Preface : Journal first track

Publisher Copyright: © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).ECSA 2021 opened up a partnership with Journal of Systems and Software (JSS) and IEEE Software to incorporate journal-first papers into its program. Authors of journal first papers accepted by JSS or IEEE Software since January 2020 were invited to submit their work to be presented at ECSA 2021. This allowed authors of journal first papers to present their work to the community. In the end five papers were selected to be presented at the conference.Peer reviewe

Undulate : A framework for data-driven software engineering enabling soft computing

Context. Especially web-facing software systems enable the collection of usage data at a massive scale. At the same time, the scale and scope of software processes have grown substantively. Automated tools are needed to increase the speed and quality of controlling software processes. The usage data has great potential as a driver for software processes. However, research still lacks constructs for collecting, refining and utilising usage data in controlling software processes.Objective. The objective of this paper is to introduce a framework for data-driven software engineering. The UNDULATE framework covers generating, collecting and utilising usage data from software processes and business processes supported by the software produced. In addition, we define the concepts and process of extreme continuous experimentation as an exemplar of a software engineering process.Method. We derive requirements for the framework from the research literature, with a focus on papers inspired by practical problems. In addition, we apply a multilevel modelling language to describe the concepts related to extreme continuous experimentation.Results. We introduce the UNDULATE framework and give requirements and provide an overview of the processes of collecting usage data, augmenting it with additional dimensional data, aggregating the data along the dimensions and computing different metrics based on the data and other metrics.Conclusions. The paper represents significant steps inspired by previous research and practical insight towards standardised processes for data-driven software engineering, enabling the application of soft computing and other methods based on artificial intelligence.Peer reviewe

Towards novel and intentional cooperation of diverse autonomous robots : An architectural approach

Publisher Copyright: © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).In most autonomous robot approaches, the individual robot’s goals and cooperation behavior are fixed during the design. Moreover, the robot’s design may limit its ability to perform other than initially planned tasks. This leaves little room for novel dynamic cooperation where new (joint) actions could be formed or goals adjusted after deployment. In this paper, we address how situational context augmented with peer modeling can foster cooperation opportunity identification and cooperation planning. As a practical contribution, we introduce our new software architecture that enables developing, training, testing, and deploying dynamic cooperation solutions for diverse autonomous robots. The presented architecture operates in three different worlds: in the Real World with real robots, in the 3D Virtual World by emulating the real environments and robots, and in an abstract 2D Block World that fosters developing and studying large-scale cooperation scenarios. Feedback loops among these three worlds bring data from one world to another and provide valuable information to improve cooperation solutions.Peer reviewe

An Exploratory Analysis of a Hybrid OSS Company’s Forum in Search of Sales Leads

—Background:Onlineforumsareinstrumentsthrough which information or problems are shared and discussed, including expressions of interests and intentions. Objective: In this paper, we present ongoing work aimed at analyzing the content of forum posts of a hybrid open source company that offers both free and commercial licenses, in order to help its community manager gain improved understanding of the forum discussions and sentiments and automatically discover new opportunities such as sales leads, i.e., people who are interested in buying a license. These leads can then be forwarded to the sales team for follow-up and can result in them potentially making a sale, thus increasing company revenue. Method: For the analysis of the forums, an untapped channel for sales leads by the company, text analysis techniques are utilized to identify potential sales leads and the discussion topics and sentiments in those leads. Results: Results of our preliminary work make a positive contribution in lessening the community manager’s work in understanding the sentiment and discussion topics in the hybrid open source forum community, as well as make it easier and faster to identify potential future customers. Conclusion: We believe that the results will positively contribute to improving the sales of licenses for the hybrid open source companyPeer reviewe

How to Report the Contributions of a CC System?

We argue that the lack of well established reporting practices for applied Computational Creativity systems is hindering progress in the field. We consider that the current lack of reporting details – and variation in form and content – makes it difficult for third parties to reliably evaluate and compare systems based on pub-licly available information. This hinders forming an un-derstanding of the similarities, differences and relative qualities of these systems. We propose a set of building blocks for robustly reporting the contributions of computationally creative systems to promote visibility and clarity in the field.Peer reviewe

