometry scenarios are represented by a set of sparse constraints. Typically, such a system is underconstrained and is solved in an interactive framework by the specification of additional constraints (inputs) by the designer. At the onset of the design solution process, and also after every input operation, it must be determined if the complete set of design constraints (both initial and input) has any redundancies. This defines the structural diagnosis problem. The set of variables and constraints that can then be solved (solution set) has to be identified, along with the most efficient order of solving them. This is the structural decomposition problem. It has been demonstrated in literature that occurrence matrices can be used to represent the structure of design systems. In this context, the diagnosis of the design system can be accomplished by the maximum transversal, and the decomposition process involves the block decomposition of the occurrence matrix representing the system of design constraints. This paper uses certain existing sparse matrix decomposition algorithms to derive algorithms for the structural diagnosis and decomposition of sparse, underconstrained design systems using occurrence matrices.     

A choice relation framework for supporting category-partition test case generation

We describe in this paper a choice relation framework for supporting category-partition test case generation. We capture the constraints among various values (or ranges of values) of the parameters and environment conditions identified from the specification, known formally as choices. We express these constraints in terms of relations among choices and combinations of choices, known formally as test frames. We propose a theoretical backbone and techniques for consistency checks and automatic deductions of relations. Based on the theory, algorithms have been developed for generating test frames from the relations. These test frames can then be used as the basis for generating test cases. Our algorithms take into consideration the resource constraints specified by software testers, thus maintaining the effectiveness of the test frames (and hence test cases) generated.     

Maintenance scheduling problems as benchmarks for constraint algorithms

The paper focuses on evaluating constraint satisfaction search algorithms on application based random problem instances. The application we use is a well-studied problem in the electric power industry: optimally scheduling preventive maintenance of power generating units within a power plant. We show how these scheduling problems can be cast as constraint satisfaction problems and used to define the structure of randomly generated non-binary CSPs. The random problem instances are then used to evaluate several previously studied algorithms. The paper also demonstrates how constraint satisfaction can be used for optimization tasks. To find an optimal maintenance schedule, a series of CSPs are solved with successively tighter cost-bound constraints. We introduce and experiment with an “iterative learning” algorithm which records additional constraints uncovered during search. The constraints recorded during the solution of one instance with a certain cost-bound are used again on subsequent instances having tighter cost-bounds. Our results show that on a class of randomly generated maintenance scheduling problems, iterative learning reduces the time required to find a good schedule. This revised version was published online in June 2006 with corrections to the Cover Date.     

Mapping DTDs to relational schemas with semantic constraints

XML is becoming a prevalent format and standard for data exchange in many applications. With the increase of XML data, there is an urgent need to research some efficient methods to store and manage XML data. As relational databases are the primary choices for this purpose considering their data management power, it is necessary to research the problem of mapping XML schemas to relational schemas. The semantics of XML schemas are crucial to design, query, and store XML documents and functional dependencies are very important representations of semantic information of XML schemas. As DTDs are one of the most frequently used schemas for XML documents in these days, we will use DTDs as schemas of XML documents here. This paper proposes the concept and the formal definition of XML functional dependencies over DTDs. A method to map XML DTDs to relational schemas with constraints such as functional dependencies, domain constraints, choice constraints, reference constraints, and cardinality constraints over DTDs is given, which can preserve the structures of DTDs as well as the semantics implied by the above constraints over DTDs. The concepts and method of mapping DTDs to relational schemas presented in the paper can be extended to the field of XML Schema just with some modifications in related formal definitions.     

Robust nonlinear internal model control of stable Wiener systems

Many process systems can be modeled as a stable Wiener system, which is a stable linear system followed by a static nonlinearity. A nonlinear control design procedure is presented that provides robustness to uncertainties while being applicable to systems with unstable zero dynamics, unmeasured states, disturbances, and measurement noise. The design procedure combines nonlinear internal model control with linear matrix inequality feasibility or optimization problems, such that all robust stability and performance criteria are computable in polynomial-time using readily available software. Application to a pH neutralization case study demonstrates the importance of taking uncertainty into account during the design of controllers for Wiener systems. The approach is generalizable to Hammerstein and sandwich systems, whether well- or poorly conditioned, and to systems with actuator constraints.     

Evolutionary multi-objective portfolio optimization in practical context

This paper addresses evolutionary multi-objective portfolio optimization in the practical context by incorporating realistic constraints into the problem model and preference criterion into the optimization search process. The former is essential to enhance the realism of the classical mean-variance model proposed by Harry Markowitz, since portfolio managers often face a number of realistic constraints arising from business and industry regulations, while the latter reflects the fact that portfolio managers are ultimately interested in specific regions or points along the efficient frontier during the actual execution of their investment orders. For the former, this paper proposes an order-based representation that can be easily extended to handle various realistic constraints like floor and ceiling constraints and cardinality constraint. An experimental study, based on benchmark problems obtained from the OR-library, demonstrates its capability to attain a better approximation of the efficient frontier in terms of proximity and diversity with respect to other conventional representations. The experimental results also illustrated its viability and practicality in handling the various realistic constraints. A simple strategy to incorporate preferences into the multi-objective optimization process is highlighted and the experimental study demonstrates its capability in driving the evolutionary search towards specific regions of the efficient frontier.     

