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The IEEE International Conference on Software Quality, Reliability, and Security celebrated its 20th anniversary in 2020.We received 156 submissions to the regular and short articles tracks. After the process of desk rejection, all remaining submissions were reviewed by three or more program committee members. Each submission was discussed online by the respective reviewers. Finally, the program chairs

The papers in this special section focus on software testing and program analysis. Software plays an integral part in our lives today because of its near-ubiquitous influence on our increasingly technological society. Taking appropriate steps to improve software quality is, therefore, of paramount importance. This has fueled the demand for techniques in software testing and program analysis. To meet

With the increasing number of software bugs, bug fixing plays an important role in software development and maintenance. To improve the efficiency of bug resolution, developers utilize bug reports to resolve given bugs. Especially, bug triagers usually depend on bugs’ descriptions to suggest priority levels for reported bugs. However, manual priority assignment is a time-consuming and cumbersome task

Poor data quality has a direct impact on the performance of the machine learning system that is built on the data. As a demonstrated effective approach for data quality improvement, transfer learning has been widely used to improve machine learning quality. However, the “quality improvement” brought by transfer learning was rarely rigorously validated, and some of the quality improvement results were

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In the coming 6G communications, network densification, high throughput, positioning accuracy, energy efficiency, and many other key performance indicator requirements are becoming increasingly strict. In the future, how to improve work efficiency while saving costs is one of the foremost research directions in wireless communications. Being able to learn from experience is an important way to approach

The popularity of mobile devices has led to an explosive growth in the number of mobile apps in which Android mobile apps are the mainstream. Android mobile apps usually undergo frequent update due to new requirements proposed by users. Just-in-time (JIT) defect prediction is appropriate for this scenario for quality assurance because it can provide timely feedback by determining whether a new code

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The reliability of products is a critical issue as it has high economic impacts, especially in current competitive markets. In modern applications, the complex and high-dimensional data of products are collected that can be used for reliability analysis and failure prediction. The existing reliability approaches, however, cannot efficiently model complex covariates and their effects on the time-to-failure

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The parallel constant-stress accelerated degradation test (PCSADT) is a popular method used to assess the reliability of highly reliable products in a timely manner. Although the maximum likelihood (ML) method is commonly utilized to estimate the PCSADT parameters, the explicit forms of the ML estimators, and their corresponding Fisher information matrix are usually difficult to obtain. In this article

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name

Reliability and safety have always been the main focus while developing safety critical systems (SCS). In this article, we have conducted a rigorous study and discussions with experienced practitioners worldwide the strategy for the development of SCS to investigate the several aspects related to reliability and safety analysis for SCS. We discussed with 21 practitioners from ten different organizations

Software aging refers to a problem of performance decay in the software systems, which are running for a long period. The primary cause of this phenomenon is the accumulation of run-time errors in the software, which are also known as aging-related bugs (ARBs). Many efforts have been reported earlier to predict the origin of ARBs in the software so that these bugs can be identified and fixed during

Workflow management systems (WfMS) are considered as accomplish platforms which can provide structured organization in business process and service architecture design. The systems contain workflow models in foundation, which provide flow control in one or more task sequences in parallel. Manipulation and access of artifacts that occur in or between the task sequences can generate unexpected state

Software defect prediction, aimed at assisting software practitioners in allocating test resources more efficiently, predicts the potential defective modules in software products. With the development of defect prediction technology, the inability of traditional software features to capture semantic information is exposed, hence related researchers have turned to semantic features to build defect prediction

Industry applications of formal verification to signaling control tables require formulation of a large number of mathematical conjectures expressing verification rules. It is paramount to establish the validity and completeness of these conjectures. This article discusses a mutation-based validation technique that guides domain experts in the construction of such verification rules. Furthermore, we

To optimize the process of software testing and to improve software quality and reliability, many attempts have been made to develop more effective methods for predicting software defects. Previous work on defect prediction has used machine learning and artificial software metrics. Unfortunately, artificial metrics are unable to represent the features of syntactic, semantic, and context information

