Related papers: Risk Assessment, Threat Modeling and Security Test…
In software testing, a set of test cases is constructed according to some predefined selection criteria. The software is then examined against these test cases. Three interesting observations have been made on the current artifacts of…
Over the last years, machine learning techniques have been applied to more and more application domains, including software engineering and, especially, software quality assurance. Important application domains have been, e.g., software…
Microsoft's STRIDE methodology is at the forefront of threat modeling, supporting the increasingly critical quality attribute of security in software-intensive systems. However, in a comprehensive security evaluation process, the general…
This paper presents the core principles of reliability in software engineering - outlining why reliability testing is critical and specifying the process of measuring reliability. The paper provides insight for both novice and experts in…
Business process management (BPM) and accompanying systems aim at enabling enterprises to become adaptive. In spite of the dependency of enterprises on secure business processes, BPM languages and techniques provide only little support for…
With the increase in the number of privacy regulations, small development teams are forced to make privacy decisions on their own. In this paper, we conduct a mixed-method survey study, including statistical and qualitative analysis, to…
Computer-based systems have solved several domain problems, including industrial, military, education, and wearable. Nevertheless, such arrangements need high-quality software to guarantee security and safety as both are mandatory for…
In order to optimize the usage of testing efforts and to assess risks of software-based systems, risk-based testing uses risk (re-)assessments to steer all phases in a test process. Several risk-based testing approaches have been proposed…
The use of free and open source software (FOSS) components in all software systems is estimated to be above 90%. With such high usage and because of the heterogeneity of FOSS tools, repositories, developers and ecosystem, the level of…
Although an ever-growing number of applications employ deep learning based systems for prediction, decision-making, or state estimation, almost no certification processes have been established that would allow such systems to be deployed in…
The majority of software developers use or are planning to use Artificial Intelligence (AI) tools in their development processes. Their top reasons include improving productivity and faster learning. In fact, Large Language Model…
Machine learning (ML) components are increasingly integrated into software products, yet their complexity and inherent uncertainty often lead to unintended and hazardous consequences, both for individuals and society at large. Despite these…
Although general-purpose AI systems offer transformational opportunities in science and industry, they simultaneously raise critical concerns about safety, misuse, and potential loss of control. Despite these risks, methods for assessing…
Accurate software cost and schedule estimation are essential for software project success. Often it referred to as the "black art" because of its complexity and uncertainty, software estimation is not as difficult or puzzling as people…
In the era of revolution, the development of softwares are increasing daily. The quality of software impacts the most in software development. To ensure the quality of the software it needs to be reviewed and updated. The effectiveness of…
Industrial Internet of Things (IIoT) application provide a whole new set of possibilities to drive efficiency of industrial production forward. However, with the higher degree of integration among systems, comes a plethora of newthreats to…
Software has the potential to be a key driver in fostering sustainability. Despite this potential, it is not clear if and how the software industry integrates consideration of sustainability into its common software development processes.…
Software estimation is one of the most important activities in the software project. The software effort estimation is required in the early stages of software life cycle. Project Failure is the major problem undergoing nowadays as seen by…
Data scientists often develop machine learning models to solve a variety of problems in the industry and academy but not without facing several challenges in terms of Model Development. The problems regarding Machine Learning Development…
The mass production of complex software has made it impossible to manually test it for security vulnerabilities. Automated security testing tools come in a variety of flavors, function at various stages of software development, and target…