面向对象软件回归测试技术研究

回归测试的目标之一是在程序修改后,只对进行修改的部分重新测试,从而达到与完全测试相同的测试覆盖.利用数据流或部分数据流技术,对结构化程序进行回归测试的技术已相继提出.随着面向对象方法的逐渐成熟,对面向对象软件测试技术的研究有了迫切的需求.通过分析对象系统的特性,定义了对象之间的依赖关系,通过这个依赖关系,导出测试对象的方法序列,并应用程序切片技术,标识那些受到程序修改影响的测试用例,只有这些测试用例才需要在回归测试中重新执行.最后给出了一完整的对象系统的回归测试解决方案.     

一种新的数据流覆盖测试数据进化生成方法

数据流覆盖可有效地检测软件中的缺陷与错误.针对该覆盖准则中存在的插装监测开销庞大和测试数据生成效率不高的问题,提出一种新的基于定值-引用对覆盖的测试数据进化生成方法.该方法主要分为两部分,首先,通过约减测试目标来减少插装开销,提出的包含关系算法可找到一个定值—引用对子集,使得覆盖该子集就能保证所有测试目标被覆盖;然后,采用遗传算法为所有测试目标生成测试数据,设计的适应度函数综合考虑个体实际执行的路径与每个测试目标的定义明确路径的匹配程度.将该方法用于8个基准程序的测试数据生成,并与其他方法比较,结果显示其可有效提高程序覆盖率和测试数据生成效率.     

测试用例排序的研究

回归测试是一个成本很高的测试过程。为了减少回归测试的成本,可以使用测试用例排序技术。测试用例排序是指按照事先确定的目标重新安排测试用例集中测试用例的执行次序,使得具有高优先级的测试用例比低优先级的测试用例在测试过程中更早执行。本文描述了测试用例排序问题;给出了两个一般测试用例排序算法,即总计排序算法和 附加排序算法;根据不同的覆盖准则（如语句、分支和定义-使用等）,可以从这两个一般算法得到对应的排序算法;最后,讨论了测试用例排序算法的有效性。     

改进型程序切片方法的测试需求约简技术研究

传统的测试用例集约简技术大多采用由测试需求集直接生成测试用例集的方法.该方法虽然能够约简测试用例集,但出现测试需求冗余,约简后的测试用例集不够精准等问题.针对这些问题,提出了一种基于六元结构表的程序切片方法.利用程序切片精简测试代码,省去构造程序依赖图的复杂步骤;根据代码间的相互关系和模块间的耦合度,利用启发式算法约简测试需求;在约简后的测试需求上,精简测试用例集.将该方法应用到当前主流的Android平台上比较约简前后G,GRE的用例集.实验结果表明:约简后的测试需求集能够在获得较少的测试用例集的前提下保证较高的覆盖率.     

Regression test size reduction using improved precision slices

We propose a technique to select regression test cases that is targeted to reduce the size of test suite by using improved precision slices. For this, we first construct the control flow graph model of an object-oriented program. Subsequently, we identify the infeasible paths and compute the definition-use (def-use) pairs only along the feasible paths. Next, we construct the dependency model using this information. This helps us to ignore the dependencies existing along infeasible paths leading to construction of precise slices. Then, we build the dependency model and construct forward slices on the dependency model to determine the affected nodes and the test cases that cover the affected nodes in the dependency graph model are selected for regression testing. The results obtained from our experimental studies indicate that our approach reduces the regression test suite size on an average by 11.25 % as compared to a related approach, without degrading the fault-revealing effectiveness.     

程序切片技术在软件测试中的应用*

基于程序切片的软件测试是一种以程序或程序和需求相结合为基础的测试,它根据程序的不同切片来缩小软件的测试范围、提高软件测试的效率、辅助测试数据的自动生成等.同时由于程序切片不仅考虑了数据依赖和控制依赖,还考虑了程序存在的其他各种依赖关系,使得测试的准确性得到提高.详细阐述了目前存在的各种切片技术及其应用领域,重点探讨了目前切片技术在测试领域中的具体应用.     

