A dynamic code coverage approach to maximize fault localization efficiency

Spectrum-based fault localization is amongst the most effective techniques for automatic fault localization. However, abstractions of program execution traces, one of the required inputs for this technique, require instrumentation of the software under test at a statement level of granularity in order to compute a list of potential faulty statements. This introduces a considerable overhead in the fault localization process, which can even become prohibitive in, e.g., resource constrained environments. To counter this problem, we propose a new approach, coined dynamic code coverage (DCC), aimed at reducing this instrumentation overhead. This technique, by means of using coarser instrumentation, starts by analyzing coverage traces for large components of the system under test. It then progressively increases the instrumentation detail for faulty components, until the statement level of detail is reached. To assess the validity of our proposed approach, an empirical evaluation was performed, injecting faults in six real-world software projects. The empirical evaluation demonstrates that the dynamic code coverage approach reduces the execution overhead that exists in spectrum-based fault localization, and even presents a more concise potential fault ranking to the user. We have observed execution time reductions of 27% on average and diagnostic report size reductions of 77% on average.     

一种可用于编译器调试的目标代码验证方法

传统编译器测试方法是通过比较预期的结果和待测的结果是否一致,以确定编译器是否存在错误。在此基础上,提出了引入参考编译器和参考仿真器的测试方法,在指令集软件仿真过程中生成可用于编译器调试的动态数据信息文件,对参考动态数据信息文件和待测动态数据信息文件进行比较,编译器测试工具可根据比较的结果来确定待测编译器存在错误的位置,这对编译器的调试是非常有用的。     

一种基于APIT的无线传感器网络混合型定位算法

针对现有近似三角形内点测试（ APIT）算法在信标节点密集环境下定位精度不高、稀疏环境下覆盖率较低的问题,提出了一种混合型定位算法。该算法通过减小三角形内点测试（ PIT）时的三角形误判、选择优良的三角形,提高了信标节点密集环境下的定位精度。同时,该算法结合DV-Hop算法与两点定位法在稀疏环境下能计算出未知节点坐标的优点,提高了信标节点稀疏环境下的定位覆盖率。仿真分析表明：混合型算法有效地提高了信标节点密集环境下的定位精度和信标节点稀疏环境下的定位覆盖率。     

Reliability of wireless sensors with code attestation for intrusion detection

Wireless sensor nodes are widely used in many areas, including military operation surveillance, natural phenomenon monitoring, and medical diagnosis data collection. These applications need to store and transmit sensitive or secret data, which requires intrusion detection mechanisms be deployed to ensure sensor node health, as well as to maintain sensor quality of service and survivability. Because wireless sensors have inherent resource constraints, it is crucial to reduce energy consumption due to intrusion detection activities. In this paper by means of a probability model, we analyze the best frequency at which intrusion detection based on code attestation on the sensor node should be performed so that the sensor reliability is maximized by exploiting the trade-off between the energy consumption and intrusion detection effectiveness. When given a set of parameter values characterizing the operational and networking conditions, the system verifier can dynamically set the intrusion detection rate identified by the mathematical model to maximize the sensor reliability and the expected sensor lifetime.     

Identification of shaft orbit for hydraulic generator unit using chain code and probability neural network

Shaft orbit identification plays an important role in the hydraulic generator unit fault diagnosis. In this paper, a novel shaft orbit identification method based on chain code and probability neural network (PNN) is proposed. For this approach, firstly, a modified chain code histogram and shape numbers are used to represent the feature of the shaft orbit contour. It has properties of less data, easy to calculate, and invariance to rotation, scaling and translation. Then, the feature vectors are input to PNN to identify various kinds of shaft orbit for hydraulic generator unit. In comparison with previous methods, the experimental results show the proposed method is effective and training the network is faster, and identifying the shaft orbit achieves satisfactory accuracy.     

SPOON: A library for implementing analyses and transformations of Java source code

This paper presents SPOON , a library for the analysis and transformation of Java source code. SPOON enables Java developers to write a large range of domain‐specific analyses and transformations in an easy and concise manner. SPOON analyses and transformations are written in plain Java. With SPOON , developers do not need to dive into parsing, to hack a compiler infrastructure, or to master a new formalism. Copyright © 2015 John Wiley & Sons, Ltd.     

