准完全最大距离伪随机测试研究

对超大规模集成电路进行随机测试的测试码之间的距离作了定量分析,在此基础上,改进了最大距离随机测试算法中测试码的生成方法,使得所生成的伪随机测试码集合同时达到最大海明距离与近似最大笛卡尔距离。因此每一个测试码可以尽可能多地独立检测到更多不重复的故障。进而提出了准完全最大距离测试新算法的思想和构建理论,并详细阐述了该算法的执行流程。在ISCAS'85基准电路上进行的大量实验数据分析表明,本方法确实有效地提高了随机测试效率,降低了随机测试成本。     

软硬件测试中预确定距离测试

在随机测试的基础上提出了VLSI电路测试中的一个新概念,即预确定距离测试.随机测试广泛应用于软硬件测试中已经有多年了.众所周知,随机测试中每个测试码都是随机选取的而不管它是否与先前生成的测试码重复.尽管由于测试码选取的随机性使得随机测试并不是十分有效,但是对它作了一些实质性修改从而大大提高了它的测试效率.在预确定距离测试中,总是选择总距离最大的测试码来进行测试,以便使得该测试码所检测到的故障与先前的测试码所检测到的故障尽可能地不同.还详细介绍了构造一个预确定距离测试序列的生成算法,并将其应用到软件测试中.最后,从基准电路上获得的实验结果以及从理论上的分析也表明这种新方法的有效性.     

3n镜像适应性随机测试算法

针对适应性随机测试中的边缘效应问题,借鉴镜像适应性随机测试(MART)的基本思想,在引入镜像距离的基础上,提出3n MART算法,通过改变候选用例与成功用例之间的距离判断策略,使其产生的用例在输入域中更均匀地分布。仿真实验结果证明,该算法可以较好地解决边缘效应问题,相比基于距离的适应性随机测试算法与MART算法,失效发现效率更高。     

基于确定模式的伪单跳变测试矢量生成技术

提出了一种基于确定模式的伪单跳变测试矢量生成方法,它是在折叠计数器确定模式的基础上,采用LFSR编码折叠计数器种子,通过选定的存储折叠距离来控制测试模式,使得产生的测试矢量之间实现伪单跳变。由于是在确定模式基础上进行的研究,没有改变原来的测试矢量,所以故障覆盖率不会改变,却大大降低了测试功耗。这样既保证了高故障覆盖率,又解决了不同种子所生成的测试矢量之间的重叠冗余。研究结果不仅表明该方案具有很好的数据压缩率,而且证明了该方案的有效性。     

降低时延测试功耗的有效方法

研究时延测试（应用）中的功耗问题，提出一种降低时延测试功耗的测试向量排序方法，该方法利用时延测试向量对之间的海明距离为测试向量对排序，实验研究表明，在不同降低时延故障覆盖率的前提下，测试功耗平均降低90％。     

命题逻辑的随机真度理论及其应用

引入命题逻辑公式的基于随机变量序列的随机真度概念,并说明其是已有文献中各种真度概念的共同一般化,证明全体公式的随机真度之集在[0,1]中没有孤立点.利用随机真度定义公式间的随机相似度,进而导出全体公式集上的一种伪距离——随机逻辑伪距离,证明在随机逻辑伪距离空间没有孤立点.指出随机真度是已有文献中各种命题逻辑真度的共同推广.利用概率论中的积分收敛定理,证明一个关于真度的极限定理,该定理沟通了已有各种真度之间的联系.证明随机逻辑伪距离空间中逻辑运算的连续性,并将概率逻辑学基本定理推广到多值命题逻辑.在随机逻辑伪距离空间中提出两种不同类型的近似推理模式.     

低成本的两级扫描测试结构

提出了一种两级扫描测试结构：根据电路结构信息对时序单元进行分组,同组的时序单元在测试生成电路中共享同一个伪输入;将时序单元划分到不同的时钟域,在测试向量的置入过程中只有很小一部分时序单元发生逻辑值的翻转;引入新的异或网络结构,消除了故障屏蔽效应.实验结果表明,该两级测试结构与以往的方法相比,在保证故障覆盖率的同时,大大降低了测试时间、测试功耗和测试数据量.     

