SC Harvester Papers Database Interface

From RE Cares to SE Cares: Software Engineering for Social Good, One Venue at a Time

Alex Dekhtyar, J. Hayes, Jared Payne, Tingting Yu, J. Horkoff et al. In: 2020 IEEE/ACM 42nd International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS). 2020

Foreword to the Special Issue in Empirical Software Engineering: Best Papers of REFSQ 2019

E. Knauss, M. Goedicke, P. Grünbacher. In: Empirical Software Engineering. 2020

Foreword to the Special Issue in Empirical Software Engineering: Best Papers of REFSQ 2019

E. Knauss, M. Goedicke, P. Grünbacher. In: Empirical Software Engineering. 2020

Cerebral ischemia detection using artificial intelligence (CIDAI)—A study protocol

L. Block, A. Merhi, Jaquette Liljencrantz, S. Naredi, M. Staron et al. In: Acta Anaesthesiologica Scandinavica. 2020

Abstract: The onset of cerebral ischemia is difficult to predict in patients with altered consciousness using the methods available. We hypothesize that changes in Heart Rate Variability (HRV), Near‐Infrared Spectroscopy (NIRS), and Electroencephalography (EEG) correlated with clinical data and processed by artificial intelligence (AI) can indicate the development of imminent cerebral ischemia and reperfusi...

Curriculum integration of sustainability in engineering education – a national study of programme director perspectives

O. Leifler, Jon-Erik Dahlin. In: International Journal of Sustainability in Higher Education. 2020

Abstract: Purpose This study aims to report on how programme directors address sustainability within engineering education at Swedish universities and engineering colleges. Design/methodology/approach The study was performed as a survey with follow-up interviews around the following core questions: to what extent do programme directors possess a deep understanding of the subject of sustainable developmen...

Developing ML/DL Models: A Design Framework

Meenu Mary John, H. Olsson, J. Bosch. In: 2020 IEEE/ACM International Conference on Software and System Processes (ICSSP). 2020

Abstract: Artificial Intelligence is becoming increasingly popular with organizations due to the success of Machine Learning and Deep Learning techniques. Using these techniques, data scientists learn from vast amounts of data to enhance behaviour in software-intensive systems. Despite the attractiveness of these techniques, however, there is a lack of systematic and structured design process for developing...

Determining Context Factors for Hybrid Development Methods with Trained Models

J. Klünder, Dzejlana Karajic, Paolo Tell, Oliver Karras, C. Münkel et al. In: 2020 IEEE/ACM International Conference on Software and System Processes (ICSSP). 2020

Abstract: Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method ...

Why do Software Teams Deviate from Scrum? Reasons and Implications

M. Mortada, Hamdy Michael Ayas, R. Hebig. In: 2020 IEEE/ACM International Conference on Software and System Processes (ICSSP). 2020

Abstract: Human, social, organizational, and technical aspects are intertwined with each other in software teams during the software development process. Practices that teams actually adopt often deviate from those of the used frameworks, such as Scrum. However, currently there is little empirical insight explaining typical deviations, including their reasons and consequences. In this paper we use observati...

Emerging and Changing Tasks in the Development Process for Machine Learning Systems

Hanyan Liu, Samuel Eksmo, Johan Risberg, R. Hebig. In: 2020 IEEE/ACM International Conference on Software and System Processes (ICSSP). 2020

Abstract: Integrating machine learning components in software systems is a task more and more companies are confronted with. However, there is not much knowledge today on how the software development process needs to change, when such components are integrated into a software system. We performed an interview study with 16 participants, focusing on emerging and changing task. The results uncover a set of 25...

From Ad-Hoc Data Analytics to DataOps

A. Munappy, D. I. Mattos, J. Bosch, H. Olsson, Anas Dakkak. In: 2020 IEEE/ACM International Conference on Software and System Processes (ICSSP). 2020

Abstract: The collection of high-quality data provides a key competitive advantage to companies in their decision-making process. It helps to understand customer behavior and enables the usage and deployment of new technologies based on machine learning. However, the process from collecting the data, to clean and process it to be used by data scientists and applications is often manual, non-optimized and er...

Cuckoo-PC: An Evolutionary Synchronization-Aware Placement of SDN Controllers for Optimizing the Network Performance in WSNs

Shirin Tahmasebi, Mohadeseh Safi, Somayeh Zolfi, Mohammad Reza Maghsoudi, H. Faragardi et al. In: Sensors (Basel, Switzerland). 2020

Abstract: Due to reliability and performance considerations, employing multiple software-defined networking (SDN) controllers is known as a promising technique in Wireless Sensor Networks (WSNs). Nevertheless, employing multiple controllers increases the inter-controller synchronization overhead. Therefore, optimal placement of SDN controllers to optimize the performance of a WSN, subject to the maximum num...

Beyond connected cars: A systems of systems perspective

Patrizio Pelliccione, E. Knauss, S. Ågren, Rogardt Heldal, Carl Bergenhem et al. In: Sci. Comput. Program.. 2020

Abstract: Abstract The automotive domain is rapidly changing in the last years. Among the different challenges OEMs (i.e. the vehicle manufacturers) are facing, vehicles are evolving into systems of systems. In fact, over the last years vehicles have evolved from disconnected and “blind” systems to systems that are (i) able to sense the surrounding environment and (ii) connected with other vehicles, the cit...

Experimentation for Business-to-Business Mission-Critical Systems: A Case Study

D. I. Mattos, Anas Dakkak, J. Bosch, H. Olsson. In: 2020 IEEE/ACM International Conference on Software and System Processes (ICSSP). 2020

Abstract: Continuous experimentation (CE) refers to a group of practices used by software companies to rapidly assess the usage, value and performance of deployed software using data collected from customers and the deployed system. Despite its increasing popularity in the development of web-facing applications, CE has not been discussed in the development process of business-to-business (B2B) mission-criti...

An empirical study of bots in software development: characteristics and challenges from a practitioner’s perspective

Linda Erlenhov, F. D. O. Neto, P. Leitner. In: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 2020

Abstract: Software engineering bots – automated tools that handle tedious tasks – are increasingly used by industrial and open source projects to improve developer productivity. Current research in this area is held back by a lack of consensus of what software engineering bots (DevBots) actually are, what characteristics distinguish them from other tools, and what benefits and challenges are associated with...

PHANTOM: Curating GitHub for engineered software projects using time-series clustering

P. Pickerill, Heiko Joshua Jungen, Miroslaw Ochodek, M. Mackowiak, M. Staron. In: Empirical Software Engineering. 2020