QualiTeam: A Support Tool When Learning Software Quality and Testing Concepts

QualiTeam is a web application to support the teaching-learning process on Software Quality Assurance, Quality Control and Testing introductory concepts. It has two main objectives: to facilitate the understanding of concepts learned in theory and to facilitate the monitoring of SW projects that students develop. The system gives the teacher control and the students a guide on the activities that must be carried out throughout a software project development. QualiTeam is a tool conceived to help in the challenge of providing students with concrete examples with which they can practice and clarify the topics taught in the classroom. With it, students can apply concepts that, in the initial training of a software engineer, are generally taught only at a theoretical level such as: review process, change requests, trouble reports, document version control and testing documentation management. QualiTeam is free and available online. It has been in operation for 5 years, through which improvements have been made until achieving a quite stable version.

Software Reliability Growth Model for Imperfect Debugging Process Considering Testing-Effort and Testing Coverage

Because of the inevitable debugging lag,imperfect debugging process is used to replace perfect debugging process in the analysis of software reliability growth model.Considering neither testing-effort nor testing coverage can describe software reliability for imperfect debugging completely,by hybridizing testing-effort with testing coverage under imperfect debugging,this paper proposes a new model named GMW-LO-ID.Under the assumption that the number of faults is proportional to the current number of detected faults,this model combines generalized modified Weibull(GMW)testing-effort function with logistic(LO)testing coverage function,and inherits GMW's amazing flexibility and LO's high fitting precision.Furthermore,the fitting accuracy and predictive power are verified by two series of experiments and we can draw a conclusion that our model fits the actual failure data better and predicts the software future behavior better than other ten traditional models,which only consider one or two points of testing-effort,testing coverage and imperfect debugging.

Incorporating S-shaped testing-effort functions into NHPP software reliability model with imperfect debugging

Testing-effort（TE） and imperfect debugging（ID） in the reliability modeling process may further improve the fitting and prediction results of software reliability growth models（SRGMs）. For describing the S-shaped varying trend of TE increasing rate more accurately, first, two S-shaped testing-effort functions（TEFs）, i.e.,delayed S-shaped TEF（DS-TEF） and inflected S-shaped TEF（IS-TEF）, are proposed. Then these two TEFs are incorporated into various types（exponential-type, delayed S-shaped and inflected S-shaped） of non-homogeneous Poisson process（NHPP）SRGMs with two forms of ID respectively for obtaining a series of new NHPP SRGMs which consider S-shaped TEFs as well as ID. Finally these new SRGMs and several comparison NHPP SRGMs are applied into four real failure data-sets respectively for investigating the fitting and prediction power of these new SRGMs.The experimental results show that：（i） the proposed IS-TEF is more suitable and flexible for describing the consumption of TE than the previous TEFs;（ii） incorporating TEFs into the inflected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S-shaped NHPP SRGMs;（iii） the inflected S-shaped NHPP SRGM considering both IS-TEF and ID yields the most accurate fitting and prediction results than the other comparison NHPP SRGMs.

The use of mathematics in software quality assurance

The use of mathematics for documenting, in- specting, and testing software is explained and illus- trated. Three measures of software quality are described and discussed. Then three distinct complementary approaches to software quality assurance are presented. A case study, the testing and inspection of a safety-critical system, is discussed in detail.

Test case generation based on orthogonal table for software black-box testing

Software testing is an important means to assure the software quality. This paper presents a practicable method to generate test cases of software testing, which is operational and high efficient. We discuss the identification of software specification categories and choices and make a classification tree. Based on the orthogonal array, it is easy to generate test cases. The number of this method is less than that of all combination of the choices.

Software Testing Applications Based on a Virtual Reality System

Software testing is an important part of software engineering and has been more and more popular as the rapid growth of the software products market. Good skills of communication with clients and programmers play a significant role for a tester during the test process. This paper presents some important and basic software testing applications （such as static testing, dynamic testing, black-box testing, white-box testing and their combinations） based on a virtual reality system, named as rocket digital simulation system （RDSS）. Different testing methods are exercised during the software developing lifecycle and finally achieving significant quality improvement.

