Formal firewall conformance testing: an application of test and proof techniques

Firewalls are an important means to secure critical ICT infrastructures. As configurable off‐the‐shelf products, the effectiveness of a firewall crucially depends on both the correctness of the implementation itself as well as the correct configuration. While testing the implementation can be done once by the manufacturer, the configuration needs to be tested for each application individually. This is particularly challenging as the configuration, implementing a firewall policy, is inherently complex, hard to understand, administrated by different stakeholders and thus difficult to validate. This paper presents a formal model of both stateless and stateful firewalls (packet filters), including NAT , to which a specification‐based conformance test case generation approach is applied. Furthermore, a verified optimisation technique for this approach is presented: starting from a formal model for stateless firewalls, a collection of semantics‐preserving policy transformation rules and an algorithm that optimizes the specification with respect of the number of test cases required for path coverage of the model are derived. We extend an existing approach that integrates verification and testing, that is, tests and proofs to support conformance testing of network policies. The presented approach is supported by a test framework that allows to test actual firewalls using the test cases generated on the basis of the formal model. Finally, a report on several larger case studies is presented. Copyright © 2014 John Wiley & Sons, Ltd.     

基于策略的网络脆弱性探测系统的研究与实现

针对现有探测系统的不足，采用C／S／Database层次式结构，设计并实现了基于策略的网络脆弱性探测系统。详细讨论了系统的体系结构、探测策略及协作工作流程，扩展设计了脆弱性数据库，提出了一种高效的探测任务调度算法，给出了常规探测、穿透防火墙探测和网络拓扑信息探测等关键功能的实现技术。     

计算机自动评卷策略分析与研究

在大规模计算机基础课考试中,自动阅卷和评分是必然选择。采用DELPHI自主开发了计算机考试系统,以自动评分模块为例,详细介绍和分析了各题型的评分策略及一些关键技术的解决方法。     

计算机自动评卷策略分析与研究

在大规模计算机基础课考试中，自动阅卷和评分是必然选择。采用DELPHI自主开发了计算机考试系统，以自动评分模块为例，详细介绍和分析了各题型的评分策略及一些关键技术的解决方法。     

基于覆盖的软件测试技术在实时嵌入式软件中的应用研究

基于覆盖软件测试技术在实时嵌入式软件中的应用进行的研究，针对实时嵌入式软件测试的特点，文中提出了一个适用于实时嵌入式系统覆盖测试的软件测试模型。并对该模型实现中的核心技术进行了阐明。最后介绍了以上软件测试技术在实际工程项目的应用情况。     

防火墙性能测试研究

防火墙作为应用最广泛的网络安全产品,其本身的性能如何将对最终网络用户得到的实际带宽有决定性的影响,因此对防火墙性能的要求越来越高,性能测试也成为防火墙测试的最重要的一部分。本文结合防火墙性能指标探讨了性能测试指标、常用测试工具,并研究提出了使用测量不确定度评定测试指标值的方法。     

An integrated automatic test data generation system

The Godzilla automatic test data generator is an integrated collection of tools that implements a relatively new test data generation method—constraint-based testing—that is based on mutation analysis. Constraint-based testing integrates mutation analysis with several other testing techniques, including statement coverage, branch coverage, domain perturbation, and symbolic evaluation. Because Godzilla uses a rule-based approach to generate test data, it is easily extendible to allow new testing techniques to be integrated into the current system. This article describes the system that has been built to implement constraint-based testing. Godzilla's design emphasizes orthogonality and modularity, allowing relatively easy extensions. Godzilla's internal structure and algorithms are described with emphasis on internal structures of the system and the engineering problems that were solved during the implementation.Parts of this research were supported by Contract F30602-85-C-0255 through Rome Air Development Center while the author was a graduate student at the Georgia Institute of Technology.     

基于场景模型的DDS架构一体化舰船任务系统测试

以数据分发服务(data-distribution service, DDS)为基础架构的新型一体化舰船任务系统在研发模式、结构和应用方面具有特殊特点, 使得其测试相当具有挑战. 基于模型的测试(model-based testing, MBT)是工业系统测试的一种有效方法. 然而, 对于类舰船任务系统, 由于其自身的...     

