An industry-academia, multidisciplinary and expertise-heterogeneous design approach: a case study on designing for mobility

Trabalho apresentado na: "DIGICOM 2021 – 5th International Conference on Design and Digital Communication", 4-6 November 2021, Teatro Gil Vicente, Barcelos, Portugal.The purpose of this article is to provide a better understanding of how to effectively develop design projects that simultaneously leverage industry and academic partners, participants from various disciplinary backgrounds, and vari- ous levels of expertise to solve complex problems. The article reports a single case of an ongoing project focused on designing smart and connected devices for mobility, which integrates the dimensions of interest. Our findings highlight the importance of careful planning of the collaborative process, contemplating of- fline and real-time communication opportunities, identifying cross-boundary roles, and considering the development of shared expertise and knowledge within the team. By confronting these findings with key literature, we offer five recom- mendations to inform similar future projects.This work is supported by European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Pro- gramme (COMPETE 2020) [Project no 039334; Funding Reference: POCI-01-0247- FEDER-039334]. This work has additional financial support from Project Lab2PT - Landscapes, Heritage and Territory laboratory - AUR/04509, with financial support from FCT/MCTES through national funds (PIDDAC) and co-financing from the Eu- ropean Regional Development Fund (FEDER) POCI-01-0145-FEDER-007528, in line with the new partnership agreement PT2020 through COMPETE 2020 – Compet- itiveness and Internationalization Operational Program (POCI)

La gestion de la connaissance des équipes de développement logiciel

RÉSUMÉ Contexte : Le développement logiciel est un travail d’équipe manipulant un produit essentiellement invisible. En conséquent, le développement logiciel nécessite des échanges de connaissances importants entre développeurs afin que l’équipe effectue une résolution de problème adéquate. Cette résolution de problème résulte en une prise de décision qui aura un impact direct sur la qualité du produit logiciel final. Objectif : Ce travail doctoral a pour objectif de mieux comprendre ces interactions entre développeurs et comment ces interactions peuvent être liées à des problèmes de qualité logicielle. Cette meilleure compréhension du phénomène permet d’améliorer les approches actuelles de développement logiciel afin d’assurer une meilleure qualité du produit final. Méthodologie : Premièrement, des revues de littérature ont été effectuées afin de mieux comprendre l’état actuel de la recherche en gestion de connaissance dans le génie logiciel. Deuxièmement, des analyses de code source et des discussions avec les développeurs ont été faites afin de mieux cerner les causes de problèmes classiques de qualité logicielle. Finalement, des observations faites dans l’industrie ont permis de comprendre la prise de décision collective, et comment cette prise de décision impacte la qualité logicielle. Résultats : Les observations effectuées ont démontré que la qualité logicielle n’est pas qu’un problème d’éducation ; l’essentiel des problèmes de qualité ont été introduits par les développeurs en toute connaissance de cause afin de répondre à d’autres impératifs plus urgents au moment de la prise de décision. Améliorer la qualité des logiciels demande de revoir la manière dont les projets de développement logiciel sont gérés afin d’assurer que les décisions prises sur le terrain n’auront pas de conséquences négatives trop coûteuses à long terme. Conclusions : Il est recommandé que les organisations se dote d’un nouveau palier décisionnel faisant la jointure entre besoins techniques (i.e. qualité logicielle) et administratifs (i.e. ressources disponibles). Ce nouveau palier décisionnel se situerait au niveau de la base de code (« codebase »), soit entre le palier organisationnel et le palier de gestion de projet. Une base de code étant modifiée de manière concurrente par plusieurs projets en parallèle, il devient nécessaire d’avoir un meilleur contrôle sur les modifications effectuées sur celle-ci. Ce nouveau palier serait le gardien des connaissances en lien avec la base de code, selon le principe « you build it, you run it » favorisé dans certaines organisations. Ce nouveau palier serait responsable d’assurer que la base de code reste d’une qualité suffisamment bonne pour supporter les activités de l’organisation dans l’avenir.----------ABSTRACT Context: Software development is a process requiring teamwork on an essentially invisible product. Therefore, software development requires important knowledge exchanges between developers in order to ensure a proper problem resolution. This problem resolution affects the decision making process, which will have a direct impact on the software quality of the final product. Objective: This thesis work aims to better understand these interactions between developers and how they can be linked to software quality problems. With a better understanding of the relation, it will be possible to improve the current software development management practices in order to ensure a better quality of the final software product. Method: First, literature reviews were made with the objective to understand the current state of the research in knowledge management in software engineering. Second, source code analyzes and discussions with the developers were executed in order to better understand the causes of typical software quality issues. Finally, observations were made in an industrial context in order to observe collective decision making in the field, and to understand how these decisions impacts software quality. Results: The bservations made demonstrated that software quality is not only an educational problem; most of the quality problems found were introduced voluntarily by the developers in order to answer a more urgent requirement at the time. Improving software quality therefore requires a review of how software development projects are managed in order to ensure that the decision made in the field do not have overly costly consequences in the long term. Conclusions: It is recommended that organization assign a new decision level linking the technical requirements (i.e. software quality) with administrative requirements (i.e. available resources). This new decision level would be situated at the codebase level, between the organizational strategy level and the project management level. A codebase being modified concurrently by multiple projects, it is therefore necessary to have a better control of the modifications made on it. The people at this new decision level would be the knowledge repository related to the codebase, under the “you build it, you run it” principle popular in some organizations. This new decision level would be responsible of ensuring that the codebase remains of a sufficient quality in order to support the future activities of the organization

