基于UML状态图的测试场景生成法

提出了一种基于UML状态图的测试场景生成方法。测试场景从状态图的基本转换路径中产生,一条转换路径对应一个测试场景。文中给出了从UML状态图获得基本转换路径的算法。该算法从状态图中的初始状态到终止状态进行遍历,得到所有的基本转换路径,根据环路复杂度可得到状态图的基本路径的最大数量,即测试场景的最小数量。根据测试场景设计测试用例,可生成较少而有效的测试用例。     

路径覆盖测试

随着软件的广泛应用及其规模和复杂度不断地提高,软件测试的方法也有许多。本文讨论了完全路径覆盖测试方法和基于控制流图的路径测试的改进方法。     

基于UML状态图的测试技术研究

统一建模语言UML具有定义良好、易于表达、功能强大的特点,同时还提供了非常强大的图例模型.目前,UML统一建模语言已经广泛应用于软件开发之中,而基于UML状态图的测试技术研究,目的就是为了能够有效地发现软件中存在的缺陷和故障,保证相应软件质量.讨论分析了基于UML状态图的测试用例生成技术,提出一种基于UML状态图的测试用例生成方法,生成较少但有效的测试用例,便于实现自动化测试,并介绍了基于状态图的测试覆盖标准,最后讨论了未来可以研究的方向.     

基于路径覆盖的高效编程测试方法研究

目前白盒测试标准,以覆盖程度为依据有6种。其中覆盖程度最高的是路径覆盖,但是传统的用例构造法没有给出达到路径覆盖的方法。本文提出一种能够达到路径覆盖的测试用例编写方法。它用树的形式把程序可能执行的路径解析出来,以达到路径覆盖的目的。此方法在单元测试用例编写中,简单、高效地覆盖程序中各种可能的路径。     

基于UML状态图的测试技术研究

文章讨论了基于UML状态图的测试用例生成方法，在此基础上，讨论了状态图测试中状态识别这一难点的解决方法，最后介绍了基于状态图的测试覆盖标准。     

基于状态图的软件测试

面向对象软件系统是多个类及类间的相互作用实现的,对象的动态性是通过状态间的转换来建模。UML状态图是在软件开发的早期设计阶段确定下来,它描述一个特定对象的所有可能状态以及由于各种事件的发生而引起状态之间的转移。根据面向对象状态图的特点,设计测试用例。     

状态图中基于事件约束的测试路径覆盖策略

提出了一个在状态图中基于事件约束的测试路径覆盖策略,介绍了具有超态的状态图模型,定义了事件约束机制(S-CSPE),在此约束机制上给出了测试路径覆盖策略。最后给出了该策略与CSPE约束覆盖策略和Rapps-Weyuker路径覆盖标准的比较结果。     

嵌入式软件路径覆盖测试的研究

路径覆盖是软件测试中一种十分重要的方法,它使程序的每个分支至少执行一次;针对嵌入式软件测试的特点,提出了嵌入式软件路径覆盖测试的策略,通过模拟测试通用型智能水量计量仪C430主控程序的各个步骤,运用基本路径插桩策略分析计算插桩探针的位置、个数,统计计算整个探针的覆盖面,构造基本路径和实际程序执行路径;测试覆盖率达到71.1%,取得了一定的效果,对增强软件测试方案设计的系统性,提高软件测试质量和效率,起到了较好的作用.     

嵌入式软件的覆盖测试

覆盖测试是验证软件功能结构正确性以及查找问题的非常重要的方法和手段,它要借助一定的工具才能取得较好的效果,满足软件在质量和时间上的双重要求(纯粹的人工测试工作量大、不方便、周期长).如何利用好这方面比较成熟的工具,对其机理的研究及适应性改造是很重要的.本文着重描述这类工具的工作机理,以及对嵌入式软件测试的特殊要求,并以对自主知识产权嵌入式操作系统的测试为例进行说明.     

一种面向测试需求部分覆盖的测试用例集约简技术

软件系统开发中频繁面对局部更新和部分缺陷修改,此时需要选择性回归测试;为降低其测试工作量需要解决部分覆盖用例集约简问题.文中基于选择性回归测试形式化定义多目标用例集约简,并设计HATS算法解决该问题.HATS算法遵循启发式贪婪搜索框架,定义权重因子a平衡两方面目标:其一是减少用例集规模;其二是避免对无关需求的覆盖.实验...     

基于控制流程图的路径覆盖测试的改进方法研究

软件测试是当前软件生成重要的研究课题。文中从源程序开始,引入基本块的方法将源程序转换为相应的控制流程图。并采用图形的方法将路径构造相应的自动机,通过对自动机中回边的处理,生成简化的并与之等价的自动机。经过若干变换后,可在自动机上直观地求出路径覆盖的条数和相应的信息。此方法实现路径覆盖的目标,简化路径覆盖生成过程,步骤直观,且减少路径生成数。     

基于二分搜索的牛耕式全覆盖规划算法研究

针对栅格环境下存在任意形状的静态障碍物问题,提出了结合二分搜索法的牛耕式全覆盖路径规划算法,该算法可以加速寻找下一个未覆盖空间的初始位置,提高了覆盖的效率。对该算法在多种室内环境中进行仿真,仿真结果表明该算法切实可行。另外,通过与其他全覆盖算法进行对比,结果表明该方法能有效地降低重复覆盖率。     