分布式计算机应用水平考试系统的设计与实现

传统的基于“集中式”的计算机应用水平考试系统存在诸多弊端，如过分依赖中心服务器、造成服务器的负载过大以及系统的扩展性和安全性差，同时，传统的集中控制模式使得系统的维护变得复杂和困难，介绍了分布式计算机应用水平考试系统的软件结构，描述了系统实现过程中的主要技术，对基于网络的考试系统的安全性，主观题阅卷系统的智能化设计进行了详细论述。     

Model-based automated testing of JavaScript Web applications via longer test sequences

JavaScript has become one of the most widely used languages for Web development. Its dynamic and event-driven features make it challenging to ensure the correctness of Web applications written in JavaScript. A variety of dynamic analysis techniques have been proposed which are, however, limited in either coverage or scalability. In this paper, we propose a simple, yet effective, model-based automated testing approach to achieve a high code-coverage within the time budget via testing with longer event sequences. We implement our approach as an open-source tool LJS, and perform extensive experiments on 21 publicly available benchmarks. On average, LJS is able to achieve 86.5% line coverage in 10 minutes. Compared with JSDEP, a state-of-the-art breadth-first search based automated testing tool enriched with partial order reduction, the coverage of LJS is 11%–19% higher than that of JSDEP on real-world large Web applications. Our empirical findings support that proper longer test sequences can achieve a higher code coverage in JavaScript Web application testing.     

专家系统规则库覆盖度量的研究及实践

针对专家系统规则库的软件测试和评价是保证专家系统质量与可靠性的重要环节。基于数据流的结构化测试技术,提出了一种规则库执行流图RBEF,用于描述规则库中不同规则之间相互连结、制约关系,进而给出了一组规则库覆盖度量准则和测试用例的设计方法,最后讨论了一个已实现并付诸于应用的基于RBEF的软件测试工具ESRTS。     

Model-based testing of a real-time adaptive motion planning system

Abstract

To enable effective and safe operations of autonomous robots in environments with unknowns and unpredictability, a key practical problem is how to test the functionality and assess the performance of real-time motion planning systems. This is a challenge because the underlying algorithms are real-time, sensing-based, and often non-deterministic. These systems’ performance depends on task environments, which can vary in countless ways. Existing testing techniques are designed heavily based on testers’ experience and hardly provide a good coverage of possible test scenarios. This paper introduces a systematic model-based testing (MBT) approach to evaluate the functionality and performance of a real-time adaptive motion planning (RAMP) system. The MBT approach uses the formal communicating extended finite state machine model to model RAMP’s concurrent components and leverage graph traversal algorithms to systematically generate behavioral test cases. First, component integration is considered by modeling the RAMP components and their interactions. Next, system-level testing is considered by modeling mobile obstacles of unpredictable motion behavior. The behavior models are leveraged to generate Abstract Behavioral Test Cases, which are transformed by test data into executable test cases. The test results demonstrate the effectiveness of applying the systematic MBT approach to the evaluation of real-time robotic systems.     

基于LabVIEW的自动测试系统

传统的通信设备测试系统以无线电综合测试仪为中心来搭建,或采用分立仪器搭建、手动测量,这种方法成本高、自动化程度低、扩展性差。因此需要寻求一种解决方案,实现高度集成化、可扩展的测试系统。文章描述了如何采用基于LabVIEW虚拟仪器技术快速方便地开发某通信设备自动测试系统。实验证明,开发的测试系统与传统仪器测试平台相比,测试效率更高,体积更小。此外具有很好的可扩展性,开发工作周期也大大缩短。     

面向深度学习系统的模糊测试技术研究进展

深度学习系统具有强大的学习与推理能力, 在无人驾驶、语音识别和机器人等领域应用广泛. 由于数据集的限制以及依赖人工标签数据, 深度学习系统易于出现非预期的行为. 近年来, 深度学习系统的质量问题受到广泛的关注, 特别是在安全攸关的领域. 由于模糊测试具有较强的故障揭示能力, 运用模糊测试技术对深度学习系统进行测试成为研究热点. 从测试用例生成(包括种子队列构建、种子选择和种子变异)、测试结果判定、覆盖分析3个方面对已有的深度学习系统的模糊测试技术进行总结, 并介绍常用的数据集以及度量指标, 最后对其发展方向进行展望.     

