基于频谱增强的软件多故障定位

检测故障是繁琐而耗时的,为了提高传统软件故障定位方法的效率以及精确度,提出了一种基于频谱的故障定位新方法;充分利用了失败的测试用例与故障之间的关系,通过使用频谱增强的方式,采取逻辑与运算的关键技术和方法,对失败的测试用例进行精简,优化失败测试用例中的频谱信息,从而得到频谱增强后的测试用例,克服了冗余测试用例对定位效果的消极影响,再根据新的频谱信息计算可疑度值,最后生成优化后的可疑度排序列表;首次将频谱增强的方法同时运用到单故障与多故障程序场景中,在包含植入故障的西门子程序和真实故障的Defects4j程序中,经实验检测证明本研究方法能够显著减少代码检查的范围,尤其是在高性能范围内(EXAM5%),并且仅通过检查Top-1至少能有效地定位超过原有约20%的故障,结果表明基于频谱增强的故障定位方法有效提升了检测率,可以更好地帮助程序员精准定位故障位置。     

基于UML活动图的用例识别

在面向对象的软件开发过程中,统一建模语言(unified modeling language, UML)的用例图用于捕获用户的需求.传统描述用例的方法一般是开发者根据自己的经验,从需求中人工获取用例.然而,如何自动生成准确的用例仍然是一个待解决的问题.本文提出了一种通过用UML活动图半自动生成用例的方法.首先通过引入形式化模型——统一结构来描述用例图与活动图,其次给出分解活动图的算法,然后根据分解活动图得到的依赖链生成对应的用例的事件流,从而得到用例模型,最后通过所开发的原型CASE工具进行案例的演示,验证了本文所提出的方法的可行性。     

考虑碳排放的综合能源系统“结构-型号-容量”优化模型

综合能源系统能源结构多样,同种设备的不同型号之间价格、性能差异性大,如何在规划阶段确定合理的能源结构、设备型号组合及装机容量是实现运行阶段节约成本的前提。文章在考虑二氧化碳排放量的基础上研究“能源结构-设备型号-装机容量”规划优化模型。首先,构建基于最近邻法(K-nearest-neighbors,KNN)的实例推理技术得出适合拟建设园区的能源结构;其次,构建“外层选型,内层定容”的双层优化框架,考虑碳排放阶梯成本,以全寿命周期总成本最低为优化目标,利用蚁群算法-遗传算法相结合的方式求解最优设备型号组合及最优装机容量。最后,通过算例分析验证所提模型在降低成本上的有效性。     

“信号与系统”课程教学实例

信号频谱分析是“信号与系统”课程中的重点内容,但学生在理解相关概念和理论时常存在较大的困难。针对这种现象,本文介绍了一种信号频谱分析的教学实例。该实例利用傅里叶变换的数值计算方法,对太阳黑子数进行频谱分析,并确定太阳活动的周期。本教学实例注重引导学生理论联系实际,既深化学生对频谱分析的基本概念与基本理论的理解,又有利于培养学生分析解决实际问题的能力。     

Multi-Objective Modified Particle Swarm Optimization for Test Suite Reduction (MOMPSO)

Software testing plays a pivotal role in entire software development lifecycle. It provides researchers with extensive opportunities to develop novel methods for the optimized and cost-effective test suite Although implementation of such a cost-effective test suite with regression testing is being under exploration still it contains lot of challenges and flaws while incorporating with any of the new regression testing algorithm due to irrelevant test cases in the test suite which are not required. These kinds of irrelevant test cases might create certain challenges such as code-coverage in the test suite, fault-tolerance, defects due to uncovered-statements and overall-performance at the time of execution. With this objective, the proposed a new Modified Particle Swarm optimization used for multi-objective test suite optimization. The experiment results involving six subject programs show that MOMPSO method can outer perform with respect to both reduction rate (90.78% to 100%) and failure detection rate (44.56% to 55.01%). Results proved MOMPSO outperformed the other stated algorithms.     