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Current research on cascading failures of wireless sensor networks (WSNs) mainly focuses on single-sink networks and rarely involves multisink networks. To this end, this article proposes a realistic cascading model for multisink WSNs based on a new load metric “multioriented link betweenness.” On this basis, a memetic algorithm MA-MSP is proposed to help WSNs resist cascading failures via multisink

Evaluations of intrusion detection systems (IDS) require log datasets collected in realistic system environments. Existing testbeds therefore offer user simulations and attack scenarios that target specific use-cases. However, not only does the preparation of such testbeds require domain knowledge and time-consuming work, but also maintenance and modifications for other use-cases involve high manual

Deep learning (DL) models are vulnerable to adversarial attacks, by adding a subtle perturbation which is imperceptible to the human eye, a convolutional neural network (CNN) can lead to erroneous results, which greatly reduces the reliability and security of the DL tasks. Considering the wide application of modulation recognition in the communication field and the rapid development of DL, by adding

Although several studies have been devoted to the reliability analysis of phased-mission systems (PMSs) considering the influence of common cause failures (CCFs), statistical correlation and repairable behavior still pose challenges to the analysis. In this article, a hierarchical formal model is proposed for the reliability analysis of repairable PMSs with CCFs. The low-level model is based on continuous

Nowadays, developers are often using multiple programming languages to exploit the advantages of each language and to reuse code. However, dependency analysis across multilanguage is more challenging compared to mono-language systems. In this article, we introduce two approaches for multilanguage dependency analysis: static multilanguage dependency analyzer) and historical multilanguage dependency

At present, when the train is running between the stations, the driver cannot see the train route situation of the station ahead. Only when the train approaches the station, will the driver be able to confirm the train route information by looking at the home signal or calling the station attendant. If the train route information cannot be confirmed in time, the driver cannot control the train in accordance

Intrusion tolerance is an ability to keep the correct service by masking the intrusion based on fault-tolerant techniques. With the rapid development of virtualization, the virtual machine (VM)-based intrusion tolerance scheme has been developed according to the concept of state machine replication with Byzantine fault tolerant technique. In this article, we present the quantitative security evaluation

The abnormal nodes of the Internet of Things (IoT) are closely related to the reliability of the network, but it is always a difficulty to predict the characteristics of the induced signals that threaten reliability. In this article, a feature analysis method for the abnormal signal inducing the unreliable anomaly in IoT based on chaos attractor is proposed to make phase space reconstruction of the

In this article, we tackle the problem of using survival signatures to compare heterogeneous systems with ordered components. The scenarios where systems have the same size and those where they have different sizes are studied. Several sufficient conditions comparing two system lifetimes in the sense of the usual stochastic order are provided. Several numerical examples are presented to illustrate

Optimal reliability design (ORD) problem is challenging and fundamental to the study of system reliability. For a system with $n$ components/stages where each of them can be set in $m$ possible reliability levels, state-of-the-art linear reformulation models of ORD problem require $O(nm)$ binary variables, $O(m^n)$ continuous variables together with either $O(m^n)$ inequality constraints or $O(nm)$

Software defect prediction (SDP) is a convenient way to identify defects in the early phases of the software development life cycle. This early warning system can help in the removal of software defects and yield a cost-effective and good quality of software products. A wide range of statistical and machine learning models have been employed to predict defects in software modules. But the imbalanced

Degradation modeling is a critical and challenging problem as it serves as the basis for system prognostics and evolution mechanism analysis. In practice, multiple sensors are used to monitor the status of a system. Thus, multisensor data fusion techniques have been proposed to capture comprehensive information for prognostic modeling and analysis, which aims at developing a composite health index

The reliability evaluation of multistate networks is primarily using minimal path (cut) vectors, namely d -MPs ( d -MCs), which are the lower (upper) boundary vectors that satisfy the system demand d . The generation of all d- MPs ( d- MCs) is an NP-hard problem. Thus, it is important to develop an efficient algorithm to search for d- MPs ( d- MCs). Existing algorithms searching for d- MPs based on

Fault tree analysis (FTA) is a prominent reliability analysis method, which is widely used in safety-critical industries. Computing the minimal cut sets (MCSs) of a fault tree, i.e., finding all the smallest combinations of the basic events that cause system failures, is a fundamental step in FTA. Since coherent fault trees are the most common in industrial systems in practice, they are the focus of