无人机飞行控制系统软件白盒测试用例设计研究

软件测试在软件生存期中占有非常突出的重要地位，也是保证软件质量的重要手段，首先介绍软件测试中白盒测试的方法；然后以某型无人机飞行控制系统软件测试为例，具体研究了无人机飞行控制系统软件白盒测试的测试用例的设计方法，总结了白盒测试的测试用例的设计步骤，比较了几种覆盖准则，指出了修正条件／判定覆盖的优点，提出并讨论了无人机飞行控制系统软件白盒测试的覆盖准则。     

基于电流信息的CMOS SRAM存储单元故障测试

针对深亚微米技术,提出了差分静态电流技术和动态电流技术相结合的方法对CMOS SRAM存储单元进行故障诊断,针对该方法改进了0-1算法。改进的0-1算法与传统的March算法相比,明显降低了测试开销。以四单元存储器为诊断实例,针对桥接故障、开路故障与耦合故障,实现了100%故障诊断覆盖率。实验结果证明了新方法具有故障覆盖率高的特点,能够诊断传统逻辑测试法难以探测的部分故障。     

XML-manipulating test case prioritization for XML-manipulating services

A web service may evolve autonomously, making peer web services in the same service composition uncertain as to whether the evolved behaviors are compatible with its original collaborative agreement. Although peer services may wish to conduct regression testing to verify the agreed collaboration, the source code of the former service may be inaccessible to them. Owing to the black-box nature of peer services, traditional code-based approaches to regression testing are inapplicable. In addition, traditional techniques assume that a regression test suite for verifying a web service is available. The location to store a regression test suite is also a problem. On the other hand, we note that the rich interface specifications of a web service provide peer services with a means to formulate black-box testing strategies. In this paper, we provide a strategy for black-box service-oriented testing. We also formulate new test case prioritization strategies using tags embedded in XML messages to reorder regression test cases, and reveal how the test cases use the interface specifications of web services. We experimentally evaluate the effectiveness of these black-box strategies in revealing regression faults in modified WS-BPEL programs. The results show that the new techniques can have a high chance of outperforming random ordering. Moreover, our experiment shows that prioritizing test cases based on WSDL tag coverage can achieve a smaller variance than that based on the number of tags in XML messages in regression test cases, even though their overall fault detection rates are similar.     

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.     

集成入侵检测引擎的增强型防火墙技术研究

提出了一种增强型防火墙技术,通过把入侵检测引擎集成到传统的包过滤防火墙中,实现两者的协同工作,使得该防火墙在具备传统安全保护功能的同时,还能够根据内嵌的入侵检测引擎的响应结果动态设置过滤规则,及时禁止可能的危险数据通信,从而更好地保护网络安全.给出了该增强型防火墙的系统功能、模块结构和协作机制.测试表明,与传统防火墙相比,该防火墙在应对未知攻击时,具有有效阻断率高的优势.     

DeepRanger:覆盖制导的深度森林测试方法

深度学习软件的结构特征与传统软件存在明显差异,因此即使展开了大量测试,依然无法有效衡量测试数据对深度学习软件的覆盖情况和测试充分性,并造成后续使用过程中依然可能存在大量未知错误.深度森林是一种新型深度学习模型,其克服了深度神经网络存在的一些缺点,例如:需要大量训练数据、需要高算力平台、需要大量超参数.但目前还没有相关工作对深度森林的测试方法进行研究.针对深度森林的结构特点,制定了一组由随机森林结点覆盖率RFNC、随机森林叶子覆盖率RFLC、级联森林类型覆盖率CFCC和级联森林输出覆盖率CFOC组成的测试覆盖率评价指标.在此基础上,基于遗传算法设计了覆盖制导的测试数据自动生成方法DeepRanger,可自动生成能有效提高模型覆盖率的测试数据集.为对所提出覆盖指标的有效性进行验证,在深度森林开源项目gcForest和MNIST数据集上设计并进行了一组实验.实验结果表明,所提出的4种覆盖指标均能有效评价测试数据集对深度森林模型的测试充分性.此外,与基于随机选择的遗传算法相比,使用覆盖信息制导的测试数据生成方法 DeepRanger能达到更高的模型覆盖率.