FAULT: A FORTRAN program for modeling the degradation of active normal fault scarps

FAULT, a FORTRAN program for modeling degradation of normal fault scarps, provides a means for estimating time(s) and amount(s) of vertical displacement along such faults. The program is based on observations of degraded fault scarps in the Basin and Range province of the western United States and of wave-cut bluffs along the shores of Lake Michigan. Scarps on which debris is loosened from the scarp face more rapidly then the debris transporting processes can remove it, degrade by reduction of curvature (rounding) of the basal concavity and crestal convexity and by decrease in gradient of the scarp face. Scarps on which debris is removed as rapidly as it is loosened from the scarp face, degrade by parallel retreat of the scarp face with the build-up of a debris apron at the scarp base.     

A sliding mode observer-based strategy for fault detection,isolation, and estimation in a class of Lipschitz nonlinear systems

This article investigates the design and application of a sliding mode observer (SMO) strategy for actuator as well as sensor fault detection, isolation, and estimation (FDIE) problem for a class of uncertain Lipschitz nonlinear systems. Actuator FDIE is addressed by regrouping the system's inputs into a structure suitable for SMO design. Similarly, by filtering the regrouped outputs, a similar system structure can be developed for sensor FDIE problem. Once in the suitable form and under certain assumptions, nonlinear SMOs are proposed for actuator and sensor FDIE. A systematic LMI-based design approach for the proposed SMO is presented. Additionally, the article addresses four problems, namely: (P1) What are the conditions for isolating single and/or multiple faults? (P2) What is the maximum number of faults that can be isolated simultaneously? (P3) How should one design SMO-based FDI approach in order to achieve multiple fault isolation using as few observers as possible? (P4) How can one estimate the shape of the faults? To solve the above problems, a new concept called fault isolation index (FIX) is proposed for actuator and sensor FDIE. It is proved that fault isolation can only be achieved if FIX?≠?0, and also that the maximum number of faults that can be isolated is equal to FIX. Using the proposed fault isolation strategy and by treating some healthy inputs or outputs as unknown inputs, a systematic FDIE design scheme using a bank of nonlinear SMOs, which provides a solution for the four problems is provided. An example is used to illustrate the proposed ideas. The simulation results show that the proposed FDIE scheme can successfully detect and isolate both slowly and fast-changing actuator faults. It is also shown that accurate estimation of actuator faults can be achieved.     

Ann: A domain-specific language for the effective design and validation of Java annotations

This paper describes a new modelling language for the effective design and validation of Java annotations. Since their inclusion in the 5th edition of Java, annotations have grown from a useful tool for the addition of meta-data to play a central role in many popular software projects. Usually they are not conceived in isolation, but in groups, with dependency and integrity constraints between them. However, the native support provided by Java for expressing this design is very limited.To overcome its deficiencies and make explicit the rich conceptual model which lies behind a set of annotations, we propose a domain-specific modelling language. The proposal has been implemented as an Eclipse plug-in, including an editor and an integrated code generator that synthesises annotation processors. The environment also integrates a model finder, able to detect unsatisfiable constraints between different annotations, and to provide examples of correct annotation usages for validation. The language has been tested using a real set of annotations from the Java Persistence API (JPA). Within this subset we have found enough rich semantics expressible with Ann and omitted nowadays by the Java language, which shows the benefits of Ann in a relevant field of application.     

Fault coverage of Constrained Random Test Selection for access control: A formal analysis

A probabilistic model of fault coverage is presented. This model is used to analyze the variation in the fault detection effectiveness associated with the use of two test selection strategies: heuristics-based and Constrained Random Test Selection (CRTS). These strategies arise in the context of conformance test suite generation for Role Based Access Control (RBAC) systems. The proposed model utilizes coverage matrix based approach for fault coverage analysis. First, two boundary instances of fault distribution are considered and then generalized. The fault coverages of the test suites generated using the heuristics-based and the CRTS strategies, applied to a sample RBAC policy, are then compared through simulation. Finally the simulation results are correlated with a case study.