基于混合算法的知识网运算表达式优化

根据知识化制造的相关概念,为了实现基于用户功能需求的知识网自动生成,研究了知识网多重集运算表达式的优化问题,给出该问题的优化模型,并采用遗传-禁忌搜索混合算法进行求解.在该混合算法中,遗传算法提供并行搜索的主框架,禁忌搜索作为遗传算法的变异算子.通过与遗传算法进行比较,得出该算法有更高的计算效率,对求解该类问题有着很好的效果.     

基于Petri网的软件测试用例生成方法

软件测试数据的生成目前主要采用的人工、半人工的方法,工作量大、测试周期长且容易遗漏;基于Petri网的测试用例生成方法主要应用于场景类测试,通过Petri网理论对测试模型建模,再对模型分析验证,最后生成测试用例集;该方法支持回归生成测试用例集,弥补了对测试用例集需求变化的情况;同时,支持测试用例的自动生成;该方法可以有效地描述系统的状态行为,并且保证了较高的覆盖率指标,有助于提高测试的效率和质量.     

基于模糊知识网的推理机设计

为了简化知识网的重构运算,文中在原有知识网定义的基础上,结合用户对重构出的知识网的满意度和用户需求的多样性,以及模糊数学的相关知识,提出了一种模糊知识网的概念;然后根据模糊知识网与原有知识网的不同,在原有知识网混合运算的基础上重新定义模糊知识网的并、交、差运算,并给出模糊知识网混合运算的算法;最后在混合运算的基础上研究了模糊知识网推理机的设计,并给出了模糊知识网推理机的主要功能模块和设计流程图以及几个主要的界面以实现模糊知识网的自重构。     

基于主干线/分支线模型的配网单线图自动生成方法

配网单线图是一种电气接线图, 其利用规定的图形符号和设备连线对配电网进行可视化, 能显著提高配网管理的效率. 针对配网单线图自动生成实际需要, 本文提供了一种基于主干线/分支线模型的配网单线图自动生成方法. 方法首先进行了主干线分支线的创建和分支布局方向的计算; 然后进行了分支初始布局和局部拉伸; 最后进行了分支局部收缩和自动布线. 经过验证, 基于主干线分支线模型的配网单线图自动生成方法, 能自动生成满足准确性、美观性等要求的单线图.     

基于模糊关联聚类的知识网选择方法

针对知识化制造系统中相似知识网日益增多和用户需求表达不清晰等导致的知识网选择问题,提出一种基于模糊关联聚类的知识网选择方法.综合知识网功能、完善程度和结构等方面构造的相似度具有反映知识网运算规律的特征.将两两知识网的相似度作为聚类数据,降低了高维特征空间的维数.模糊关联矩阵的分解,获得了知识网-类关系.目标知识网与类中类隶属度高的知识网的比较缩小了用户选择范围.最后的实例表明该方法是有效可行的.     

支持服务组合的需求模型及其可满足性判定

服务组合一般是根据用户需求来查找匹配的服务并对其进行组合,但用户需求往往是基于自然语.言的,很难用于服务的自动组合.提出了一种基于环境本体的组合服务需求模型,该模型以环境实体上的意图为基础,将关联意图集定义为任务.引入Petri网作为任务间的控制逻辑关系,并给出了一种判定需求可满足性的方法.最后选择旅行安排作为具体案例...     

一种基于Messy GA的结构测试数据自动生成方法

结构性测试是标识测试用例的基本方法之一.由于程序语言的复杂性以及被测程序的多样性,自动生成结构测试数据的一种有效方法是根据程序运行结果指导生成过程,通过不断迭代,生成符合要求的测试数据集.提出一种基于Messy GA的结构测试数据自动生成方法,将测试覆盖率表示为测试输入集X的函数F(X),并利用Messy GA不需要染色体模式排列的先验知识即可进行优化求解的性质对F(X)进行迭代寻优,进一步提高了搜索的并行性,并最终提高测试覆盖率.对一组标准测试程序和若干实际应用程序的实验结果表明,较之现有基于遗传算法的生成方法,该方法能够以更高的效率生成更高质量的测试数据,并适用于较大规模的程序.     

