无回溯并行多路径搜索测试向量生成算法

无回溯并行多路径搜索算法（NBMP）在生成测试向量过程中生成基于原始输入端奇异立方和与原始输出端关联的传输立方,并利用生成的奇异立方和传输立方生成测试向量。算法在实现过程采用无须回溯和多路径探索策略。通过分析和实验结果证明算法时间复杂度近似为线性。算法对ISCAS85基准电路中规模最大的8个电路进行实验,将实验结果与传统算法进行比较,结果表明NBMP算法故障覆盖率优于传统算法。     

Automatic, evolutionary test data generation for dynamic software testing

This paper proposes a dynamic test data generation framework based on genetic algorithms. The framework houses a Program Analyser and a Test Case Generator, which intercommunicate to automatically generate test cases. The Program Analyser extracts statements and variables, isolates code paths and creates control flow graphs. The Test Case Generator utilises two optimisation algorithms, the Batch-Optimistic (BO) and the Close-Up (CU), and produces a near to optimum set of test cases with respect to the edge/condition coverage criterion. The efficacy of the proposed approach is assessed on a number of programs and the empirical results indicate that its performance is significantly better compared to existing dynamic test data generation methods.     

Annealing-based heuristics and genetic algorithms for circuit partitioning in parallel test generation

In this paper simulated annealing and genetic algorithms are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuristics, is also proposed and compared with pure tabu search and simulated annealing algorithms, and also with a genetic algorithm. The solutions obtained are compared and evaluated by including the hybrid partitioning algorithm in a parallel test generator which is used to determine the test patterns for the circuits of the frequently used ISCAS benchmark set.     

Evolutionary test data generation: a comparison of fitness functions

Previous research using genetic algorithms to automate the generation of data for path testing has utilized several different fitness functions, assessing their usefulness by comparing them to random generation. This paper describes two sets of experiments that assess the performance of several fitness functions, relative to one another and to random generation. The results demonstrate that some fitness functions provide better results than others, generating fewer test cases to exercise a given program path. In these studies, the branch predicate and inverse path probability approaches were the best performers, suggesting that a two‐step process combining these two methods may be the most efficient and effective approach to path testing. Copyright © 2005 John Wiley & Sons, Ltd.     

面向云测试的并行测试用例自动生成方法

为实现云计算环境下的高效软件测试,提出一种Web 应用系统功能测试的并行测试用例自动生成方法。该方法首先根据场景流图采用深度优先遍历算法生成并行测试路径,录制组合产生并行测试脚本,并进行参数化处理;然后,使用基于搜索的软件测试(SBST)方法自动生成可经过目标路径的有效测试数据集,脚本与数据耦合形成大量可并行部署的自动化测试用例。为验证方法的有效性设计了自动化云测试原型系统。实验结果表明,该并行测试用例自动生成方法可以高效地为云平台提供测试用例输入,提高测试效率。     

基于GA-PSO算法的路径测试数据自动生成*

为了实现测试数据自动生成,许多遗传算法及其改进算法应用到了测试领域。针对遗传算法具有较强的全局搜索能力,但局部搜索能力较弱,且收敛速度慢的特点。将遗传算法与粒子群算法结合起来形成新的混合算法（GA-PSO）,并成功应用到软件测试数据自动生成过程中。实验结果表明,该算法结合了遗传算法和粒子群算法的优点,在保证软件测试数据正确生成的情况下,极大地提高了数据生成的效率。     

A lower cost graphics system for VLSI design,design rule checking and pattern generation

Increasing interest by traditional systems houses in the design of custom and semi-custom integrated circuits (LSI and VLSI) provided the impetus for the development of a lower cost interactive graphics systems (IGS) for VLSI design, design verification, and the efficient generation of optical pattern generation and electron beam control files.While extremely attractive, but expensive, IGS units are available from such manufactures as Applicon and Calma for use in very large design groups, it was felt that a lower cost system incorporating the latest in design aids was needed for smaller or geographically dispersed design operations. This paper describes the implementation of one such system, and examines the various implementation options which must be examined by any group which might wish to build or acquire such a capability.     