非相干扩频测控系统距离模拟电路设计

针对非相干体制扩频测控系统信号模拟器的要求,提出的基于现场可编程门阵列(FPGA)与DSP的信号模拟器距离模拟电路设计及实现方案.该距离模拟电路采用计数器与伪码数控振荡器(NCO)共同实现对伪码扩频信号的距离精确模拟,经过硬件电路实测结果表明,该距离模拟电路模拟精度高,满足系统的要求.     

组合电路随机测试的一种新方法

本文在随机测试的基础上提出了逆随机测试（ART）的新概念，在该测试序列的集合中各测试码之间的海明距离为尽可能的大，这样可以使不同的测试码检测到更多不同的故障，从则提高了测试效率和故障覆盖率。本文给出了构造逆随机测试序列（ARTS）的详细过程，并且严格证明了该序列的高效和正确性，同时还给出了用Benchmark和其它电路作为例子的实验结果。     

一种基于双约束传播的面向路径自动随机测试方法

随机测试是一种常用的软件测试自动化方法。该方法随机地从程序输入域中选取测试输入,其自动测试实现容易。但随机地从输入域中选取满足某种测试准则的输入数据,测试生成效率较低。为此提出了一种基于双约束传播的面向路径自动随机测试方法,通过对输入变量的取值范围进行切分,执行两次约束传播来求取指定路径的输入域,在此基础上开发了一个自动随机测试生成系统,并与PRT方法进行了实验对比分析。结果表明,该方法计算出的路径输入域更加精确,可有效地减少对无效域的测试生成,提高了随机测试的效率。     

应用代数规约和数据变异策略测试类

在应用基于代数规约测试类时,虽然可以有效解决测试数据生成和测试结果判断这两个测试难题,但是,因为该方法常常随机生成测试数据,会导致对于同一待测试类两次测试会得到不同的测试效果。为克服这个缺陷,提出应用数据变异方法,对已生成的测试用例进行变异。变异测试实验表明：该方法能够有效地改善代数测试方法的测试效果。     

一种基于轮流扫描捕获的低功耗低费用BIST方法

过高的测试功耗和过长的测试应用时间是基于伪随机内建自测试(BIST)的扫描测试所面临的两大主要问题.提出了一种基于扫描子链轮流扫描捕获的BIST方法.在提出的方法中,每条扫描链被划分成N(N>1)条子链,使用扫描链阻塞技术,同一时刻每条扫描链中只有一条扫描子链活跃,扫描子链轮流进行扫描和捕获,有效地降低了扫描移位和响应捕获期间扫描单元的翻转频率.同时,为检测抗随机故障提出了一种适用于所提出测试方法的线性反馈移位寄存器(LFSR)种子产生算法.在ISCAS89基准电路上进行的实验表明,提出的方案不但降低约(N-1)?N的平均功耗和峰值功耗,而且显著地减少随机测试的测试应用时间和LFSR重播种的种子存储量.     

Fault diagnosis of a logical circuit by use of a pseudorandom signal and a neural network

This paper describes a new method of pseudorandom testing of a digital circuit by use of a correlation method and a neural network. The authors have recently proposed a new method of fault diagnosis in a logical circuit by applying a pseudorandom M-sequence to the circuit under test, calculating the cross-correlation function between the input and the output, and comparing the cross-correlation functions with the references. This method, called the M-sequence correlation (MSEC) method, is further extended by using a neural network in order not only to detect the existence of faults, but also to find the place or location of the faults. The authors investigated the effects of using parts of the fault patterns to train the neural network to be able to detect faults. It is shown that more than 95% of faults can be detected even when only 60% of the possible training data are used.     