基于解释结构模型的需求最高优先级设定方法

对用户需求进行排序是软件项目开发的基础。针对当前需求优先级排序方法,将用户需求放在同一层次上进行比较设定优先级,而对需求层次性和对多个需求整体赋予优先级则考虑的不多。从需求的层次性出发,用解释结构模型对需求进行分层处理;然后对顶层需求的相关需求集进行交运算,整体设定需求的最高优先级;最后给出案例分析。结果表明,该方法能够突出需求层次性,直接生成最高优先级需求集,提高需求优先级设定的效率。     

基于字形动态描述库的Webfont汉字生成方法

现有的Webfont汉字生成方法,需要设计专门的字库,工作量大且灵活性差。针对这一问题,将汉字特征点用字形动态描述库记录,在此基础上提出一种新的Webfont汉字的自动生成方法。研究基于特征点描述的汉字笔画提取、连接和优化方法,并对比基于B样条曲线和贝塞尔曲线的字形优化效果。为方便用户进行个性化字体生成,设计了用户自定义字形优化方法。实验结果证明,基于汉字字形动态描述库,用户无需下载字库,即可以在网页上生成符合自身需求的Webfont汉字。     

程序缺陷自动修复研究进展及关键问题

程序缺陷自动修复是指针对程序中存在的缺陷,自动生成相应的程序补丁,进而使程序恢复正常运行.首先,根据补丁生成方式的不同,将程序缺陷自动修复方法划分为4类,分别为基于搜索的、基于语义的、基于机器学习的以及基于错误报告驱动的程序缺陷自动修复方法.基于搜索的程序缺陷自动修复方法运用启发式算法在搜索空间内通过搜索生成程序补丁;基于语义的程序缺陷自动修复方法将修复约束作为合成程序补丁的规约,最后通过约束求解器生成程序补丁;基于机器学习的程序缺陷自动修复方法使用数据集训练并生成修复模型,通过修复模型生成程序补丁;基于错误报告驱动的程序缺陷自动修复方法通过利用程序执行以及用户反馈的错误信息生成程序补丁.本文对以上4类程序缺陷自动修复方法进行了详细阐述;其次,总结了检验程序缺陷自动修复方法及工具修复效果所用到的缺陷库;最后,分析了程序缺陷自动修复在工业界的应用现状并总结了该领域面临的关键问题及未来研究的方向.     

Automatic construction and optimization of knowledge mesh for self-reconfiguration of knowledgeable manufacturing system

This paper deals with an approach to the automatic construction and optimization of the knowledge mesh (KM) based on the user’s function requirements. Once a KM multiple set operation expression is obtained, a new KM can be inferred from the expression by the developed KM-based inference engine and transformed into its corresponding KMS (knowledgeable manufacturing system) software automatically by the developed automatic program construction software so as to realize the self-reconfiguration of the KMS. Thus, the automatic construction and optimization of a KM multiple set operation expression is equivalent to the automatic construction and optimization of its corresponding KM and KMS software. To explore the automatic construction and optimization of the new KM by the user’s function requirements, an automatic construction procedure of a KM aiming at the user’s maximum function-satisfaction is proposed. Firstly, the fuzzy function-satisfaction degree relationships of the users’ requirements for the KM functions are defined, and so are the multiple fuzzy function-satisfaction degrees of the relationships. Secondly, operations (union, intersection and minus) on both fuzzy and multiple fuzzy function-satisfaction degrees are proposed and clarified, along with the proof that there exists a one-to-one mapping between the KM multiple set operation expression and the KM-function-satisfaction degree expression. Then, the optimization model of the KM multiple set operation expression is constructed and proved to be very NP-hard. And finally, the KM multiple set operation expression is optimized by the hybrid genetic-tabu algorithm, with the steps of the KM’s automatic construction presented in detail as well. Based upon the above, the KM’s automatic construction and optimization are illustrated by an actual KM example which corresponds to the management information system (MIS) software used in a vehicle body plant. The proposed approach proves to be very effective.     

Knowledge management, insights from the trenches

In 1999, the Software Productivity Consortium-a not-for-profit alliance of industry, government, and academia-asked our members to indicate which technological advances they need most urgently. Most respondents stressed the need to better leverage an increasingly vast and complex array of intellectual assets. Such assets represent today's new capital, marking a profound shift from more traditional types of capital. To address this urgent need, the Consortium launched a knowledge management (KM) program to develop our competency in knowledge management so that we can better serve our members and to provide products and services that will help members develop their own KM competencies. We focused first on making access to Consortium assets easier through an enterprise portal. Then, to address the larger KM issues, we also partnered with George Washington University and its new Institute for Knowledge Management, which seeks to establish a sound theoretical foundation for KM. Here, we recap the lessons we have learned in pursuing our KM mandate and set forth what we believe are the keys to KM's future success     

Knowledge management at Infosys

Knowledge management (KM) is important to software engineering, because organizations need more than just human capital to successfully distribute and use their employees' knowledge. Knowledge might be inexpensive, but effectively using and managing it is not. This article reviews KM practices at Infosys, highlighting KM's importance and benefits     