Development Methodologies for Network Softwarization: A Comparison of DevOps, NetOps, and Verification

This white paper explores three popular development methodologies for network softwarization: DevOps, NetOps, and Verification. The paper compares and contrasts the strengths and weaknesses of each approach and provides recommendations for organizations looking to adopt network softwarization.

基于深度学习和遗传算法的方法调用缺陷自动修复方法

为提高软件缺陷自动修复技术的修复效果,针对面向对象程序中出现概率较大的方法调用缺陷,提出一种基于深度学习和遗传算法的方法调用缺陷自动修复方法。基于深度学习构造方法调用缺陷修复模型,使用修复模型生成候选补丁并验证;若补丁无效,则基于这些候选补丁,使用改进的基于遗传算法的缺陷修复方法生成候选补丁。实验结果表明,在Defects4 J数据集上,所提方法与DEAR、TBar、SequenceR和jGenProg自动化缺陷修复工具相比,缺陷修复率和补丁正确率都有提高。

Cooperative Software Testing and Analysis: Advances and Challenges

In recent years, to maximize the value of software testing and analysis, we have proposed the methodology of cooperative software testing and analysis （in short as cooperative testing and analysis） to enable testing and analysis tools to cooperate with their users （in the form of tool-human cooperation）, and enable one tool to cooperate with another tool （in the form of tool-tool cooperation）. Such cooperations are motivated by the observation that a tool is typically not powerful enough to address complications in testing or analysis of complex real-world software, and the tool user or another tool may be able to help out some problems faced by the tool. To enable tool-human or tool-tool cooperation, effective mechanisms need to be developed 1） for a tool to communicate problems faced by the tool to the tool user or another tool, and 2） for the tool user or another tool to assist the tool to address the problems. Such methodology of cooperative testing and analysis forms a new research frontier on synergistic cooperations between humans and tools along with cooperations between tools and tools. This article presents recent example advances and challenges on cooperative testing and analysis.

基于RTC闭环覆盖率驱动的自动化测试系统研究

为解决手工测试、自动化测试过程中漏测问题,优化回归测试,提高测试精准度和执行效率;首先,采用头脑风暴和项目历史经验的方法,分析了软件测试过程中产生漏测的原因,列举了常用解决漏测问题的措施;然后,常用方法只能反应软件开发过程中某一方面会引起软件质量问题,不能在软件全生命周期综合定量反馈软件质量,针对该问题,从软件工程RAD开发模型理论引入需求覆盖、测试用例覆盖、代码覆盖测量指标,分析3个指标之间关联关系,提出“软件需求-代码-测试用例”闭环覆盖率方法监测软件测试质量;其次,设计了基于软件需求、代码、测试用例闭环率驱动的自动化测试系统模型,并阐述了其设计模型和实现方法,同时开发了原型系统;最后,进行案例实验,验证方法可行性和效果,并针对实验过程的问题提出后续改进方向。

Intelligent Management Based on Chemical Reagent Quality Analysis

Access database technology and Visual Basic programming language are used to develop a set of chemical reagents quality analysis and inspection of intelligent management application software, and its stability was investigated. The results show that the sotfware is used to manage intelligently the quality analysis of chemical reagents test each linkage, to upload and save the analysis of test data and results in the network in time for users, to build a network of information sharing platform for enterprises and quality management departments, and its quality of chemical reagents test results is used to manage by the computer with practical application value. The software is simple, convenient, fast, friendly interface, stable operation, accurate and reliable results, with a high value to promote the application.

Food Additives-Ascorbic Acid Quality Assay Test Intelligent Management

In this paper, based on the analysis and test methods of national standards （GB 14754-2010） and chemical analysis and test items carried out by chemical enterprises, a set of automatic processing of quality analysis test data of ascorbic acid products was developed by using access database technology and Visual Basic programming language system, and its stability was investigated. The results show that the software can manage intelligently all aspects of the quality analysis and test of ascorbic acid products, uploading timely the data and results of the analysis and inspection to the network and saving it for users, enterprises and quality management, which set up a network of information sharing platform to ensure the authenticity and reliability of measurement results, improving greatly the speed of data processing, saving valuable time, reducing production costs with good economic efficiency and social benefit. It has practical value for ascorbic acid quality analysis test data processing automatically the results of the implementation of intelligent management.

