SC Harvester Papers Database Interface

Verifiable strategy synthesis for multiple autonomous agents: a scalable approach

Rong Gu, P. G. Jensen, D. B. Poulsen, C. Seceleanu, Eduard Paul Enoiu et al. In: International Journal on Software Tools for Technology Transfer. 2022

Abstract: Path planning and task scheduling are two challenging problems in the design of multiple autonomous agents. Both problems can be solved by the use of exhaustive search techniques such as model checking and algorithmic game theory. However, model checking suffers from the infamous state-space explosion problem that makes it inefficient at solving the problems when the number of agents is large, whi...

Agile Beyond Teams and Feedback Beyond Software in Automotive Systems

S. Ågren, Rogardt Heldal, E. Knauss, Patrizio Pelliccione. In: IEEE Transactions on Engineering Management. 2022

Abstract: In order to increase the ability to build complex, software-intensive systems, as well as to decrease time-to-market for new functionality, automotive companies aim to scale agile methods beyond individual teams. This is challenging, given the specifics of automotive systems that are often safety-critical and consist of software, hardware, and mechanical components. In this article, we investigate...

Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing

M. H. Moghadam, Markus Borg, Mehrdad Saadatmand, S. J. Mousavirad, M. Bohlin et al. In: ArXiv. 2022

Abstract: This paper presents an extended version of Deeper, a search-based simulation-integrated test solution that generates failure-revealing test scenarios for testing a deep neural network-based lane-keeping system. In the newly proposed version, we utilize a new set of bio-inspired search algorithms, genetic algorithm (GA), $({\mu}+{\lambda})$ and $({\mu},{\lambda})$ evolution strategies (ES), and par...

Machine learning testing in an ADAS case study using simulation‐integrated bio‐inspired search‐based testing

M. H. Moghadam, Markus Borg, Mehrdad Saadatmand, S. J. Mousavirad, M. Bohlin et al. In: Journal of Software: Evolution and Process. 2022

Abstract: This paper presents an extended version of Deeper, a search‐based simulation‐integrated test solution that generates failure‐revealing test scenarios for testing a deep neural network‐based lane‐keeping system. In the newly proposed version, we utilize a new set of bio‐inspired search algorithms, genetic algorithm (GA), (μ+λ) and (μ,λ) evolution strategies (ES), and particle swarm optimization (PS...

Non-Functional Requirements for Machine Learning: An Exploration of System Scope and Interest

K. M. Habibullah, Gregory Gay, J. Horkoff. In: 2022 IEEE/ACM 1st International Workshop on Software Engineering for Responsible Artificial Intelligence (SE4RAI). 2022

Abstract: Systems that rely on Machine Learning (ML systems) have differing demands on quality—non-functional requirements (NFRs)— compared to traditional systems. NFRs for ML systems may differ in their definition, scope, and importance. Despite the importance of NFRs for ML systems, our understanding of their definitions and scope—and of the extent of existing research—is lacking compared to our understan...

On the computation of interprocedural weak control closure

A. Masud, B. Lisper. In: Proceedings of the 31st ACM SIGPLAN International Conference on Compiler Construction. 2022

Abstract: Many program analysis techniques depend on capturing the control dependencies of the program. Most existing control dependence algorithms either compute intraprocedural control dependencies only, or they compute control dependence relations that are not precise in general including nonterminating systems. Weak control closure (WCC) subsumes all known nontermination insensitive control dependence r...

Compliance checking of software processes: A systematic literature review

Julieth Patricia Castellanos Ardila, B. Gallina, Faiz ul Muram. In: Journal of Software: Evolution and Process. 2022

Abstract: The processes used to develop software need to comply with normative requirements (e.g., standards and regulations) to align with the market and the law. Manual compliance checking is challenging because there are numerous requirements with changing nature and different purposes. Despite the importance of automated techniques, there is not any systematic study in this field. This lack may hinder o...

Empirical study on software and process quality in bioinformatics tools

Katalin Ferenc, K. Otto, Francisco Gomes de Oliveira Neto, Marcela Dávila López, J. Horkoff et al. In: bioRxiv. 2022

Abstract: Software quality in computational tools impacts research output in a variety of scientific disciplines. Biology is one of these fields, especially for High Throughput Sequencing (HTS) data, such tools play an important role. This study therefore characterises the overall quality of a selection of tools which are frequently part of HTS pipelines, as well as analyses the maintainability and process ...

Dependency management bots in open-source systems—prevalence and adoption

Linda Erlenhov, F. D. O. Neto, P. Leitner. In: PeerJ Computer Science. 2022

Abstract: Bots have become active contributors in maintaining open-source repositories. However, the definitions of bot activity in open-source software vary from a more lenient stance encompassing every non-human contributions vs frameworks that cover contributions from tools that have autonomy or human-like traits (i.e., Devbots). Understanding which of those definitions are being used is essential to ena...

ROUTE: A Framework for Customizable Smart Mobility Planners

Fahed Alkhabbas, Martina De Sanctis, A. Bucchiarone, A. Cicchetti, Romina Spalazzese et al. In: 2022 IEEE 19th International Conference on Software Architecture (ICSA). 2022

Abstract: Multimodal journey planners are used worldwide to support travelers in planning and executing their journeys. Generated travel plans usually involve local mobility service providers, consider some travelers’ preferences, and provide travelers information about the routes’ current status and expected delays. However, those planners cannot fully consider the special situations of individual cities w...

Digital Twins

Jeffrey C. Carver, M. Staron, R. Capilla, H. Muccini, L. Hochstein. In: IEEE Softw.. 2022

Correction to: On the relationship between similar requirements and similar software

Muhammad Abbas, Alessio Ferrari, Anas Shatnawi, Eduard Paul Enoiu, Mehrdad Saadatmand et al. In: Requirements Engineering. 2022

Human-based Test Design versus Automated Test Generation: A Literature Review and Meta-Analysis

Ted Kurmaku, Eduard Paul Enoiu, Musa Kumrija. In: Proceedings of the 15th Innovations in Software Engineering Conference. 2022

Abstract: Automated test generation has been proposed to allow test cases to be created with less effort. While much progress has been made, it remains a challenge to automatically generate strong as well as small test suites that are also relevant to engineers. However, how these automated test generation approaches compare to or complement manually written test cases is still an open research question. In...

Towards an AI‐driven business development framework: A multi‐case study

Meenu Mary John, H. Olsson, Jan Bosch. In: Journal of Software: Evolution and Process. 2022

Abstract: Artificial intelligence (AI) and the use of machine learning (ML) and deep learning (DL) technologies are becoming increasingly popular in companies. These technologies enable companies to leverage big quantities of data to improve system performance and accelerate business development. However, despite the appeal of ML/DL, there is a lack of systematic and structured methods and processes to help...

Registered Report: A Laboratory Experiment on Using Different Financial-Incentivization Schemes in Software-Engineering Experimentation

Jacob Krüger, G. Çalikli, Dmitri Bershadskyy, Robert Heyer, Sarah Zabel et al. In: ArXiv. 2022

Abstract: Empirical studies in software engineering are often conducted with open-source developers or in industrial collaborations. This has resulted in few experiments using financial incentives (e.g., money, vouchers) as a strategy to motivate the participants’ behavior; which is typically done in other research communities, such as economics or psychology. Even the current version of the SIGSOFT Empiric...