一种用于测试数据生成的动态程序切片算法

介绍了程序切片技术的基本概念，提出了一种基于前向分析的动态程序切片算法，探讨了程序切片在软件测试数据生成中的应用，结果表明可以有效地提高基于路径的测试数据生成效率。     

An approach and tool for measurement of state variable based data-flow test coverage for aspect-oriented programs

ContextData-flow testing approaches have been used for procedural and object-oriented programs, and shown to be effective in detecting faults. However, few such approaches have been evaluated for aspect-oriented programs. In such programs, data-flow interactions can occur between base classes and aspects, which can affect the behavior of both. Faults resulting from such interactions are hard to detect unless the interactions are specifically targeted during testing.ObjectiveThis paper presents an approach and tool implementation for measuring data-flow coverage based on state variables defined in base classes or aspects in AspectJ programs. The paper also reports on an empirical study that compares the cost and effectiveness of data-flow test criteria that are based on state variables with two control-flow criteria.MethodEffectiveness of the criteria was evaluated for various fault types. Cost-effectiveness of test suites that cover all state variable definition-use associations (DUAs) was evaluated for three coverage levels: 100%, 90%, and 80%.ResultsThe effort needed to obtain a test case that achieves data-flow coverage is higher than the effort needed to obtain a test case that covers a block or a branch in an advised class. Covering certain data flow associations requires more effort than for other types of data flow associations. The data-flow test criteria based on state variables of a base-class are in general more effective than control-flow criteria.ConclusionsOverall, it is cost-effective to obtain test suites at the 90% coverage level of data-flow criteria.     

Employing static information in the generation of test cases

A commonly used approach for detecting defects in a program is to generate a suite of test inputs which exercises the entire program under a given testing criterion. Current techniques to generate test cases automatically that satisfy a testing criterion choose test input data by considering the testing requirements in an arbitrary order. In this paper, a technique is presented that groups the requirements and orders the generation of the test cases to reduce the number of test cases generated. The grouping is based on the statically determined property of post-dominance. Test cases for each group are generated taking into account requirements for other groups. The use of this technique to generate test cases can be expected to produce fewer test cases that have to be retained with the software. A smaller number of test cases will require less effort and resources to test the software. The technique is especially useful in the maintenance environment, whether retesting of a changed program is done exhaustively or incrementally. The technique not only attempts to minimize the number of test cases generated but also reduces the effort to generate the test cases using the concept of a program slice.     

基于路径引导的回归测试用例集扩增方法

为了全面测试演化软件,回归测试通常需要生成新的测试用例。concolic测试是一种沿着具体执行路径进行符号执行的软件验证技术,通过生成测试数据来执行程序的所有可行路径。回归测试中,由于concolic测试关注于程序本身,没有利用已有测试用例和软件演化信息,导致生成大量无效测试数据,浪费资源和时间。为解决此问题,提出一种基于路径引导的回归测试用例集扩增方法。该方法将目标路径作为引导,根据软件演化信息选择有利于覆盖目标路径的测试用例,利用已有测试用例跳过重叠初始子路径,对后续目标子路径进行concolic测试并生成覆盖目标路径的测试数据。案例分析表明,本文方法相比传统concolic测试,本方法在覆盖程序可行路径的同时,可有效减少concolic测试路径,提高测试数据生成效率。     

UML状态图切片系统的设计与实现

UMI．状态图切片系统是一个基于C＋＋程序UML状态图的切片生成系统。系统生成的LrML状态图切片可应用于C＋＋程序的测试、回归测试、排错、维护等方面。文章主要介绍UML状态图切片系统的设计思想、系统的结构、工作原理以及系统实现的重要技术细节。     

基于数据切片度量JAVA内聚性

面向对象的程序切片在程序分析、程序理解、软件测试和调试以及软件维护方面有着广泛的用途.首先建立了抽象数据切片和类内切片的概念,然后基于这两种切片讨论了JAVA语言中存在的内聚问题,通过分析这些切片与数据、方法、类之间的关系来度量数据、方法以及类的内聚性问题.     

Experiments with test case prioritization using relevant slices

Software testing and retesting occurs continuously during the software development lifecycle to detect errors as early as possible and to gain confidence that changes to software do not introduce defects. Once developed, test suites are reused and updated frequently, and their sizes grow as software evolves. Due to time and resource constraints, an important goal during regression testing of software is to prioritize the execution of test cases in a suite so as to improve the chances of increasing the rate of fault detection. Prior techniques for test case prioritization are based on the total number of coverage requirements exercised by the test cases. In this paper, we present a new approach to prioritize test cases that takes into account the coverage requirements present in the relevant slices of the outputs of test cases. We have implemented three different heuristics based on our relevant slicing based approach to prioritize test cases and conducted experiments to compare the effectiveness of our techniques with those of the traditional techniques that only account for the total requirement coverage. Our detailed experimental study and results provide interesting insights into the effectiveness of using relevant slices for test case prioritization in terms of ability to achieve high rate of fault detection.     