MonkeyRunner环境用例脚本化的Android软件测试模型

Android平台软件自动化测试能够提升测试质量和效率,降低测试成本,为了代替繁重的人工重复劳动,针对Android操作系统的特点,设计并实现了一种基于MonkeyRunner环境用例脚本化的Android软件测试系统。首先对Android软件测试的API进行分析,然后构建了基于用例脚本化的测试模型,并对该模型得到耦合度适合的测试用例序列进行分析。系统测试结果表明,本文提出的基于Mon-keyRunner环境用例脚本化的Android软件测试系统切实有效,值得推广使用。

Framework for Extensible Application Testing

In recent years large corporations as well as smaller commercial enterprises have begun to devote increased attention to software testing and software quality. This paper introduces a novel tool—the Framework for Extensible Application Testing (FEAT), implemented by the author and applicable for automatic generation and execution of test cases. The paper discusses system requirements, design, architecture and modes of operation. It also contains a detailed comparison of the FEAT framework with existing test environments, focusing in particular on the STAF/STAX framework. The final section is devoted to experimental research into the applicability and efficiency of the presented tools in various projects and configurations, as reflected by quality metrics.

基于敏捷软件开发方法的C语言符号表构造实现研究

信息化飞速发展,需求随之变动,现今社会对软件产品质量的要求逐渐提高。该文首先介绍传统软件开发和敏捷软件开发体系,然后对比分析瀑布模型与极限编程,测试驱动开发与传统软件测试、V模型的各自特点,并结合实际,具体阐释敏捷软件开发方法在C语言符号表的构造实现,最后从测试覆盖率方面评估此次测试集。从测试评估报告结果看,采用先测试再编码步骤的测试驱动开发TDD方法开发的软件,不仅测试更为完备、彻底,而且更适用于需求变动的环境。

“软件质量保证与测试”课程思政建设探索

“软件质量保证与测试”是软件工程专业的核心课程,旨在帮助学生全面了解现代软件测试技术及其主要发展方向,掌握软件测试的工作任务,培养批判性思维和问题解决能力,为学生未来的职业发展和进一步的学术研究奠定坚实的基础。通过将思政教育元素融入“软件质量保证与测试”课程教学中,可以引导学生思考软件质量保证与测试背后所蕴含的价值观,鼓励学生积极思考和讨论软件测试在社会发展中的重要作用,同时提高教师的教育教学水平,以更好地引导学生成长为具有社会责任感和良好道德品质的软件工程专业人才。

基于机器学习识别偶然正确测试用例

基于频谱的故障定位(Spectrum-Based Fault Localization,SBFL)技术已被广泛研究,可以帮助开发人员快速找到程序错误位置,以降低软件测试成本。然而,测试套件中存在一种特殊的测试用例,其执行了错误的语句但能输出符合预期的结果,这种测试用例被称为偶然正确(Coincidental Correct,CC)测试用例。CC测试用例会对SBFL技术的性能产生负面影响。为了减轻CC产生的负面影响,提升SBFL技术性能,文中提出了一种基于机器学习的CC测试用例识别方法(CC test cases Identification via Machine Learning,CCIML)。CCIML结合怀疑度公式特征和程序静态特征来识别CC测试用例,从而提高SBFL技术的故障定位精度。为了评估CCIML方法的性能,文中基于Defects4J数据集进行对比实验。实验结果表明,CCIML方法识别CC测试用例的平均召回率、准确率和F 1分数分别为63.89%,70.16%和50.64%,该结果优于对比方法。除此之外,采用清洗和重标策略处理CCIML方法识别出的CC测试用例后,最终取得的故障定位效果也优于对比方法。其中,在清洗策略和重标策略下,错误语句怀疑度值排在第一位的数量分别为328和312,相比模糊加权K近邻(Fuzzy Weighted K-Nearest Neighbor,FW-KNN)方法,定位到的故障数量分别增长了124.66%,235.48%。

