SC Harvester Papers Database Interface

Citizens’ views on climate-change adaptation: A study of the views of participants in the 2020 Climate Change Megagame

Ola Uhrqvist, O. Leifler, Magnus C Persson. In: Skrifter från Forum för utomhuspedagogik. 2021

Abstract: This report presents and analyses the use of a megagame. Games with the primary aim to educate or enhance dialogue between different actors can be valuable for the engagement with and pedagogy of places and thus an interesting method for outdoor education and learning. The game discussed in this report has the capacity to gather between 40 and 100 participants and is thus considered to be a Megaga...

Towards Human-Like Automated Test Generation: Perspectives from Cognition and Problem Solving

Eduard Paul Enoiu, R. Feldt. In: 2021 IEEE/ACM 13th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE). 2021

Abstract: Automated testing tools typically create test cases that are different from what human testers create. This often makes the tools less effective, the created tests harder to understand, and thus results in tools providing less support to human testers. Here, we propose a framework based on cognitive science and, in particular, an analysis of approaches to problem solving, for identifying cognitive...

On the Experiences of Adopting Automated Data Validation in an Industrial Machine Learning Project

Lucy Ellen Lwakatare, Ellinor Rånge, I. Crnkovic, J. Bosch. In: 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP). 2021

Abstract: Data errors are a common challenge in machine learning (ML) projects and generally cause significant performance degradation in ML-enabled software systems. To ensure early detection of erroneous data and avoid training MLmodels using bad data, research and industrial practice suggest incorporating a data validation process and tool in the ML system development process. Aim: The study investigates...

A validated model for the scoping process of quality requirements: a multi-case study

Thomas Olsson, K. Wnuk, S. Jansen. In: Empirical Software Engineering. 2021

Abstract: Quality requirements are vital to developing successful software products. However, there exist evidence that quality requirements are managed mostly in an “ad hoc” manner and down-prioritized. This may result in insecure, unstable, slow products, and unhappy customers. We have developed a conceptual model for the scoping process of quality requirements – QREME – and an assessment model – Q-REPM –...

A validated model for the scoping process of quality requirements: a multi-case study

Thomas Olsson, K. Wnuk, S. Jansen. In: Empirical Software Engineering. 2021

7th International Workshop on Automotive System/Software Architecture (WASA 2021)

Stefan Kugele, Darko Durisic, Y. Dajsuren, M. Staron. In: 2021 IEEE 18th International Conference on Software Architecture Companion (ICSA-C). 2021

Abstract: This volume contains the papers presented at the 7th International Workshop on Automotive System/Software Architecture (WASA 2021) held on March 22, 2021, in Stuttgart, Germany. WASA was organized as part of the 18th IEEE International Conference on Software Architecture (ICSA 2021), the premier software architecture conference. Due to the worldwide SARS-CoV-2 pandemic, the main conference and the...

Nursing students’ experience of risk assessment, prevention and management: a systematic review

S. Dionisi, M. Di Muzio, N. Giannetta, Emanuele Di Simone, B. Gallina et al. In: Journal of Preventive Medicine and Hygiene. 2021

Abstract: Summary Introduction As a fundamental dimension of quality, the patient safety and healthcare workers safety in the healthcare environment depend on the ability of each healthcare workers (whether administrators or technicians) to reduce the probability of error. This review focused on nursing students. The aim was to assess level and determinants of knowledge about risk assessment, risk preventio...

What Is the Future of Modeling?

A. Bucchiarone, Federico Ciccozzi, L. Lambers, A. Pierantonio, M. Tichy et al. In: IEEE Software. 2021

Abstract: Modeling languages and frameworks have been the key technology for advancing model-driven engineering (MDE) methods and tools. Many industrial and research tools have been realized and are used across many domains. Hence, we think it is the right time to define what should be the future of modeling technologies, especially the requirements for the next generation of modeling frameworks and languag...

Aligning Architecture with Business Goals in the Automotive Domain

Alessio Bucaioni, Patrizio Pelliccione, Rebekka Wohlrab. In: 2021 IEEE 18th International Conference on Software Architecture (ICSA). 2021

Abstract: When designing complex automotive systems in practice, employed technologies and architectural decisions need to reflect business goals. While the software architecture community has acknowledged the need to align business goals with architectural decisions, there is a lack of practical approaches to achieve this alignment. In this paper, we intend to close this gap by providing a systematic appro...

Why and How Your Traceability Should Evolve: Insights from an Automotive Supplier

Rebekka Wohlrab, Patrizio Pelliccione, A. Shahrokni, E. Knauss. In: 2021 IEEE 18th International Conference on Software Architecture Companion (ICSA-C). 2021

Abstract: Traceability is a key enabler of various activities in automotive software and systems engineering and required by several standards. However, most existing traceability management approaches do not consider that traceability is situated in constantly changing development contexts involving multiple stakeholders. Together with an automotive supplier, we analyzed how technology, business, and organ...

How Explicit Feature Traces Did Not Impact Developers’ Memory

J. Krüger, G. Çalıklı, T. Berger, Thomas Leich. In: 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). 2021

Abstract: Software features are intuitive entities used to abstract and manage the functionalities of a software system, for instance, in product-line engineering and agile software development. Nonetheless, developers rarely make features explicit in code, which is why they have to perform costly program comprehension and particularly feature location to (re-)gain knowledge about the code. In a previous pa...

CEOs’ understanding of blockchain technology and its adoption in export-oriented companies in West Sweden: a survey

Viktor Elliot, Jonas Flodén, C. Overland, Zeeshan Raza, M. Staron et al. In: . 2021

Abstract: Purpose The purpose of this paper is to study current practices in adopting blockchain technology amongst export companies in West Sweden and to capture their CEOs’ knowledge of and attitudes towards blockchains. Design/methodology/approach Factors enabling or hindering the adoption of blockchains were identified from a comprehensive literature review and a survey of 72 chief executive officers...

Model-Based Testing in Practice: An Industrial Case Study using GraphWalker

M. Zafar, W. Afzal, Eduard Paul Enoiu, A. Stratis, Aitor Arrieta et al. In: Proceedings of the 14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference). 2021

Abstract: Model-based testing (MBT) is a test design technique that supports the automation of software testing processes and generates test artefacts based on a system model representing behavioural aspects of the system under test (SUT). Previous research has shown some positive aspects of MBT such as low-cost test case generation and fault detection effectiveness. However, it is still a challenge for bot...

Asking about social circles improves election predictions even with many political parties

W. B. de Bruin, M. Galesic, Rasmus Bååth, Jochem de Bresser, Lars Hall et al. In: International Journal of Public Opinion Research. 2021

Abstract: Traditionally, election polls have asked for participants’ own voting intentions. In Nature HumanBehaviour, we reported that we could improve predictions of the 2016 US and 2017 Frenchpresidential elections by asking participants how they thought their social circles would vote. Apotential concern is that the social circle question might predict less well in elections with largernumbers of politic...

Learning how to search: generating effective test cases through adaptive fitness function selection

H. Almulla, Gregory Gay. In: Empirical Software Engineering. 2021

Abstract: Search-based test generation is guided by feedback from one or more fitness functions—scoring functions that judge solution optimality. Choosing informative fitness functions is crucial to meeting the goals of a tester. Unfortunately, many goals—such as forcing the class-under-test to throw exceptions, increasing test suite diversity, and attaining Strong Mutation Coverage—do not have effective fi...