混合粒子群算法的软件测试数据自动生成

针对全连接拓扑结构的粒子群算法在生成测试数据过程中,存在收敛精度低,易陷入局部极值的问题,提出一种混合粒子群算法HPSO,并将其应用于测试数据自动生成。该算法在保证全局收敛性的前提下,对多样性匮乏的种群,首先采用定长环形拓扑结构取代粒子群的全连接拓扑结构;其次,采用轮盘赌方法选择候选解,更新粒子位置信息和速度信息;最后引入条件禁忌算法,对处于局部极值的粒子采取禁忌处理。通过实验比较表明:与基本粒子群算法(BPSO)相比,HPSO使种群多样性得到大幅度提升;在测试数据生成性能上,HPSO的搜索成功率和路径覆盖率均优于遗传算法与粒子群算法混合算法GA-PSO,而平均耗时与BPSO算法相当,性能表现优越。     

Search‐based software test data generation: a survey

The use of metaheuristic search techniques for the automatic generation of test data has been a burgeoning interest for many researchers in recent years. Previous attempts to automate the test generation process have been limited, having been constrained by the size and complexity of software, and the basic fact that, in general, test data generation is an undecidable problem. Metaheuristic search techniques offer much promise in regard to these problems. Metaheuristic search techniques are high‐level frameworks, which utilize heuristics to seek solutions for combinatorial problems at a reasonable computational cost. To date, metaheuristic search techniques have been applied to automate test data generation for structural and functional testing; the testing of grey‐box properties, for example safety constraints; and also non‐functional properties, such as worst‐case execution time. This paper surveys some of the work undertaken in this field, discussing possible new future directions of research for each of its different individual areas. Copyright © 2004 John Wiley & Sons, Ltd.     

Java存储过程的自动生成与测试

通过定义存储过程模板,并根据表信息替换模板中的变量,从而生成大量具有类似处理流程的Java存储过程.给出了Update存储过程的生成模板、注册模板以及测试程序模板,并用VBA实现了自动生成Java存储过程的主要方法,还讨论了测试数据的准备、测试及测试结果的确认方法.实践表明,该方法能保证软件的质量、缩短开发周期以及提高软件的可修改性.     

基于局域网的有限元网格分布式并行生成

在常见的PC＋Windows＋LAN环境下,采用Winsock API网络通信接口实现了局域网上的分布式并行有限元网格生成。网格生成区域在服务器上按照工作站数量被分解为若干个子区域,这些子区域及网格控制参数通过局域网（LAN）传给工作站。子区域在工作站上被剖分成子网格并通过局域网传回服务器以合并形成最终网格。算例表明只要有足够的计算节点,分布式并行技术可以将网格生成速度大幅度提高,而网络通信所占时间的比例基本固定。     

一种基于混沌搜索的IDDT测试产生算法*

针对瞬态电流测试提出了一种测试产生算法。该算法利用改进FAN算法的反向蕴涵部分激活故障并将测试向量空间映射到混沌空间,采用混沌搜索来确定未确定的测试向量位。模拟实验结果表明,将这种方法用于瞬态电流测试产生是可行的。     

OBDD在组合逻辑电路测试中的应用研究

传统的组合逻辑电路测试方法在搜索过程中都不可避免地要进行反向回溯,由于反向回溯的次数过多,往往会降低算法的效率,文中利用OBDD来表示电路中每个节点所代表的逻辑函数,把传统算法中的反向回溯过程转换为OBDD图的问题,从而加快了故障测试的速度,同时,OBDD在测试矢量集的生成以及必要值的确定中也显示出一定的优越性。     

基于演化算法的结构测试数据自动生成方法评述

结构测试数据自动生成是结构测试结构测试数据自动生成方法后,重点对基于演化算法的结构测试数据自动生成方法加以评述.归纳了该方法的基本思想和基本流程,按照适应度函数构造方式的不同将其划分为面向覆盖法、面向距离法和综合法三大类,并结合相关文献分析了这三类方法各自的技术特点,比较了各自的优劣.最后,指出了存在的不足,探讨了发展方向.     

