Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

This page or pages intentionally left blank.

This page or pages intentionally left blank.

Massive malicious jamming devices and advanced jamming techniques have been emerged along with the development of wireless communication networks. In order to effectively eliminate the harmful interference, a new scheme known as the cognitive frequency hopping (CHF) is proposed recently, which can evaluate the occupancy of frequency hopping slots and adjust the parameters dynamically according to the

The accelerated degradation testing (ADT) has been widely applied as an efficient strategy to obtain the reliability (life) information of the assets in a shorter-than-normal period of time by exposing the assets to higher-than-normal stresses. Recently, with advances in the sensor technology, it has been revealed that the degradation of some assets demonstrates a long-term memory effect, which implies

Imbalanced data is a significant issue in software fault prediction. It is very challenging for software engineers to handle imbalanced software fault data for the early prediction of software faults. In the last two decades, many researchers have used synthetic minority oversampling technique (SMOTE), SMOTE for regression and other such techniques to preprocess the imbalanced software fault data.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

This page or pages intentionally left blank.

This page or pages intentionally left blank.

Spectrum-based fault localization (SBFL) techniques can automatically localize software faults. They employ the program spectrum, such as code coverage profile with test verdicts, to rank the program entities based on their code suspiciousness. In the past decades, researchers have proposed many approaches to optimize these techniques; however, the program structure, which can influence their performance

Presents the table of contents for this issue of this publication.

Provides a listing of current staff, committee members and society officers.

Presents the introductory editorial for this issue of the publication.

Software failures caused by data race bugs have always been major concerns in parallel and distributed systems, despite significant efforts spent in software testing. Due to their nondeterministic and hard-to-reproduce features, when evaluating systems' operational reliability, a rather long period of experimental execution time is expected to be spent on observing failures caused by data race conditions

This paper analyzes security problems of modern computer systems caused by vulnerabilities in their operating systems (OSs). Our scrutiny of widely used enterprise OSs focuses on their vulnerabilities by examining the statistical data available on how vulnerabilities in these systems are disclosed and eliminated, and by assessing their criticality. This is done by using statistics from both the National

Software defect prediction (SDP) is an available way to enhance test efficiency and guarantee software reliability. However, there are more clean instances than defective instances in real software projects, and this results in severe class distribution skews and gets the poor performance of classifiers. So solving the class-imbalance problem in SDP has attracted growing attention from industry and

With the rapid development of smart devices, mobile phones have permeated many aspects of our life. Unfortunately, their widespread popularization attracted endless attacks that are serious threats for users. As the mobile system with the largest market share, Android has already become the hardest hit for years. To Detect Android Malware by ORGB Analysis, in this paper, we present DAMBA, a novel prototype

Security vulnerability prediction (SVP) can identify potential vulnerable modules in advance and then help developers to allocate most of the test resources to these modules. To evaluate the performance of different SVP methods, we should take the security audit and code inspection into account and then consider effort-aware performance measures (such as ACC and P opt ). However, to the best of our

Code commenting is a common programming practice of practical importance to help developers review and comprehend source code. In our developer survey, commenting has become an important, yet often-neglected activity when programming. Moreover, there is a lack of formal and automatic way in current practice to remind developers where to comment in the source code. To provide informative guidance on

Cyber-physical software delivers context-aware services through continually interacting with its physical environment and adapting to the changing surroundings. However, when the software's assumptions on the environment no longer hold, the interactions can introduce errors for leading to unexpected behaviors and even system failures. One promising solution to this problem is to conduct runtime monitoring

The rapid growth of Android malware results in a large body of approaches devoted to malware analysis by leveraging machine learning algorithms. However, the effectiveness of these approaches primarily depends on the manual feature engineering process, which is time-consuming and labor-intensive based on expert knowledge and intuition. In this paper, we propose an automatic approach that engineers

Context: Ranking-oriented defect prediction (RODP) ranks software modules to allocate limited testing resources to each module according to the predicted number of defects. Most RODP methods overlook that ranking a module with more defects incorrectly makes it difficult to successfully find all of the defects in the module due to fewer testing resources being allocated to the module, which results

Requirements traceability is broadly recognized as a critical element of any rigorous software development process, especially for building safety-critical software (SCS) systems. Model-driven development (MDD) is increasingly used to develop SCS in many domains, such as automotive and aerospace. MDD provides new opportunities for establishing traceability links through modeling and model transformations

Malware detection is an important and challenging issue in the Android ecosystem. Many approaches have been proposed to distinguish malicious applications from benign ones, but few of them can represent the behavior patterns of malicious applications and help understand their intention. In this paper, we propose LSCDroid, a malware detecting approach that cannot only detect malware but also help understand

