SC Harvester Papers Database Interface

Combining Model-Based Testing and Automated Analysis of Behavioural Models using GraphWalker and UPPAAL

Saurabh Tiwari, K. Iyer, Eduard Paul Enoiu. In: 2022 29th Asia-Pacific Software Engineering Conference (APSEC). 2022

Abstract: Model-based Testing (MBT) has been proposed to create test cases more efficiently and effectively. In contrast, analysis techniques (e.g., model checking) have been used separately from testing and have shown great potential when applied early in the development process. Still, these are confronted by applicability and scalability issues and work on specific modeling languages. The combined use of...

Metal- and antibiotic-resistant heterotrophic plate count bacteria from a gold mine impacted river: the Mooi River system, South Africa

J. Bosch, Carlos C. Bezuidenhout, R. Coertze, L. Molale-Tom. In: Environmental Science and Pollution Research International. 2022

Abstract: The Wonderfonteinspruit, South Africa, is highly impacted by a century of gold mining activities. The aim of this study was to investigate the physico-chemical properties of the Wonderfonteinspruit and the receiving Mooi River system, the levels of antimicrobial (metals and antibiotics) resistance characteristics and heterotrophic bacteria levels in these water systems. Various physico-chemical pa...

Ethics of Autonomous Collective Decision-Making: The Caesar Framework

Mirgita Frasheri, Václav Struhár, A. Papadopoulos, Aida Čaušević. In: Science and Engineering Ethics. 2022

Abstract: In recent years, autonomous systems have become an important research area and application domain, with a significant impact on modern society. Such systems are characterized by different levels of autonomy and complex communication infrastructures that allow for collective decision-making strategies. There exist several publications that tackle ethical aspects in such systems, but mostly from the...

Concepts and Relationships in Safety and Security Ontologies: A Comparative Study

Malina Adach, Kaj Hänninen, K. Lundqvist. In: 2022 6th International Conference on System Reliability and Safety (ICSRS). 2022

Abstract: Safety and security ontologies quickly become essential support for integrating heterogeneous knowledge from various sources. Today, there is little standardization of ontologies and almost no discussion of how to compare concepts and their relationships, establish a general approach to create relationships or model them in general. However, concepts with similar names are not semantically similar...

CASCADE: An Asset-driven Approach to Build Security Assurance Cases for Automotive Systems

Mazen Mohamad, Rodi Jolak, Örjan Askerdal, J. Steghöfer, R. Scandariato. In: ACM Transactions on Cyber-Physical Systems. 2022

Abstract: Security Assurance Cases (SAC) are structured arguments and evidence bodies used to reason about the security of a certain system. SACs are gaining focus in the automotive industry, as the needs for security assurance are growing in this domain. However, the state-of-the-arts lack a mature approach able to suit the needs of the automotive industry. In this article, we present CASCADE, an asset-dri...

Identifying security-related requirements in regulatory documents based on cross-project classification

Mazen Mohamad, J. Steghöfer, Alexander Åström, R. Scandariato. In: Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering. 2022

Automation of the creation and execution of system level hardware-in-loop tests through model-based testing

V. Karlsson, Ahmed Almasri, Eduard Paul Enoiu, W. Afzal, P. Charbachi. In: Proceedings of the 13th International Workshop on Automating Test Case Design, Selection and Evaluation. 2022

Predicting build outcomes in continuous integration using textual analysis of source code commits

K. Al-Sabbagh, M. Staron, R. Hebig. In: Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering. 2022

Automating Safety Argument Change Impact Analysis for Machine Learning Components

Carmen Cârlan, Lydia Gauerhof, B. Gallina, S. Burton. In: 2022 IEEE 27th Pacific Rim International Symposium on Dependable Computing (PRDC). 2022

Abstract: The need to make sense of complex input data within a vast variety of unpredictable scenarios has been a key driver for the use of machine learning (ML), for example in Automated Driving Systems (ADS). Such systems are usually safety-critical, and therefore they need to be safety assured. In order to consider the results of the safety assurance activities (scoping uncovering previously unknown haz...

RBDMS: Rate-Adaptation and Buffer-Awareness Data Gathering for Mobile Sink Scheduling in WSNs

Morteza Biabani, N. Yazdani, H. Fotouhi. In: IEEE Sensors Journal. 2022

Abstract: Employing a mobile sink (MS) to act as a relay node in wireless sensor network (WSN) applications is a promising solution for efficient power saving and data collection. However, establishing long-distance traveling leads to larger latency or inefficient buffer management at rendezvous points (RPs), e.g., flying UAVs in disaster management. Moreover, there is no efficient solution to guarantee the...

An Eco-System Approach to Project-Based Learning in Software Engineering Education

Daniel Ståhl, K. Sandahl, L. Buffoni. In: IEEE Transactions on Education. 2022

Abstract: Contribution: This article identifies the participation of external stakeholders as a key contributing factor for positive outcomes in project-based software engineering courses. A model for overlapping virtuous circles of lasting positive impact on both stakeholders and students from such courses is proposed. Background: Project-based courses are widespread in software engineering education, and ...

Can RE Help Better Prepare Industrial AI for Commercial Scale?

Boris Scharinger, Markus Borg, Andreas Vogelsang, Thomas Olsson, Markus Borg. In: IEEE Software. 2022

Abstract: “Hey AI, show me the money!” Sure, the impact of AI on industries and society is huge. However, we are still waiting for that steady stream of lucrative success stories in industrial artificial intelligence (AI)....

AI Engineering Research in Software Engineering Venues

A. Serebrenik, M. Staron, Jordi Cabot, B. Penzenstadler, L. Hochstein et al. In: IEEE Softw.. 2022

AI Engineering: Realizing the Potential of AI

Jan Bosch, H. Olsson, B. Brinne, I. Crnkovic. In: IEEE Softw.. 2022

DeepFlexiHLS: Deep Neural Network Flexible High-Level Synthesis Directive Generator

M. Riazati, M. Daneshtalab, Mikael Sjödin, B. Lisper. In: 2022 IEEE Nordic Circuits and Systems Conference (NorCAS). 2022

Abstract: Deep Neural Networks (DNNs) are now widely adopted to solve various problems ranging from speech recognition to image classification. Since DNNs demand a large amount of processing power, their implementation on hardware, i.e., FPGA or ASIC, has received much attention. High-level synthesis is widely used since it significantly boosts productivity and flexibility and requires minimal hardware know...