SC Harvester Papers Database Interface

Feature encoding with autoencoder and differential evolution for network intrusion detection using machine learning

M. Leon, Tijana Markovic, S. Punnekkat. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2022

Abstract: With the increasing use of computer networks and distributed systems, network security and data privacy are becoming major concerns for our society. In this paper, we present an approach based on an autoencoder trained with differential evolution for feature encoding of network data with the goal of improving security and reducing data transfers. One of the novel elements used in differential evol...

Feedback-based resource management for multi-threaded applications

A. Papadopoulos, Kunal Agrawal, Enrico Bini, Sanjoy Baruah. In: Real-Time Systems. 2022

Abstract: Reconciling the constraint of guaranteeing to always meet deadlines with the optimization objective of reducing waste of computing capacity lies at the heart of a large body of research on real-time systems. Most approaches to doing so require the application designer to specify a deeper characterization of the workload (and perhaps extensive profiling of its run-time behavior), which then enables...

Multiconcern, Dependability-Centered Assurance Via a Qualitative and Quantitative Coanalysis

Barbara Gallina, Leonardo Montecchi, A. Oliveira, L. Bressan. In: IEEE Software. 2022

Abstract: To contribute to multiconcern assurance, we focus on system design and present a high-level process that builds on top of the synergy between qualitative and quantitative dependability analysis techniques, which have been used for mono- as well as multiconcern analysis....

Software Design Trends Supporting Multiconcern Assurance

B. Penzenstadler, S. Abrahão, M. Staron, Jeffrey C. Carver, L. Hochstein. In: IEEE Softw.. 2022

Bayesian causal inference in automotive software engineering and online evaluation

Yuchu Liu, D. I. Mattos, Jan Bosch, H. Olsson, Jonn Lantz. In: ArXiv. 2022

Abstract: Randomised field experiments, such as A/B testing, have long been the gold standard for evaluating software changes. In the automotive domain, running randomised field experiments is not always desired, possible, or even ethical. In the face of such limitations, we develop a framework BOAT (Bayesian causal modelling for ObvservAtional Testing), utilising observational studies in combination with B...

Verifying the timing of a persistent storage for stateful fog applications

Z. Bakhshi, G. Rodríguez-Navas, Hans A. Hansson. In: 2022 6th International Conference on Computer, Software and Modeling (ICCSM). 2022

Abstract: In this paper, we analyze the failure semantics of a persistent fault-tolerant storage solution for stateful fog applications. This storage system is a container-based solution that provides data availability and consistency in a distributed container-based fog architecture. We evaluate the behavior of this storage system with a formal model that includes all the important time parameters and temp...

Corrigendum: Task Roadmaps: Speeding Up Task Replanning

A. Lager, Giacomo Spampinato, A. Papadopoulos, T. Nolte. In: Frontiers in Robotics and AI. 2022

Abstract: [This corrects the article DOI: 10.3389/frobt.2022.816355.]....

Big Tech’s power, political corporate social responsibility and regulation

Juho Lindman, J. Makinen, E. Kasanen. In: Journal of Information Technology. 2022

Abstract: The economic dominance of large Internet tech companies, specifically the ‘Big Five’ (Google, Apple, Meta née Facebook, Amazon and Microsoft), is fundamentally complicating the organisation of society. Their positions raise profound questions, old and new, at the intersection of information systems and political philosophy, where companies have traditionally appeared in liberal democracies as econ...

A retrospective clinical study of fixed tooth- and implant-supported prostheses in titanium and cobalt-chromium-ceramic: 5–9-year follow-up

S. Nilsson, V. Stenport, Marco Nilsson, Catharina Göthberg. In: Clinical Oral Investigations. 2022

Abstract: The aim of this retrospective study was to evaluate the clinical outcome of fixed tooth- and implant-supported protheses manufactured in porcelain veneered cobalt-chromium (CoCr) or titanium with a follow-up period of 5–9 years. This study included 63 patients with a total of 86 fixed dental protheses (FDPs) (53 implant-supported and 33 tooth-supported). In total, 67 were short-span FDPs (3–5 unit...

Optimization-based attack against control systems with CUSUM-based anomaly detection

Gabriele Gualandi, M. Maggio, A. Papadopoulos. In: 2022 30th Mediterranean Conference on Control and Automation (MED). 2022

Abstract: Security attacks on sensor data can deceive a control system and force the physical plant to reach an unwanted and potentially dangerous state. Therefore, attack detection mechanisms are employed in cyber-physical control systems to detect ongoing attacks, the most prominent one being a threshold-based anomaly detection method called CUSUM. Literature defines the maximum impact of stealth attacks ...

Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation

Danny Weyns, I. Gerostathopoulos, Barbora Buhnova, Nicolás Cardozo, Emilia Cioroaica et al. In: ACM SIGSOFT Software Engineering Notes. 2022

Abstract: Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introduced to support research in the field of self-adaptive systems. While these artifacts have shown their value, it is not clear to what extent these artifacts support research on problems in self-adaptation that are relevan...

The integration of machine learning into automated test generation: A systematic mapping study

Afonso Fontes, Gregory Gay. In: Software Testing. 2022

Abstract: Machine learning (ML) may enable effective automated test generation. We characterize emerging research, examining testing practices, researcher goals, ML techniques applied, evaluation, and challenges in this intersection by performing. We perform a systematic mapping study on a sample of 124 publications. ML generates input for system, GUI, unit, performance, and combinatorial testing or improve...

The integration of machine learning into automated test generation: A systematic mapping study

Afonso Fontes, Gregory Gay. In: Software Testing. 2022

Abstract: Machine learning (ML) may enable effective automated test generation. We characterize emerging research, examining testing practices, researcher goals, ML techniques applied, evaluation, and challenges in this intersection by performing. We perform a systematic mapping study on a sample of 124 publications. ML generates input for system, GUI, unit, performance, and combinatorial testing or improve...

Blended modeling in commercial and open-source model-driven software engineering tools: A systematic study

István Dávid, Malvina Latifaj, Jakob Pietron, Wei-Xing Zhang, Federico Ciccozzi et al. In: Software and Systems Modeling. 2022

Digital transformation in local government organisations: empirical evidence from blockchain initiatives

S. Mahula, Mikael Lindquist, Livia Norström, Juho Lindman. In: Proceedings of the 23rd Annual International Conference on Digital Government Research. 2022

Abstract: Local government organisations are the first contact between the citizen and state authorities. However, the rapid technological development in the private sector raises questions on how public actors can keep up. Seeking improvement, local governments undergo the process of digital transformation (DT). This encompasses a variety of processes and initiatives, including experimenting with new techn...