基于机群架构的并行数据库实现技术研究

在总结了现有并行数据库实现模型的基础上,基于"半重写变换"模型[1]实现了一个并行数据库系统的原型.通过对数据划分/重划分、并行选择、并行排序、并行连接等关键操作的实验分析,指出了.半重写变换"模型存在的缺陷,并提出了一种混合式的改进模型.从理论上说,在机群架构下实现并行数据库系统,这种混合模型较单一模型更有优势.     

Automatic string test data generation for detecting domain errors

Domain testing is designed to detect domain errors that result from a small boundary shift in a path domain. Although many researchers have studied domain testing, automatic domain test data generation for string predicates has seldom been explored. This paper presents a novel approach for the automatic generation of ON–OFF test points for string predicate borders, and describes a corresponding test data generator. Our empirical work is conducted on a set of programs with string predicates, where extensive trials have been done for each string predicate, and the results are analysed using the SPSS tool. Conclusions are drawn that: (i) the approach is promising and effective; (ii) there is a strong linear relationship between the performance of the test generator and the length of target string in the predicate tested; and (iii) initial inputs, no shorter than the target string and with characters generated randomly, may enhance the performance in the test data generation for string predicates. Copyright © 2009 John Wiley & Sons, Ltd.     

EFSM模型的字符串类型测试数据自动生成

基于软件描述模型的测试数据自动生成研究中,字符串类型测试数据生成是一个研究热点和难点。EFSM模型是一种重要的软件描述模型。分析了EFSM模型的特点,针对面向EFSM模型目标路径的字符串测试数据生成,建立了字符串输入变量模型和操作模型,结合静态测试的特点,给出了通过字符串变量模型在目标路径上的符号执行结果生成字符串类型测试数据的方法。实验结果表明,该方法能够达到预期效果,提高测试生成效率。     

多路径测试数据自动生成方法及应用

以程序结构测试自动生成为研究背景,提出了一种重叠路径结构用以描述程序路径,并以此为基础设计了一种多路径测试数据生成适应值算法,实现了一次搜索完成多条路径的测试数据生成。算法通过目标路径间共享遗传算法产生的中间个体减少单一路径搜索始于随机产生的无序个体的初期迭代,从而加快搜索收敛的速度。应用于常用的基准程序和取自实际项目的程序,该算法与典型的分支谓词距离算法相比平均消耗时间缩短了70.6%。     

Evolutionary algorithms for the multi‐objective test data generation problem

Automatic test data generation is a very popular domain in the field of search‐based software engineering. Traditionally, the main goal has been to maximize coverage. However, other objectives can be defined, such as the oracle cost, which is the cost of executing the entire test suite and the cost of checking the system behavior. Indeed, in very large software systems, the cost spent to test the system can be an issue, and then it makes sense by considering two conflicting objectives: maximizing the coverage and minimizing the oracle cost. This is what we did in this paper. We mainly compared two approaches to deal with the multi‐objective test data generation problem: a direct multi‐objective approach and a combination of a mono‐objective algorithm together with multi‐objective test case selection optimization. Concretely, in this work, we used four state‐of‐the‐art multi‐objective algorithms and two mono‐objective evolutionary algorithms followed by a multi‐objective test case selection based on Pareto efficiency. The experimental analysis compares these techniques on two different benchmarks. The first one is composed of 800 Java programs created through a program generator. The second benchmark is composed of 13 real programs extracted from the literature. In the direct multi‐objective approach, the results indicate that the oracle cost can be properly optimized; however, the full branch coverage of the system poses a great challenge. Regarding the mono‐objective algorithms, although they need a second phase of test case selection for reducing the oracle cost, they are very effective in maximizing the branch coverage. Copyright © 2011 John Wiley & Sons, Ltd.