基于冗余覆盖信息约简的软件缺陷定位方法

软件规模和复杂程度的不断提高,为软件质量保障带来了严峻的挑战.软件缺陷定位是一种重要的软件质量保障技术,其中基于频谱的缺陷定位(Spectrum-based Fault Localization,SFL)是应用最为广泛的软件缺陷定位技术,其通过分析语句覆盖信息矩阵计算代码语句的可疑度值,并根据可疑度值定位缺陷所在语句.然而,语句覆盖信息矩阵中存在着严重的数据冗余问题,冗余的数据极大地影响了SFL的缺陷定位性能.以Defects4J数据集中395个程序的语句覆盖信息矩阵为例,在超过一半的语句覆盖信息矩阵中有90%的语句存在与其具有相同覆盖信息的语句.特征选择是常用的数据预处理技术,通过去除冗余和不相关特征来获取原始特征集中有价值的特征子集.因此,我们将语句覆盖信息矩阵作为原始特征集,将冗余覆盖信息约简建模为特征选择问题,提出了一种基于冗余覆盖信息约简的软件缺陷定位方法(Fault Localization based on Redundant coverage information Reduction,FLRR).首先,使用特征选择技术对语句覆盖信息和测试用例执行结果组成的语句覆盖信息矩阵进行约简,得到语句覆盖信息矩阵子集;然后,使用SFL计算语句覆盖信息矩阵子集中语句的可疑度值,并根据可疑度值对语句进行降序排列,以定位缺陷语句.本文使用六种常用的特征选择技术对语句覆盖信息矩阵进行特征选择和约简,以得到语句覆盖信息矩阵子集,并使用四种典型的SFL技术对语句覆盖信息矩阵子集中的语句进行缺陷定位.为评估FLRR的缺陷定位性能,本文使用E_(inspect)@n和MRR(Mean Reciprocal Rank)评价指标在基于Defects4J的数据集上与四种典型的SFL技术进行了对比实验.实验结果表明,FLRR能够有效提升SFL的缺陷定位性能.对于E_(inspect)@n指标,当n=1时,FLRR相比DStar、Ochiai、Barinel和OP2分别多定位到23条、26条、14条和13条缺陷语句,分别增加了69.70%、76.47%、45.16%和38.24%;对于MRR指标,FLRR相比DStar、Ochiai、Barinel和OP2分别提升了20.08%、24.94%、17.45%和19.15%.

星敏感器时间同步设计与测试验证

高分辨率卫星和载荷标校对姿态具有极高的实时性要求,星敏感器测量的是曝光中点时刻的姿态数据,时间同步可以使姿态数据和时间更加精准匹配。首先提出了硬件脉冲信号时间同步设计方法,梳理出硬件脉冲时间同步流程,根据脉冲信号控制星敏感器曝光,对脉冲信号、曝光起始和结束时刻等信号的时序关系进行了详细描述,并给出了基于硬件脉冲信号的曝光中点时刻的计算方法,时间同步延时100ns,时间同步精度达到20ns。随后提出了软件指令时间同步设计方法,梳理出软件指令时间同步流程,并给出了基于软件指令时间基准的曝光中点时刻的计算方法和溢出保护措施,时间同步延时440μs,时间同步精度达到20ns。通过对硬件脉冲信号和软件指令两种时间同步设计进行测试,验证了硬件脉冲信号时间同步计数、曝光时刻、软件指令时间同步、守时计数器等功能。

城市固废焚烧智能算法测试与验证模块化半实物平台

城市固废焚烧(Municipal solid waste incineration,MSWI)过程因工业现场的安全要求和控制系统的封闭特性导致离线研究的各类智能算法难以在线验证.此外,已有的实验室仿真平台难以模拟领域专家基于多模态数据进行智能感知、认知、决策和控制的工业实际.针对上述问题,首先,在综述现有面向工业过程的仿真平台研究现状和所面临挑战的基础上,描述面向MSWI过程智能算法测试与验证平台的需求,提出并构建由多模态历史数据驱动系统、安全隔离与优化控制系统和多入多出回路控制系统组成的模块化半实物平台.然后,在实验室环境中完成平台硬件搭建、工业软件开发、仿真功能实现和典型场景验证,并移植部分模块至工业现场进行应用.最后,总结与展望模块化半实物平台的研究方向.