Link functions of distributional and model parameters, such as linear, log-linear, or inverse linear functions, are commonly utilized in accelerated life testing to include expert knowledge and to reduce the number of unknown parameters. Although, there might be some evidence in choosing a specific link function in the analysis of an experiment, it should be verified by data. In a constant stress test

The validation of a cloud system can be complicated by the size of the system, the number of users that can concurrently request services, and the virtualization used to give the illusion of using dedicated machines. Unfortunately, it is not feasible to use conventional testing methods with cloud systems. This article proposes a framework, called TEA- Cloud , that integrates simulation with testing

In this article, we build a statistical model able to predict the reliability of the system based on a dataset. Our objective is double. On the one hand, we aim at constructing a function that classifies the system in one of the two categories (operative or failed) based on the knowledge of components states. On the other hand, we present a statistical test to decide the order of importance of components

This article presents a novel data encryption technique suitable for Internet of Things (IoT) applications. The cryptosystem is based on the application of a Catalan object (as a cryptographic key) that provides encryption based on combinatorial structures with noncrossing or nonnested matching. The experimental part of this article includes a comparative analysis of the proposed encryption method

Parallel redundancy is a common approach to increase network availability. As a consequence of providing redundancy, the loading of that component changes, affecting its reliability. In this article, a holistic approach combining two models is introduced to assess both instantaneous and future effects on general failure rates in the context of competing risks and dynamic degradation. Concretely, both

It has become commonplace to observe frequent multiple disk failures in big data centers in which thousands of drives operate simultaneously. Disks are typically protected by replication or erasure coding to guarantee a predetermined reliability. However, in order to optimize data protection, real life disk failure trends need to be modeled appropriately. The classical approach to modeling is to estimate

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

Code cloning, which reuses a fragment of source code via copy-and-paste with or without modifications, is a common way for code reuse and software prototyping. However, the duplicated code fragments often affect software quality, resulting in high maintenance cost. The existing clone detectors using shallow textual or syntactical features to identify code similarity are still ineffective in accurately

In many real-world applications, phased-mission systems (PMSs) often have time redundancy in the form of that mission task failed in one phase can be re-executed in a backup phase with change of its configurations. In this case, a new kind of dependence among phase tasks is involved: the success or failure of a phase task may result in a different configuration of its backup phases, and the original

Test-suite-based automated program repair (APR) techniques acquire information from an input test suite to guide the repair process, aiming to produce a repair that can pass all test cases of the input test suite. Obviously, the input test suite has a critical impact on the repair effectiveness of APR techniques. This article reports on a study of the APR input test suites from a new perspective. We

In this article, the coverage reliability of wireless sensor network is evaluated from a new perspective. Based on the D–S evidence theory, we define the concept of belief degree of sensing result, establish a belief-degree-coverage model considering common cause failures, and define three indexes to evaluate the reliability of the above coverage model. In order to calculate the belief degree of the

Remaining useful life (RUL) prediction under time-varying operating conditions is critical to the prognostics and health management of rotating machinery. In the literature, both the degradation rate and variation of a machinery component are often assumed to be solely dependent on operating conditions. However, this strong assumption is usually violated in many industrial applications. In this article

Existing test case prioritization (TCP) techniques have limitations when applied to real-world projects, because these techniques require certain information to be made available before they can be applied. For example, the family of input-based TCP techniques are based on test case values or test script strings; other techniques use test coverage, test history, program structure, or requirements information

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

To solve multiple response optimization problems that often involve incommensurate and conflicting responses, a robust interactive desirability function approach is proposed in this article. The proposed approach consists of a parameter initialization phase and calculation and decision-making phases. It considers a decision maker's preference information regarding tradeoffs among responses and the

As vast amounts of data are saved, hard drive failure prediction is critical to reducing the cost of data loss and backup. Most existing studies used to detect the anomalous status of a hard drive using self-monitoring, analysis, and reporting technology (SMART) attributes, and then predicted whether the drive would have an impending failure. However, as most researchers focus on a specific model of

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.

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