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Software vulnerabilities represent one of the most pressing threats to computing systems. Identifying vulnerabilities in source code is crucial for protecting user privacy and reducing economic losses. Traditional static analysis tools rely…
Smart Manufacturing refers to optimization techniques that are implemented in production operations by utilizing advanced analytics approaches. With the widespread increase in deploying Industrial Internet of Things (IIoT) sensors in…
Advancements in data-driven machine learning have emerged as a pivotal element in supporting automotive software systems (ASSs) engineering across various levels of the V-development process.…
In hardware accelerators used in data centers and safety-critical applications, soft errors and resultant silent data corruption significantly compromise reliability, particularly when upsets occur in control-flow operations, leading to…
Large Language Models (LLMs) show promise in generating firmware for embedded systems, but often introduce security flaws and fail to meet real-time performance constraints. This paper proposes a three-phase methodology that combines…
Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for process and product improvement continue to grow, the quality of…
Debugging is considered as a rigorous but important feature of software engineering process. Since more than a decade, the software engineering research community is exploring different techniques for removal of faults from programs but it…
This paper presents a novel mutual information (MI) matrix based method for fault detection. Given a $m$-dimensional fault process, the MI matrix is a $m \times m$ matrix in which the $(i,j)$-th entry measures the MI values between the…
PerfDetectiveAI, a conceptual framework for performance gap analysis and suggestion in software applications is introduced in this research. For software developers, retaining a competitive edge and providing exceptional user experiences…
In the context of Industry 4.0, effective monitoring of multiple targets and states during assembly processes is crucial, particularly when constrained to using only visual sensors. Traditional methods often rely on either multiple sensor…
We propose a systematic method to directly identify a sensor fault estimation filter from plant input/output data collected under fault-free condition. This problem is challenging, especially when omitting the step of building an explicit…
Software defects rediscovered by a large number of customers affect various stakeholders and may: 1) hint at gaps in a software manufacturer's Quality Assurance (QA) processes, 2) lead to an over-load of a software manufacturer's support…
Effort estimation is a key factor for software project success, defined as delivering software of agreed quality and functionality within schedule and budget. Traditionally, effort estimation has been used for planning and tracking project…
Ensuring the reliability of autonomous driving perception systems requires extensive environment-based testing, yet real-world execution is often impractical. Synthetic datasets have therefore emerged as a promising alternative, offering…
Vulnerability discovery and exploits detection are two wide areas of study in software engineering. This preliminary work tries to combine existing methods with machine learning techniques to define a metric classification of vulnerable…
Context: Technical Debt requirements are related to the distance between the ideal value of the specification and the system's actual implementation, which are consequences of strategic decisions for immediate gains, or unintended changes…
Defect estimation and prediction are some of the main modulating factors for the success of software projects in any software industry. Maturity and competency of a project manager in efficient prediction and estimation of resource…
Testing plays an important role in securing the success of a software development project. Prior studies have demonstrated beneficial effects of applying acceptance testing within a Behavioural-Driven Development method. In this research,…
Reliability and availability analysis are essential in dependable critical embedded systems. The classical implementation of dependability for an embedded system relies on merging both fundamental structures with the required dependability…
Estimating software testability can crucially assist software managers to optimize test budgets and software quality. In this paper, we propose a new approach that radically differs from the traditional approach of pursuing testability…