基于案例的文化创意产品设计方法研究

针对文化产品的造型设计,将与产品造型相关的设计元素细分为功能、行为、文化、情感和构造法五个方面,结合基于案例的设计(case-based design,CBD)技术、遗传算法以及形状文法知识,建立文化创意产品设计概念原型系统并对文化创意产品进行引导设计。提出产品造型相关设计元素多目标优化模型,对用户需求进行匹配操作。提出文化产品造型设计方法模型,结合产品基因树交叉操作与形状文法知识,将现代类产品与文化器物类产品的设计元素进行交叉重组。通过对产品造型相关设计元素进行深入研究,并在文化创意产品设计概念原型系统中融入基于案例的设计技术、遗传算法和形状文法的知识,辅助设计师对文化产品进行创意设计。以小音箱为例,验证了该方法的可行性,为文化产品设计提供了一种有效方法。     

Self-reinforcing mechanisms for cellularisation: a longitudinal case study

Firms that adopt cellular manufacturing (CM) often need to restructure their products, personnel, equipment, factory management and organisation culture. Despite voluminous literature on CM, only a few case studies related to cellularisation exist. Therefore, to enhance understanding in this area, this paper presents a longitudinal case study on cellularisation in an electronic assembly plant. Six years of data were collected from the observations and discussions of an industrialist and an academician. Events instrumental to the persistence of CM were highlighted, with reference to path dependence analysis. Cellularisation is not entirely evolutionary or teleological but is an interplay of the two; it is significantly influenced by the positive feedback of self-reinforcing mechanisms after departing from critical junctures. The observed self-reinforcing mechanisms were expounded and divided into six categories.     

An Optimal Solution for Test Case Generation Using ROBDD Graph and PSO Algorithm

Software testing is one of the most important techniques to examine the behavior of the software products to assure their quality. An effective and efficient testing approach must balance two important but conflicting requirements. One of them is the accuracy that needs a large number of test cases for testing, and the second one is reducing the time and cost, which requires a few test cases. Even for small software, the number of possible test cases is typically very large, and exhaustive testing is impractical. Hence, selecting appropriate test suite is necessary. Cause–effect graph testing is a common black‐box testing technique, which is equivalently representing Boolean relations between input parameters. However, the other traditional black‐box strategies cannot identify the relations that it may result in loss of some of the important test cases. Although the cause–effect graph is regarded very promising in specification testing, it is observed that most of the proposed approaches using the graph are complex or generate impossible and a large number of test cases. This observation has motivated our research to propose an efficient strategy to generate minimal test suite that simultaneously achieves high coverage of input parameters. To do so, at first, we identify major effects from the cause–effect graph using reduced ordered binary decision diagram (ROBDD). ROBDD makes the related Boolean expression of the graph concise and obtains a unique representation of the expression. Using the ROBDD, it is possible to reduce the size of the generated test suite and to perform testing faster. After that, our proposed method utilizes particle swarm optimization (PSO) algorithm to select the optimal test suite, which covers all pairwise combinations of input parameters. The experimental results show that our approach simultaneously achieves high efficacy and reduces cost of testing by selecting appropriate test cases, respectively, to both test size and coverage size. Also, it outperforms some existing state‐of‐the‐art strategies in the black‐box testing. Copyright © 2015 John Wiley & Sons, Ltd.     

摄影作品在设计中的应用研究

目的探究摄影作品在艺术设计中的应用方式。方法结合艺术设计学、美术学、广告学、传播学理论知识,采用案例分析法、观察研究法、归纳法等方法,归纳艺术设计中摄影作品的具体处理手法。结论摄影与艺术设计的融合是现代艺术设计的创意灵魂,既符合消费者的审美求,又蕴藏有巨大的商业价值,对于现代艺术设计具有重要的指导意义。     

Test Case Prioritization in Unit and Integration Testing: A Shuffled-Frog-Leaping Approach

Both unit and integration testing are incredibly crucial for almost any software application because each of them operates a distinct process to examine the product. Due to resource constraints, when software is subjected to modifications, the drastic increase in the count of test cases forces the testers to opt for a test optimization strategy. One such strategy is test case prioritization (TCP). Existing works have propounded various methodologies that re-order the system-level test cases intending to boost either the fault detection capabilities or the coverage efficacy at the earliest. Nonetheless, singularity in objective functions and the lack of dissimilitude among the re-ordered test sequences have degraded the cogency of their approaches. Considering such gaps and scenarios when the meteoric and continuous updations in the software make the intensive unit and integration testing process more fragile, this study has introduced a memetics-inspired methodology for TCP. The proposed structure is first embedded with diverse parameters, and then traditional steps of the shuffled-frog-leaping approach (SFLA) are followed to prioritize the test cases at unit and integration levels. On 5 standard test functions, a comparative analysis is conducted between the established algorithms and the proposed approach, where the latter enhances the coverage rate and fault detection of re-ordered test sets. Investigation results related to the mean average percentage of fault detection (APFD) confirmed that the proposed approach exceeds the memetic, basic multi-walk, PSO, and optimized multi-walk by 21.7%, 13.99%, 12.24%, and 11.51%, respectively.