SQL injection attack (SQLIA) is among the most common security threats to web-based services that are deployed on cloud. By exploiting web software vulnerabilities, SQL injection attackers can run arbitrary malicious code on target databases to acquire or compromise sensitive data. Although web application firewalls (WAFs) are offered by most cloud service providers, tenants are reluctant to pay for

Numerical computation is often involved in software of embedded control systems, cyber-physical systems, artificial neural network systems, big data processing systems, etc. Automatically discovering numerical loop invariants is fundamental for checking the safety of such software. Abstract interpretation provides a framework to automatically discover sound invariants but which may be not precise enough

Prediction of event such as failure event or critical warning event plays an important role in reliability engineering. In this paper, we present a semiparametric method to predict event occurrences for an individual unit in real time using recurrent event data. The intensity of event occurrence is modeled using the extended Cox proportional-hazard model and the distinction of units is achieved using

In this paper, the new generalized inflection S-shaped software reliability growth model is proposed. It is a very flexible finite failure Poisson process that possesses two distinguishing features: 1) includes as special cases the popular inflection S-shaped model, Goel generalized nonhomogenous Poisson process, and Goel-Okumoto model and 2) differently than these latter models, allows for modeling

This paper develops an improved dynamic reliability model for compressor rotor system, defined as a “unconventional active system” here. First, regarding to the variety of system-component connections, system specific reliability modeling technique is presented, in which the stress and strength are both nonnegative stochastic processes. The new model fully considers the load characteristics of rotor

The global reliability sensitivity index (GRSI) can measure the effect of model input variable on the failure probability of the structure and provide guidance for the reliability-based design optimization. In this paper, to efficiently estimate the GRSI, an equivalent form of the GRSI is derived by elaborative combination of Bayes' theorem and the law of total expectation in the successive intervals

The reliability assessment for a system with multiple prior information can be challenging. In this paper, we propose a novel Bayesian melding (BM) approach to combine the inconsistent prior distributions. This approach is first investigated to address a flaw in traditional BM methods and then extended to a general multilevel hierarchical system with biased priors and limited data. We realize our method

Dependability and performance analysis of modern systems is facing great challenges: their scale is growing, they are becoming massively distributed, interconnected, and evolving. Such complexity makes model-based assessment a difficult and time-consuming task. For the evaluation of large systems, reusable submodels are typically adopted as an effective way to address the complexity and to improve

With the rapid development of technology scaling and cell density improvement for capacity increase and cost reduction, nand flash memory is confronted with degraded reliability. On one hand, while low-density parity-check (LDPC) codes have been deployed in today's nand flash memories to enhance reliability, flash read latency has still been a performance bottleneck with the increased raw bit error

To cope with the control problem of industrial processes with partial actuator failure and disturbance, an improved synthetic minmax optimization design-based H ∞ linear quadratic (LQ) tracking control strategy is presented in this paper. A new state space model that integrates the dynamics of the process states and the tracking error is first formulated as the basic dynamic process representation

Mutation testing is a fault-oriented software testing technique, and a test suite generated based on the criterion of mutation testing generally has a high capability in detecting faults. A mutant that is hard killed is called a stubborn one. The traditional methods of test data generation often fail to generate test data that kill stubborn mutants. To improve the efficiency of killing stubborn mutants

Abstract test cases (ATCs) have been widely used in practice, including in combinatorial testing and in software product line testing. When constructing a set of ATCs, due to limited testing resources in practice (e.g., in regression testing), test case prioritization (TCP) has been proposed to improve the testing quality, aiming at ordering test cases to increase the speed with which faults are detected

For a long time, the machinery's reliability allocation methods have followed the electronics', and thus all of the interactions among moving components and parts in machines are neglected. In fact, the allocated results are not reasonable for mechanical products; even the allocation granularity is not appropriate to guide the reliability design. To overcome these problems, this paper proposes an allocation

Wireless sensor networks (WSNs) find application in various fields like environmental monitoring, health-care, land security, and many more. To ease our day-to-day activity, WSNs have become an integral tool for complex data gathering tasks. Monitoring a phenomenon by a WSN depends on the collective data provided by the sensor nodes. To ensure reliable operation of WSNs, it is important to quantify

Remaining useful life (RUL) prediction of rolling element bearings plays a pivotal role in reducing costly unplanned maintenance and increasing the reliability, availability, and safety of machines. This paper proposes a hybrid prognostics approach for RUL prediction of rolling element bearings. First, degradation data of bearings are sparsely represented using relevance vector machine regressions

This page or pages intentionally left blank.

This page or pages intentionally left blank.