面向对象Java语言的类成员防火墙回归测试

回归测试是软件测试和维护过程中的一种重要过程，当软件经过修改后，为确保程序修改的正确性以及验证修改没有对其它部分产生负面影响，回归测试是不可避免的。本文首先构造成员依赖图，再根据图中各成员之间的关系构建类成员防火墙，分析程序修改所影响的部分。在回归测试中并不需要全部重新测试，仅仅对修改以及修改所影响的部
部分进行重新测试，这样减少了回归测试的时间和成本。     

一种Web服务的测试数据自动生成方法

软件测试是保证Web服务质量的重要技术手段.测试数据生成是Web服务测试的重要内容.测试数据的质量将直接影响Web服务测试的效率和成本.文章基于合约式设计的 Web服务测试技术,提出一种 Web服务的测试数据自动生成方法.首先根据WSDL文档采用随机法自动生成初始测试数据,然后使用合约变异技术进行测试数据的选择,据此可以生成一组达到一定合约变异充分度的有效测试数据,从而提高 Web服务的测试质量和效率.最后实现了一个Web服务的测试数据自动生成工具原型,并通过实验验证了方法的有效性.     

Using hybrid algorithm for Pareto efficient multi-objective test suite minimisation

Test suite minimisation techniques seek to reduce the effort required for regression testing by selecting a subset of test suites. In previous work, the problem has been considered as a single-objective optimisation problem. However, real world regression testing can be a complex process in which multiple testing criteria and constraints are involved. This paper presents the concept of Pareto efficiency for the test suite minimisation problem. The Pareto-efficient approach is inherently capable of dealing with multiple objectives, providing the decision maker with a group of solutions that are not dominated by each other. The paper illustrates the benefits of Pareto efficient multi-objective test suite minimisation with empirical studies of two and three objective formulations, in which multiple objectives such as coverage and past fault-detection history are considered. The paper utilises a hybrid, multi-objective genetic algorithm that combines the efficient approximation of the greedy approach with the capability of population based genetic algorithm to produce higher-quality Pareto fronts.     

用于回归测试数据验算的筛选方法

通过利用覆盖数据技术和回归测试集选择技术,提出一种用于回归测试数据验算的筛选方法,该方法通过深度优先遍历程序的相关记录来筛选测试用例,能有效地提高回归测试的准确性,减少回归测试的测试时间和省略无需测试的测试用例,以达到降低回归测试的成本的目的.对顺序、循环和分支3类程序设计了相关的实验,比较了该算法在这3类程序上的使用效果.     

Regression test selection for C++ software

Regression testing is an important but expensive software maintenance activity performed with the aim of providing confidence in modified software. Regression test selection techniques reduce the cost of regression testing by selecting test cases for a modified program from a previously existing test suite. Many researchers have addressed the regression test selection problem for procedural language software, but few have addressed the problem for object‐oriented software. This paper presents a regression test selection technique for use with object‐oriented software. The technique constructs graph representations for software, and uses these graphs to select test cases, from the original test suite, that execute code that has been changed for the new version of the software. The technique is strictly code based, and requires no assumptions about the approach used to specify or test the software initially. The technique applies to modified and derived classes, and to application programs that use modified classes. Copyright © 2000 John Wiley & Sons, Ltd.     

Reduction-based methods and metrics for selective regression testing

In corrective maintenance, modified software is regression tested using selected test cases in order to ensure that the modifications have not caused adverse effects. This activity of selective regression testing involves regression test selection, which refers to selecting test cases from the previously run test suite, and test-coverage identification. In this paper, we propose three test-selection methods and two coverage identification metrics. The three methods aim to reduce the number of selected test cases for retesting the modified software. The first method, referred to as modification-based reduction version 1 (MBR1), selects a reduced number of test cases based on the modification made and its effects in the software. The second method, referred to as modification-based reduction version 2 (MBR2) improves MBR1 by further omitting tests that do not cover the modification. The third method, referred to as precise reduction (PR), reduces the number of test cases selected by omitting non-modification-revealing tests from the initial test suite. The two coverage metrics are McCabe-based regression test metrics, which are referred to as the Reachability regression Test selection McCabe-based metric (RTM), and data-flow Slices regression Test McCabe-based metric (STM). These metrics aim to assist the regression tester in monitoring test-coverage adequacy, reveal any shortage or redundancy in the test suite, and assist in identifying, where additional tests may be required for regression testing.We empirically compare MBR1, MBR2, and PR with three reduction and precision-oriented methods on 60 test-problems. The results show that PR selects the least number of test cases most of the time and omits non-modification-revealing tests. We also demonstrate the applicability of our proposed methods to object-oriented regression testing at the class level. Further, we illustrate typical application of the RTM and STM metrics using the 60 test-problems and two coverage-oriented selective regression-testing methods.