Context : Multiple fault localization (MFL) is the act of identifying the locations of multiple faults (more than one fault) in a faulty software program. This is known to be more complicated, tedious, and costly in comparison to the traditional practice of presuming that a software contains a single fault. Due to the increasing interest in MFL by the research community, a broad spectrum of MFL debugging

Context Internet of Things (IoT) is a promising paradigm due to the growing number of devices that may be connected, defined as “things”. Managing these “things” is still considered a challenge. One way to overcome this challenge may be by adopting the software product line (SPL) paradigm and the variability management (VM) activity. SPL engineering consists of mechanisms that provide identification

Context: Neural Network (NN) algorithms have been successfully adopted in a number of Safety-Critical Cyber-Physical Systems (SCCPSs). Testing and Verification (T&V) of NN-based control software in safety-critical domains are gaining interest and attention from both software engineering and safety engineering researchers and practitioners. Objective: With the increase in studies on the T&V of NN-based

Context:Behavior-Driven Development (BDD) features the capability, through appropriate domain-specific languages, of specifying acceptance test cases and making them executable. The availability of frameworks such as Cucumber or RSpec makes the application of BDD possible in practice. However, it is unclear to what extent developers use such frameworks, and whether they use them for actually performing

Context : Software testing is a complex area since it has a large number of specific methods, processes and strategies, involving a lot of domain concepts. Therefore, it would be valuable to have a conceptualized software testing ontology that explicitly and unambiguously defines the concepts. Consequently, it is important to find out the available evidence in the literature on primary studies for

Context : Nowadays, the use of GPU to improve performance of computationally expensive systems are widely explored. On GPU-accelerated programs, performance is related to the partition of the problem into blocks of threads in such a way that the parallel tasks to be executed better fit the GPU architecture. Although there exists some general guidelines to help defining block dimensions, finding the

Context:Software testing based on finite-state machines. Objective:Improving the performance of existing testing methods by construction of more efficient separating sequences, so that states entered by a system under test can be identified in a much shorter span of time. Method: This paper proposes an efficient way to construct separating sequences for subsets of states for any deterministic finite-state

Context: Functional Size Measurement (FSM) methods, like Function Points Analysis (FPA) or COSMIC, are well-established approaches to estimate software size. Several approximations of these methods have been recently proposed as they require less time/information to be applied, however their effectiveness for effort prediction is not known. Objective: The effectiveness of approximated functional size

Context: The quality of user experience is the cornerstone of any organization’s successful digital transformation journey. Web pages are the main touchpoint for users to access services in a digital mode. Web page performance is a key determinant of the quality of user experience. The negative impact of poor web page performance on the productivity, profits, and brand value of an organization is well-recognized

Context When conducting a Systematic Literature Review (SLR), researchers usually face the challenge of designing a search strategy that appropriately balances result quality and review effort. Using digital library (or database) searches or snowballing alone may not be enough to achieve high-quality results. On the other hand, using both digital library searches and snowballing together may increase

Context The model-based analysis is preferred over the code-based analysis as it speeds up the development process and directs the guiding effort. In the software industry, the Unified Modeling Language (UML) is a set standard followed by the developers as well as system analysts to extract all attainable paths of controls, usually known as scenarios under an activity diagram. Objective In this manuscript

Context: Software Fault Localisation (FL) refers to finding faulty software elements related to failures produced as a result of test case execution. This is a laborious and time consuming task. To allow FL automation search-based algorithms have been successfully applied in the field of Search-Based Fault Localisation (SBFL). However, there is no study mapping the SBFL field to the best of our knowledge

Context : Software vulnerability detection is essential to ensure cybersecurity. Currently, most software is published in binary form, thus researchers can only detect vulnerabilities in these software by analysing binary programs. Although existing research approaches have made a substantial contribution to binary vulnerability detection, there are still many deficiencies, such as high false positive

Context Quality requirements (QRs) describe the desired quality of software, and they play an important role in the success of software projects. In agile software development (ASD), QRs are often ill-defined and not well addressed due to the focus on quickly delivering functionality. Rapid software development (RSD) approaches (e.g., continuous delivery and continuous deployment), which shorten delivery

Context The importance of automotive software has been rapidly increasing because software controls many components of motor vehicles such as smart-key system, tire pressure monitoring system, and advanced driver assistance system. Consequently, the automotive industry spends a large amount of human effort to test automotive software and is interested in automated testing techniques to ensure high-quality

Context The severity of a bug is often used as an indicator of how a bug negatively affects system functionality. It is used by developers to prioritize bugs which need to be fixed. The problem is that, for various reasons, bug submitters often enter the incorrect severity level, delaying the bug resolution process. Techniques that can automatically predict the severity of a bug can significantly reduce

CONTEXT Scientific software plays an important role in critical decision making, for example making weather predictions based on climate models, and computation of evidence for research publications. Recently, scientists have had to retract publications due to errors caused by software faults. Systematic testing can identify such faults in code. OBJECTIVE This study aims to identify specific challenges

CONTEXT A distributed business process is executed in a distributed computing environment. The service-oriented architecture (SOA) paradigm is a popular option for the integration of software services and execution of distributed business processes. Entailment constraints, such as mutual exclusion and binding constraints, are important means to control process execution. Mutually exclusive tasks result