The fifth version of the Hypertext Markup Language (HTML) standard is widely adopted in the diverse landscape of browser vendors and their continuously upgrading releases. One primary feature of HTML5 is native multimedia playback. The browsers’ native implementations of multimedia support bring lots of benefits such as improved security but require thorough testing, especially on the web page of complex

Traditional maintenance planning problems usually presume that preventive maintenance (PM) policies will be executed exactly as planned. In reality, however, maintainers often deviate from the intended PM policy, resulting in unpunctual PM executions that may reduce maintenance effectiveness. This article studies two imperfect PM policies with unpunctual executions for infinite and finite planning

The synthesis problem is to construct a system fulfilling some specific requirements when interacting with the environment, which is one of the most crucial and challenging tasks in robotics. In comparison to the case of dealing with a single robot, synthesizing of a system constituted with multiple robots is, in general, much more involved. Actually, information is shared among robots in the latter

In this article, vertical interconnection implemented as capacitive-based chip-to-chip differential signaling offers crosstalk noise reduction in three-dimensional (3-D) die stacking. To investigate the effects of signal transmission reliability on the 3-D stacked die structure, this article aims at providing the parametric models. The signal and noise properties of capacitively coupled channels are

Motivated by an accelerated degradation test (ADT) on the power gain of microwave power amplifiers, in this article we propose a model-ranking approach for the estimation of some important reliability characteristics. Different degradation models and statistical lifetime distributions are applied to model the data obtained from the ADT. We study the effect of model misspecification in estimating the

Unsupervised machine learning is the training of an artificial intelligence system using information that is neither classified nor labeled, with a view to modeling the underlying structure or distribution in a dataset. Since unsupervised machine learning systems are widely used in many real-world applications, assessing the appropriateness of these systems and validating their implementations with

Recently, the advancements in the field of wireless technologies and micro-electro-mechanical systems lead to the development of potential applications in wireless sensor networks (WSNs). The visual sensors in WSN create a significant impact on computer vision based applications such as pattern recognition and image restoration. generate a massive quantity of multimedia data. Since transmission of

In this article, test diversity has been suggested to be a valid way to improve test suite effectiveness. Extended finite state machine (EFSM) is a widely used formal model, but little attention is paid on the test suite generation with more diversity. EFSM test suite generation involves test paths generation and test data generation. Considering the discrepancy between test paths has a more crucial

This article proposes a system design optimization for a circular k -out-of- n : G balanced system with equal load-sharing units. The system consists of n identical units whose failure times are assumed to follow an exponential distribution, and it is subject to an equally shared load among the working units. The load-sharing relationship between the amount of load and the failure rates of the working

Obtaining lower confidence bounds on the reliability of a series system remains a problem of interest. Engineers and practitioners desire methods with good properties to obtain lower confidence bounds when only component-level binomial test data are available. With numerous methods proposed in the literature–none of which are uniformly superior–it can be an overwhelming task to select the method which

Software systems often receive a large number of bug reports. Triagers read through such reports and assign different priorities to different reports so that important and urgent bugs could be fixed on time. However, manual prioritization is tedious and time-consuming. To this end, in this article, we propose a convolutional neural network (CNN) based automatic approach to predict the multiclass priority

In this article, we present a model for delayed reporting of faults: multiple nonfatal faults are accumulated and then simultaneously reported and repaired. The reporting process is modeled as a stochastic process dependent on the underlying stochastic process generating the faults. We derive the joint distribution of the reporting times and numbers of reported faults, giving general results and results

Due to the advancements in sensing technologies and computational capabilities, system health assessment and prognostics have been extensively investigated in the literature. Industry has adopted and implemented many advanced system prognostic applications. This article reviews recent research advances and applications in prognostics modeling methods for engineering systems. The reviewed papers are

Due to the artificial division of a machine performance state and unpredictable external working conditions, the performance and state transition strength of multistate machines (that is, their fuzzy multistate characteristic) cannot be accurately identified. Moreover, existing research on the reliability evaluation of multistate systems does not consider the operating mechanism of a manufacturing

Test oracles differentiate between the correct and incorrect system behavior. Automation of test oracles for visual output systems mainly involves image comparison, where a snapshot of the output is compared with respect to a reference image. Hereby, the captured snapshot can be subject to variations such as scaling and shifting. These variations lead to incorrect evaluations. Existing approaches employ

In indoor localization, reliability and optimization analysis are the most vital factors to be considered. Numerous modern-day services require precise location information for their application. Location fingerprinting using WLAN is the most acknowledged technique for indoor localization purposes. Both accuracy and coverage can be enhanced by deploying the WLAN access points (APs) appropriately. In

In this article, we propose a hierarchical fault localization technique using a deep neural network (DNN). First, we prioritize the functions of a program based on their suspiciousness score. Subsequently, the fault is localized to specific statements within the top k suspected functions, where the value of k is determined heuristically. We use two function-level features to train a DNN for fault localization