A new complicated-knowledge representation approach based on knowledge meshes

This paper presents a new complicated-knowledge representation method for the self-reconfiguration of complex systems such as complex software systems, complex manufacturing systems, and knowledgeable manufacturing systems. Herein, new concepts of a knowledge mesh (KM) and an agent mesh (AM) are proposed along with a new KM-based approach to complicated-knowledge representation. KM is the representation of such complicated macroknowledge as an advanced manufacturing mode, focusing on knowledge about the structure, functions, and information flows of an advanced manufacturing system. The multiple set, KM, and the mapping relationships between both, are then formally defined. The union, intersection, and minus operations on the multiple sets are proposed, and their properties proved. Then, the perfectness of a KM, the redundancy set between the two KMs, and the multiple redundancy set on the redundancy set are defined. Three examples are provided to illustrate the concepts of the KM, multiple set, multiple redundancy set, and logical operations. On the basis of the above, the KM-based inference engine is presented. In logical operations on KMs, each KM is taken as an operand. A new KM obtained by operations on KM multiple sets can be mapped into an AM for automatic reconfiguration of complex software systems. Finally, the combination of two real management modes is exemplified for the effective application of the new KM-based method to the self-reconfiguration of complex systems. It is worth mentioning that KM multiple sets can also be taken as a new formal representation of software systems if their corresponding AMs are the real software systems.     

What Do We Know about Knowledge Management? Practical Implications for Software Engineering

There have been many claims about knowledge management's benefits in software engineering, such as decreased time and cost for development, increased quality, and better decision-making abilities. Although we can find some success stories illustrating these claims, particularly on aspects related to the systems and engineering schools, more research is necessary to explore the intersection between each school and the software engineering field. Researchers should continue to emphasize the need for a broad focus across multiple KM schools to suceed in improving KM's practical application in software engineering.     

Understanding the effect of knowledge management strategies on knowledge management performance: A contingency perspective

The universalistic perspective research on employing a unidimensional knowledge management (KM) strategy has yielded conflicting findings and recommendations in different contexts. This study proposes a contingency model for investigating the effects of KM strategies on KM performance to resolve these contradictions. Drawing on the knowledge-based view (KBV) of the firm, which identifies knowledge type and origin as two key KM dimensions, this study first defines four KM strategies: external codification, internal codification, external personalization, and internal personalization. A multiple contingency model of KM strategy is then developed based on a technology–organization–environment framework. This study proposes that the effectiveness of each KM strategy depends on both external and internal contextual conditions, namely, environmental knowledge intensity and organizational information systems (IS) maturity. To test and validate the contingency model, we analyze data from 141 firms to explain the effects of KM strategies on KM performance. Our results reveal three KM strategies, not including the internal personalization strategy, which have a significant association with KM performance in their hypothesized contexts. This study expands KM strategy research by theoretically developing an advanced contingency model aligned with external and internal contexts and by providing valuable practical suggestions to managers for selecting a KM strategy based on multiple contingencies related to the external and internal conditions of a firm.     

企业知识管理集成关键技术及概念模型研究

知识经济时代下，大规模定制企业能否提供知识含量高的产品或服务，是决定企业竞争能力的关键因素。提高产品或服务的知识含量唯一的途径就是依靠企业知识管理。构建一个切实可行的知识管理解决方案是企业成功实施知识管理的前提。该文基于技术集成平台和文化平台构建企业知识管理解决方案，并从技术与工具的角度，阐述了企业知识管理运作全过程。     

改进的APRIORI算法在试卷系统数据挖掘中的应用

本文通过对数据挖掘技术的研究,采用关联规则法对学生答题数据进行分析,并在关联规则使用中采用改进型的Apriori算法进行运算,构建高频集,并对于高分学生和低分学生的试卷进行了加权处理,使得高频集中的试题在知识点和难度上的关联更加突出,便于在自动组卷时更科学地评价试卷.     

自动装填系统故障检测适配器设计

针对装甲车辆自动装填系统的电气故障检测需求,分析了装甲车辆自动装填系统的基本工作原理和电信号特点,设计了以单片机AT89C52为核心的装甲车辆自动装填系统电气故障检测适配器;该设计具有多CAN通信通道、开关量和模拟量采集、开关量输出功能,构建了适配器与控制终端PC机组成的上下位机测控系统,可应用于我多型号坦克、步兵战车自动装填系统的功能测试和电气故障检测,具有较好的通用性、可靠性和较强抗电磁干扰性能,实际应用效果良好。     

白龟山水库遥测系统北斗卫星信道建设

针对河南省白龟山水库水情自动测报系统的现状,提出以短信和北斗卫星2种信道同时作为系统主信道的升级改造方案,极大地增强系统的稳定可靠性和抵抗自然灾害能力,解决在连续阴雨天气、交流电停电、网络中断等极端条件下系统不能独立正常运行的问题。其在利用北斗通信信道方面作出的成功探索,对其它水情自动测报系统的建设有很好的借鉴意义。