基于蚁群算法的测试用例优先排序

测试用例优先排序技术通过优化测试用例的执行次序来提高软件测试的效率,是增强型软件测试和回归测试的重要研究课题。针对基于需求的测试用例优先排序问题,提出了一种基于蚁群算法的求解方法,采用不同的测试用例间距离及用例序列评价策略,给出了该方法的2种不同实现方式。首先,针对黑盒测试特点,设计了基于需求的一般性测试用例序列评价指标;其次,提出测试用例吸引度概念,基于测试用例吸引度定义了测试用例间的距离;然后,给出了信息素更新策略、最优解集更新策略、局部最优解突变策略等主要设计策略,分别实现了该方法基于距离和基于指标的2种实现方式。实验结果表明,该方法具有很好的全局寻优能力,整体效果上优于粒子群算法、遗传算法和随机测试。     

Traffic-aware stress testing of distributed real-time systems based on UML models using genetic algorithms

This paper presents a model-driven, stress test methodology aimed at increasing chances of discovering faults related to network traffic in distributed real-time systems (DRTS). The technique uses the UML 2.0 model of the distributed system under test, augmented with timing information, and is based on an analysis of the control flow in sequence diagrams. It yields stress test requirements that are made of specific control flow paths along with time values indicating when to trigger them. The technique considers different types of arrival patterns (e.g., periodic) for real-time events (common to DRTSs), and generates test requirements which comply with such timing constraints. Though different variants of our stress testing technique already exist (that stress different aspects of a distributed system), they share a large amount of common concepts and we therefore focus here on one variant that is designed to stress test the system at a time instant when data traffic on a network is maximal. Our technique uses genetic algorithms to find test requirements which lead to maximum possible traffic-aware stress in a system under test. Using a real-world DRTS specification, we design and implement a prototype DRTS and describe, for that particular system, how the stress test cases are derived and executed using our methodology. The stress test results indicate that the technique is significantly more effective at detecting network traffic-related faults when compared to test cases based on an operational profile.     

Pattern‐based GUI testing: Bridging the gap between design and quality assurance

Software systems with a graphical user interface (GUI) front end are typically designed using user interface (UI) Patterns, which describe generic solutions (with multiple possible implementations) for recurrent GUI design problems. However, existing testing techniques do not take advantage of this fact to test GUIs more efficiently. In this paper, we present a new pattern‐based GUI testing (PBGT) approach that formalizes the notion of UI Test Patterns, which are generic test strategies to test UI patterns over their different implementations. The PBGT approach is evaluated via 2 case studies. The first study involves 2 fielded Web application subjects; findings show that PBGT is both practical and useful, as testing teams were able to find real bugs in a reasonable time interval. The second study allows deeper analysis by studying software subjects seeded with artificial faults; the findings show that PBGT is more effective than a manual model‐based test case generation approach.     

蜕变测试和断言检查的比较与实验研究

在软件测试中,测试预言是一种用于检查程序在测试中是否正常运行的机制.然而在某些实际情况下,还无法制定测试预言或者难以有效地应用测试预言.针对此类测试预言问题,蜕变测试于近年应运而生,但蜕变测试的效率问题还没有被充分地加以研究.作者用控制实验的方法研究了使用蜕变测试的成本及效率,进而将蜕变测试和常用的断言检查两种方法的错误检测率和时间成本进行了比较和分析.实验结果表明,相比于断言检查方法,蜕变测试具有检测到更多错误的潜力.通过分析蜕变测试的效率和性能,与断言测试相比,蜕变测试的错误检测率更高效而效率有待提高,可适用于较为粗粒度的测试需求.     

Selecting a Cost-Effective Test Case Prioritization Technique

Regression testing is an expensive testing process used to validate modified software and detect whether new faults have been introduced into previously tested code. To reduce the cost of regression testing, software testers may prioritize their test cases so that those which are more important, by some measure, are run earlier in the regression testing process. One goal of prioritization is to increase a test suite's rate of fault detection. Previous empirical studies have shown that several prioritization techniques can significantly improve rate of fault detection, but these studies have also shown that the effectiveness of these techniques varies considerably across various attributes of the program, test suites, and modifications being considered. This variation makes it difficult for a practitioner to choose an appropriate prioritization technique for a given testing scenario. To address this problem, we analyze the fault detection rates that result from applying several different prioritization techniques to several programs and modified versions. The results of our analyses provide insights into which types of prioritization techniques are and are not appropriate under specific testing scenarios, and the conditions under which they are or are not appropriate. Our analysis approach can also be used by other researchers or practitioners to determine the prioritization techniques appropriate to other workloads.