Software product lines and variability modeling : A tertiary study

Context: A software product line is a means to develop a set of products in which variability is a central phenomenon captured in variability models. The field of SPLs and variability have been topics of extensive research over the few past decades. Objective: This research characterizes systematic reviews (SRs) in the field, studies how SRs analyze and use evidence-based results, and identifies how variability is modeled. Method: We conducted a tertiary study as a form of systematic review. Results: 86 SRs were included. SRs have become a widely adopted methodology covering the field broadly otherwise except for variability realization. Numerous variability models exist that cover different development artifacts, but the evidence is insufficient in quantity and immature, and we argue for better evidence. SRs perform well in searching and selecting studies and presenting data. However, their analysis and use of the quality of and evidence in the primary studies often remains shallow, merely presenting of what kinds of evidence exist. Conclusions: There is a need for actionable, context-sensitive, and evaluated solutions rather than novel ones. Different kinds of SRs (SLRs and Maps) need to be better distinguished, and evidence and quality need to be better used in the resulting syntheses. (C) 2019 The Authors. Published by Elsevier Inc.Context: A software product line is a means to develop a set of products in which variability is a central phenomenon captured in variability models. The field of SPLs and variability have been topics of extensive research over the few past decades. Objective: This research characterizes systematic reviews (SRs) in the field, studies how SRs analyze and use evidence-based results, and identifies how variability is modeled. Method: We conducted a tertiary study as a form of systematic review. Results: 86 SRs were included. SRs have become a widely adopted methodology covering the field broadly otherwise except for variability realization. Numerous variability models exist that cover different development artifacts, but the evidence is insufficient in quantity and immature, and we argue for better evidence. SRs perform well in searching and selecting studies and presenting data. However, their analysis and use of the quality of and evidence in the primary studies often remains shallow, merely presenting of what kinds of evidence exist. Conclusions: There is a need for actionable, context-sensitive, and evaluated solutions rather than novel ones. Different kinds of SRs (SLRs and Maps) need to be better distinguished, and evidence and quality need to be better used in the resulting syntheses. (C) 2019 The Authors. Published by Elsevier Inc.Context: A software product line is a means to develop a set of products in which variability is a central phenomenon captured in variability models. The field of SPLs and variability have been topics of extensive research over the few past decades. Objective: This research characterizes systematic reviews (SRs) in the field, studies how SRs analyze and use evidence-based results, and identifies how variability is modeled. Method: We conducted a tertiary study as a form of systematic review. Results: 86 SRs were included. SRs have become a widely adopted methodology covering the field broadly otherwise except for variability realization. Numerous variability models exist that cover different development artifacts, but the evidence is insufficient in quantity and immature, and we argue for better evidence. SRs perform well in searching and selecting studies and presenting data. However, their analysis and use of the quality of and evidence in the primary studies often remains shallow, merely presenting of what kinds of evidence exist. Conclusions: There is a need for actionable, context-sensitive, and evaluated solutions rather than novel ones. Different kinds of SRs (SLRs and Maps) need to be better distinguished, and evidence and quality need to be better used in the resulting syntheses. (C) 2019 The Authors. Published by Elsevier Inc.Peer reviewe

On the Inherent Creativity of Self-Adaptive Systems

We argue that frameworks employed in architecting self-adaptive systems allow the system to exhibit creative behaviour, and that many of the existing self-adaptive systems operating in domains which are typically not associated with creativity are inherently creative. However, even the current state-of-the-art solutions do not fully exploit stronger forms of creative behaviour, which are required in complex environments, where the system constantly encounters fundamentally novel situations. To this end, software development necessitates a paradigm shift parallel to moving from procedural design methodology toward self-aware systems where the system adapts to its context at run time.Peer reviewe

An Architectural Approach for Enabling and Developing Cooperative Behaviour in Diverse Autonomous Robots

The paper introduces an architecture for robot-to-robot cooperation which takes into consideration how situational context augmented with peer modeling fosters cooperation opportunity identification and cooperation planning. The presented architecture allows developing, training, testing, and deploying dynamic cooperation solutions for diverse autonomous robots using ontology-based reasoning. The architecture operates in three different worlds: in the Real World with real robots, in a 3D Virtual World by emulating the real environments and robots, and in an abstract Block World that enables developing and studying large-scale cooperation scenarios. We describe an assessment practice for our architecture and cooperation procedures, which is based on scenarios implemented in all three worlds, and provide initial results of stress testing the cooperation procedures in the Block World. Moreover, as the core part of our architecture can operate in all the three worlds, development of the robot cooperation with the architecture can regularly accommodate insights gained from experimenting and testing in one world as improvements in another. We report our insights from developing the architecture and cooperation procedures as additional research outcomes.Peer reviewe

Aspects of Self-awareness: An Anatomy of Metacreative Systems

We formulate a model of computational metacreativity. It consists of various aspects of creative self-awareness that potentially contribute, in various combinations, to the metacreative capabilities of a creative system. Our model is inspired by a psychological view of metacreativity promoting the awareness of one's thoughts during the creative process, and draws from the field of self-adaptive software systems to explicate different viewpoints of metacreativity in creative systems. The model is designed to help in analyzing metacreative capabilities of creative systems, and to guide the development of creative systems to a more autonomous and adaptive direction.Peer reviewe

Energizing collaborative industry‑academia learning: a present case and future visions

In Industry-Academia Collaborations (IAC) both academic, scientific research results and industrial practitioner findings and experiences are produced. Both types of knowledge should be gathered, codified, and disseminated efficiently and effectively. This paper investigates a recent (2014-2017) large-scale IAC R&D&I program case (Need for Speed, N4S) from a learning perspective. It was one of the programs in the Finnish SHOK (Strategic Centres of Science, Technology, and Innovation) system. The theoretical bases are in innovation management, knowledge management, and higher education (university) pedagogy. In the future, IAC projects should be more and more commonplace since major innovations are hardly ever done in isolation, not even by the largest companies. Both intra-organizational and inter-organizational learning networks are increasingly critical success factors. Collaborative learning capabilities will thus be required more often from all the participating parties. Efficient and effective knowledge creation and sharing are underpinning future core competencies. In this paper, we present and evaluate a collaboratively created and publicly shared digital knowledge repository called "Treasure Chest" produced during our case program. The starting point was a jointly created Strategic Research and Innovation Agenda (SRIA), which defined the main research themes and listed motivating research questions to begin with-i.e., intended learning outcomes (ILO). During the 4-year program, our collaborative industry-academia (I-A) learning process produced a range of theoretical and empirical results, which were iteratively collected and packaged into the Treasure Chest repository. Outstandingly, it contained, in addition to traditional research documents, narratives of the industrial learning experiences and more than 100 actionable knowledge items. In conclusion, our vision of the future is that such transparently shared, ambitious, and versatile outcome goals with a continuous integrative collection of the results are keys to effective networked I-A collaboration and learning. In that way, the N4S largely avoided the general problem of often conflicting motives between industrial firms seeking answers and applied solutions to their immediate practical problems and academic researchers aiming at more generalizable knowledge creation and high-quality scientific publications.Peer reviewe