线性独立路径覆盖率的软件测试充分性判别方法

软件测试充分性判别准则是决定一个软件系统是否已经被充分测试的停止准则,而充分性判别准则的关键是它的揭错能力。对充分性判别准则进行了形式化描述,并且讨论了充分性判别准则的性质及准则之间的比较方法。为了给保障软件测试充分性提供理论依据,提出了一个软件测试充分性的度量准则。     

Complete coverage path planning for wheeled agricultural robots

In the agricultural industry, an evolutionary effort has been made over the last two decades to achieve precise autonomous systems to perform typical in-field tasks, including harvesting, mowing, and spraying. One of the main objectives of an autonomous system in agriculture is to improve the efficiency while reducing the environmental impact and cost. Due to the nature of these operations, complete coverage path planning (CCPP) approaches play an essential role to find an optimal path which covers the entire field while taking into account land topography, operation requirements, and robot characteristics. The aim of this paper is to propose a CCPP approach defining the optimal movements of mobile robots over an agricultural field. First, a method based on tree exploration is proposed to find all potential solutions satisfying some predefined constraints. Second, a similarity check and selection of optimal solutions method is proposed to eliminate similar solutions and find the best solutions. The optimization goals are to maximize the coverage area and to minimize overlaps, nonworking path length, and overall travel time. To explore a wide range of possible solutions, our approach is able to consider multiple entrances for the robot. For fields with a complex shape, different dividing lines to split them into simple polygons are also considered. Our approach also computes the headland zones and covers them automatically which leads to a high coverage rate of the field.     

Research on the logic coverage method of white-box testing

Software testing is an effective and direct way to improve the reliability of software. This paper presents a class of white-boxes testing methods-the logic coverage testing methods, and discuses how to design testing cases of the various programmes by using condition coverage method with examples. And makes condition coverage method, statement coverage method and decision coverage method in-depth and detailed comparison. At last, analyzes the current software testing methods.     

基于栅格地图的机器人覆盖路径规划研究

研究了基于接触传感器的机器人覆盖问题,提出了基于栅格地图的内螺旋覆盖(ISC)算法.ISC算法通过边界探索获得环境边界地图之后,在线规划覆盖路径,用距离转变的搜索方法保证了完全覆盖,通过设置gate栅格降低了重复覆盖率.通过对三个房间组成的室内环境的覆盖仿真试验验证了该方法的可行性.     

未知环境下移动机器人遍历路径规划

为提高未知环境下移动机器人遍历路径规划的效率,提出了一种可动态调节启发式规则的滚动路径规划算法.该算法以生物激励神经网络为环境模型,通过在线识别环境信息特征,动态调用静态搜索算法和环绕障碍搜索算法,有效减少了路径的转弯次数.引入虚拟障碍和直接填充算法,解决了u型障碍区域的连续遍历问题.最后通过仿真实验表明了该方法在未知复杂环境下的有效性.     

基于Wright的SA级测试路径生成方法

软件体系结构用来描述系统的高层结构和行为特征,软件体系结构描述语言ADLs是对软件体系结构的形式化描述.在软件体系结构描述语言Wright的基础上,引入了一种图形的表示方法,即以动态行为图(BG图)来表示相关的构件间的动态行为及它们之间的关系,并提出了软件体系结构测试覆盖准则.根据BG图中路径的定义,给出了BG图中测试路径生成算法的基本思想.以C/S体系结构为例,验证了该方法在生成SA级的测试路径上是可行的.     

Generating test data for both path coverage and fault detection using genetic algorithms

The aim of software testing is to find faults in a program under test, so generating test data that can expose the faults of a program is very important. To date, current stud- ies on generating test data for path coverage do not perform well in detecting low probability faults on the covered path. The automatic generation of test data for both path coverage and fault detection using genetic algorithms is the focus of this study. To this end, the problem is first formulated as a bi-objective optimization problem with one constraint whose objectives are the number of faults detected in the traversed path and the risk level of these faults, and whose constraint is that the traversed path must be the target path. An evolution- ary algorithm is employed to solve the formulated model, and several types of fault detection methods are given. Finally, the proposed method is applied to several real-world programs, and compared with a random method and evolutionary opti- mization method in the following three aspects： the number of generations and the time consumption needed to generate desired test data, and the success rate of detecting faults. The experimental results confirm that the proposed method can effectively generate test data that not only traverse the target path but also detect faults lying in it.     

Generating test data for both path coverage and fault detection using genetic algorithms

The aim of software testing is to find faults in a program under test, so generating test data that can expose the faults of a program is very important. To date, current studies on generating test data for path coverage do not perform well in detecting low probability faults on the covered path. The automatic generation of test data for both path coverage and fault detection using genetic algorithms is the focus of this study. To this end, the problem is first formulated as a bi-objective optimization problem with one constraint whose objectives are the number of faults detected in the traversed path and the risk level of these faults, and whose constraint is that the traversed path must be the target path. An evolutionary algorithmis employed to solve the formulatedmodel, and several types of fault detectionmethods are given. Finally, the proposed method is applied to several real-world programs, and compared with a random method and evolutionary optimization method in the following three aspects: the number of generations and the time consumption needed to generate desired test data, and the success rate of detecting faults. The experimental results confirm that the proposed method can effectively generate test data that not only traverse the target path but also detect faults lying in it.