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The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integration of…
Software defect prediction heavily relies on the metrics collected from software projects. Earlier studies often used machine learning techniques to build, validate, and improve bug prediction models using either a set of metrics collected…
One of the prerequisites of any organization is an unvarying sustainability in the dynamic and competitive industrial environment. Development of high quality software is therefore an inevitable constraint of any software industry. Defect…
Insufficient steel quality in mass production can cause extremely costly damage to tooling, production downtimes and low quality products. Automatic, fast and cheap strategies to estimate essential material properties for quality control,…
Embedded software used in industrial systems frequently relies on data that ensures the correct and efficient operation of these systems. Thus, companies invest considerable resources in fine-tuning this data, making it their valuable…
Software reliability models are an important tool in quality management and release planning. There is a large number of different models that often exhibit strengths in different areas. This paper proposes a model that is based on a…
Finding a suited software solution for a company poses a resource-intensive task in an ever-widening market. Software should solve the technical task at hand as perfectly as possible and, at the same time, match the company strategy. Based…
Software needs to be secure, in particular, when deployed to critical infrastructures. Secure coding guidelines capture practices in industrial software engineering to ensure the security of code. This study aims to assess the level of…
Checking software application suitability using automated software tools has become a vital element for most organisations irrespective of whether they produce in-house software or simply customise off-the-shelf software applications for…
Detecting machine failures promptly is of utmost importance in industry for maintaining efficiency and minimizing downtime. This paper introduces a failure detection algorithm based on quantum computing and a statistical change-point…
Several important aspects of software product quality can be evaluated using dynamic metrics that effectively capture and reflect the software's true runtime behavior. While the extent of research in this field is still relatively limited,…
The idea of automatizing the assessment of objectoriented design is not new. Different approaches define and apply their own quality models, which are composed of single metrics or combinations thereof, to operationalize software design.…
Critical software systems face stringent requirements in safety, security, and reliability due to the circumstances surrounding their operation. Safety and security have progressively gained importance over the years due to the integration…
The continued existence of any software industry depends on its capability to develop nearly zero-defect product, which is achievable through effective defect management. Inspection has proven to be one of the promising techniques of defect…
Cyber-Physical Systems (CPSs) tightly interconnect digital and physical operations within production environments, enabling real-time monitoring, control, optimization, and autonomous decision-making that directly enhance manufacturing…
The integration of Formal Verification tools with Large Language Models (LLMs) offers a path to scale software verification beyond manual workflows. However, current methods remain unreliable: without a solid theoretical footing, the…
Software dependency network metrics extracted from the dependency graph of the software modules by the application of Social Network Analysis (SNA metrics) have been shown to improve the performance of the Software Defect prediction (SDP)…
Today's distributed systems operate in complex environments that inevitably involve faults and even adversarial behaviors. Predicting their performance under such environments directly from formal designs remains a longstanding challenge.…
Software debugging is a very time-consuming process, which is even worse for multi-threaded programs, due to the non-deterministic behavior of thread-scheduling algorithms. However, the debugging time may be greatly reduced, if automatic…
We adopted an approach based on an LSTM neural network to monitor and detect faults in industrial multivariate time series data. To validate the approach we created a Modelica model of part of a real gasoil plant. By introducing hacks into…