SC Harvester Papers Database Interface

MALOC: Building an adaptive scheduling and routing framework for rate-constrained TSN traffic

Nitin Desai, R. Dobrin, S. Punnekkat. In: 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA). 2022

Abstract: Time Sensitive Networking (TSN) is a set of standards aimed at providing real-time guarantees over existing Ethernet standards. Worst-case traversal time (WCTT) analyses of network traffic are traditionally used in schedulability and routing analyses to determine feasible routes for traffic streams. However, worst-case conditions happen quite rarely from a probabilistic perspective. The typical or...

Aspects of Modelling Requirements in Very-Large Agile Systems Engineering

Grischa Liebel, E. Knauss. In: J. Syst. Softw.. 2022

Abstract: Using models for requirements engineering (RE) is uncommon in systems engineering, despite the widespread use of model-based engineering in general. One reason for this lack of use is that formal models do not match well the trend to move towards agile developing methods. While there exists work that investigates challenges in the adoption of requirements modeling and agile methods in systems engi...

Model-Based System Engineering Adoption in the Vehicular Systems Domain

Henrik Gustavsson, Jan Carlson, Eduard Paul Enoiu. In: 2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS). 2022

Abstract: As systems continue to increase in complexity, some companies have turned to Model-Based Systems Engineering (MBSE) to address different challenges such as requirement complexity, consistency, traceability, and quality assurance during system development. Consequently, to foster the adoption of MBSE, practitioners need to understand what factors are impeding or promoting success in applying such a...

The broken windows theory applies to technical debt

William Lev'en, Hampus Broman, Terese Besker, R. Torkar. In: Empirical Software Engineering. 2022

Abstract: The term technical debt (TD) describes the aggregation of sub-optimal solutions that serve to impede the evolution and maintenance of a system. Some claim that the broken windows theory (BWT), a concept borrowed from criminology, also applies to software development projects. The theory states that the presence of indications of previous crime (such as a broken window) will increase the likelihood...

The Broken Windows Theory Applies to Technical Debt

William Lev'en, Hampus Broman, Terese Besker, R. Torkar. In: ArXiv. 2022

Abstract: — Context : The term technical debt (TD) describes the aggregation of sub-optimal solutions that serve to impede the evolution and maintenance of a system. Some claim that the broken windows theory (BWT), a concept borrowed from criminology, also applies to software development projects. The theory states that the presence of indications of previous crime (such as a broken window) will increase th...

Bots in Software Engineering

B. Penzenstadler, S. Abrahão, M. Staron, A. Serebrenik, Jeffrey C. Carver et al. In: IEEE Softw.. 2022

AMon: A domain-specific language and framework for adaptive monitoring of Cyber-Physical Systems

Michael Vierhauser, Rebekka Wohlrab, Marco Stadler, J. Cleland-Huang. In: J. Syst. Softw.. 2022

Abstract: Cyber–Physical Systems (CPS) are increasingly used in safety–critical scenarios where ensuring their correct behavior at runtime becomes a crucial task. Therefore, the behavior of the CPS needs to be monitored at runtime so that violations of requirements can be detected. With the inception of edge devices that facilitate runtime analysis at the edge and the increasingly diverse environments that ...

TriggerBench: A Performance Benchmark for Serverless Function Triggers

Joel Scheuner, M. Bertilsson, O. Grönqvist, He Tao, Henrik Lagergren et al. In: 2022 IEEE International Conference on Cloud Engineering (IC2E). 2022

Abstract: Serverless computing offers a scalable event-based paradigm for deploying managed cloud-native applications. Function triggers are essential building blocks in serverless, as they initiate any function execution. However, function triggering is insufficiently studied and inherently hard to measure given the distributed, ephemeral, and asynchronous nature of event-based function coordination. To ad...

Designing Self-Adaptive Software Systems with Control Theory: An Overview

A. Papadopoulos. In: 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). 2022

Abstract: The complexity of modern software systems is continuously growing, as well as the amount of data that is produced on a daily basis. This calls for sound and scalable approaches that can be used to tame such an emerging complexity. This tutorial aims at introducing the basic concepts of control theory that can be used to design self-adaptive systems. The tutorial is divided into two main parts. The...

DELFASE: A Deep Learning Method for Fault Space Exploration

Ali Sedaghatbaf, M. Moradi, J. Almasizadeh, B. Sangchoolie, Bert Van Acker et al. In: 2022 18th European Dependable Computing Conference (EDCC). 2022

Abstract: Cyber-Physical Systems (CPSs) are increasingly used in various safety-critical domains; assuring the safety of these systems is of paramount importance. Fault Injection is known as an effective testing method for analyzing the safety of CPSs. However, the total number of faults to be injected in a CPS to explore the entire fault space is normally large and the limited budget for testing forces tes...

Kubernetes Orchestration of High Availability Distributed Control Systems

Bjarne Johansson, Mats Rågberger, T. Nolte, A. Papadopoulos. In: 2022 IEEE International Conference on Industrial Technology (ICIT). 2022

Abstract: Distributed control systems transform with the Industry 4.0 paradigm shift. A mesh-like, network-centric topology replaces the traditional controller-centered architecture, enforcing the interest of cloud-, fog-, and edge-computing, where lightweight container-based virtualization is a cornerstone. Kubernetes is a well-known container management system for container orchestration in cloud computin...

Keynote - Requirements Engineering for Machine Learning: Non-functional Requirements as Core Functions

J. Horkoff. In: 2022 IEEE 30th International Requirements Engineering Conference Workshops (REW). 2022

Abstract: This extended abstract gives a short summary of one of the keynotes for the 9th International Workshop on Artificial Intelligence and Requirements Engineering (AIRE), 2022, co-located with the 30th IEEE International Requirements Engineering 2022 Conference....

Comparing Input Prioritization Techniques for Testing Deep Learning Algorithms

V. Mosin, M. Staron, Darko Durisic, F. D. O. Neto, Sushant Kumar Pandey et al. In: 2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). 2022

Abstract: Deep learning (DL) systems are becoming an essential part of software systems, so it is necessary to test them thoroughly. This is a challenging task since the test sets can grow over time as the new data is being acquired, and it becomes time-consuming. Input prioritization is necessary to reduce the testing time since prioritized test inputs are more likely to reveal the erroneous behavior of a ...

An Empirical Analysis of Microservices Systems Using Consumer-Driven Contract Testing

Hamdy Michael Ayas, Hartmut Fischer, P. Leitner, F. D. O. Neto. In: 2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). 2022

Abstract: Testing has a prominent role in revealing faults in software based on microservices. One of the most important discussion points in MSAs is the granularity of services, often in different levels of abstraction. Similarly, the granularity of tests in MSAs is reflected in different test types. However, it is challenging to conceptualize how the overall testing architecture comes together when combin...

Maintainability Challenges in ML: A Systematic Literature Review

Karthik Shivashankar, A. Martini. In: 2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). 2022

Abstract: Background: As Machine Learning (ML) advances rapidly in many fields, it is being adopted by academics and businesses alike. However, ML has a number of different challenges in terms of maintenance not found in traditional software projects. Identifying what causes these maintainability challenges can help mitigate them early and continue delivering value in the long run without degrading ML perfo...