无人机航迹控制模块的优化设计与实现

当前在无人机作业过程中,能够根据预设的目的地信息自主控制飞行的模块,在多个最优方案条件下,需要预设复杂约束条件,否则就会存在寻优过程不收敛的问题,导致控制效果不佳。针对这一问题,研究了无人机航迹自主控制模块的改进设计。设计可以采集无人机的位置、速度等飞行信息,并上传至飞行主控器的模块硬件,软件在符合无人机飞行约束与威胁约束的条件下,规划获取后续飞行的最优航迹点。为了保证无人机飞行距离最短、高度最小,将无人机航迹自主控制问题变成优化问题。在面临多个最优方案条件下,构建基于鲸鱼算法的无人机航迹选择模型,以无人机飞行航线代价最小为目的,使用鲸鱼算法求解无人机航迹自主控制方案,完成软件设计。实验结果显示：使用所设计模块后,无人机可自主控制飞行航迹,成功避开静态威胁因素、动态威胁因素安全飞行至目的地。     

On the choice of consistent canonical form during moment normalization

The key issue in normalization with respect to geometric transformation is how to obtain a consistent canonical form which remains unchanged for different geometric transformation related images. Due to ambiguities inherent in the specified normalization methods, more than one canonical form may occur during the normalization procedure. This causes difficulties in obtaining the expected invariant features or the transformation parameters through normalization. This paper aims to provide general schemes to analyze the ambiguity characteristics and to derive the ambiguity matrices through which ambiguities can be eliminated. Three kinds of ambiguities caused by the multi-roots of high-order polynomials, the symmetrical normalization constraints, and the reflection are addressed and solutions are provided to obtain a consistent canonical form for each kind of ambiguities.     

Supporting learning in a shared design environment

Design is a complex problem solving and knowledge refinement process. Learning is a part of this process that can improve computer based design support systems by using the knowledge representing the experience and expertise of designers. Learning from past design examples, and acquiring new knowledge during the process of design are closely related activities that must be supported by future computer supported design systems.This paper analyses the relation between design and learning activity to propose a learning model of design first. Then it presents the software architecture of a design agent with an inductive learning mechanism. Subsequently it introduces the knowledge representation and learning algorithms in a multi-agent design system. Finally, the paper examines the possible ways in which the proposed learning model and the software architecture can be placed in an industrial and engineering design context for developing application tools for design support.     

Output strutural controllability: a tool for integrated process design and control

This paper seeks to expose the relative merits of output structural controllability (OSC) as an integrative tool for process design and control. Output structural controllability assists the design engineer in flow-sheet selection, via the elimination of uncontrollable flowsheets, and in control structure synthesis. The qualitative nature of the technique means that it can be performed at the early stages of design, when alternative flowsheets have been proposed, but quantitative design parameters are unknown. As such, OSC may significantly reduce the amount of quantitative modelling required, thereby providing a significant cost saving. Two industrial case studies are examined: a wet grinding circuit and the purification section of an ethylene oxide production plant. In both cases, a control structure is synthesised using a protoype software package developed at The University of Queensland. The control structure designs are seen to be operable recommendations, and similar to those employed by both operating companies; designs which were probably the result of much trial-and-error, many iterations and based on far greater (quantitative) information. The integration of process design and control is a difficult problem. This paper demonstrates that OSC is one tool which may be employed by process design and control engineers to address this problem.     

Refining Restriction Enzyme Genome Maps

A genome map is an ordering of a set of clones according to their believed position on a DNA string. Simple heuristics for genome map assembly based on single restriction enzyme with complete digestion data can lead to inaccuracies and ambiguities. This paper presents a method that adds additional constraint checking to the assembly process. An automaton is presented that for any genome map produces a refined genome map where both the clones and the restriction fragments in each clone are ordered satisfying natural constraints called step constraints. Any genome map that cannot be refined is highly likely to be inaccurate and can be eliminated as a possibility.     

基于自由度分析的几何约束凝聚计算方法的改进

采用基于自由度分析的方法,对几何约束问题进行求解,就是用一定的模式在图形的GCG图中,进行不断匹配、求解的过程。对最常用到的几种模式的凝聚计算方法进行了改进,特别是提出可以对非构造性凝聚模式添加部分约束,这些约束的值将作为迭代变量,对约束耦合问题进行约束凝聚,凝聚过程结束后,没有用到的约束作为迭代的目标函数,进行迭代计算,大大减少了解决复杂约束耦合问题所需要的变量数,提高了计算过程的稳定性和计算速度。     

基于实时操作系统μC/OS-Ⅱ的通信管理机的研发

在介绍实时操作系统μC/OS-Ⅱ和通讯规约的基础上,提出了基于嵌入式实时操作系统μC/OS-Ⅱ的通信管理机。从硬件选型、软件实现流程和约定的通信协议上阐述通信管理机的软硬件设计。该管理机具有多种通信接口,支持多种规约的相互转换,能使不同种类的网络相互通信,从而大大提高变电站自动化系统对设备选择的自由度,具有广阔的应用前景。