Empirical Standards for Software Engineering Research

Empirical Standards are natural-language models of a scientific community's expectations for a specific kind of study (e.g. a questionnaire survey). The ACM SIGSOFT Paper and Peer Review Quality Initiative generated empirical standards for research methods commonly used in software engineering. These living documents, which should be continuously revised to reflect evolving consensus around research best practices, will improve research quality and make peer review more effective, reliable, transparent and fair.Comment: For the complete standards, supplements and other resources, see https://github.com/acmsigsoft/EmpiricalStandard

Towards an operationalization of test-driven development skills: An industrial empirical study

Abstract Context: The majority of the empirical studies on Test-driven development (TDD) are concerned with verifying or refuting the effectiveness of the technique over a traditional approach, and they tend to neglect whether the subjects possess the necessary skills to apply TDD, though they argue such skills are necessary. Objective: We evaluate a set of minimal, a priori and in process skills necessary to apply TDD. We determine whether variations in external quality (i.e., number of defects) and productivity (i.e., number of features implemented) can be associated with different clusters of the TDD skills? set. Method: We executed a quasi-experiment involving 30 practitioners from industry. We first grouped the participants according to their TDD skills? set (consisting of a priori experience on programming and testing as well as in-process TDD conformance) into three levels (Low-Medium-High) using k-means clustering. We then applied ANOVA to compare the clusters in terms of external quality and productivity, and conducted post-hoc pairwise analysis. Results: We did not observe a statistically significant difference between the clusters either for external software quality ( F ( 2 , 27 = 1.44 , p = . 260 ), or productivity ( F ( 2 , 27 ) = 3.02 , p = . 065 ). However, the analysis of the effect sizes and their confidence intervals shows that the TDD skills? set is a factor that could account for up to 28% of the external quality, and 38% for productivity. Conclusion: We have reason to conclude that focusing on the improvement of TDD skills? set investigated in this study could benefit software developers in improving their baseline productivity and the external quality of the code they produce. However, replications are needed to overcome the issues related with the statistical power of this study. We suggest practical insights for future work to investigate the phenomenon further.hisresearchispartiallysupportedbytheAcademyofFinlandwithdecisionno.:278354,andbyFinnishDistinguishedProfessor(Fi.Di.Pro.) programme, ESEIL

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

Quality measurement in agile and rapid software development: A systematic mapping

Context: In despite of agile and rapid software development (ARSD) being researched and applied extensively, managing quality requirements (QRs) are still challenging. As ARSD processes produce a large amount of data, measurement has become a strategy to facilitate QR management. Objective: This study aims to survey the literature related to QR management through metrics in ARSD, focusing on: bibliometrics, QR metrics, and quality-related indicators used in quality management. Method: The study design includes the definition of research questions, selection criteria, and snowballing as search strategy. Results: We selected 61 primary studies (2001-2019). Despite a large body of knowledge and standards, there is no consensus regarding QR measurement. Terminology is varying as are the measuring models. However, seemingly different measurement models do contain similarities. Conclusion: The industrial relevance of the primary studies shows that practitioners have a need to improve quality measurement. Our collection of measures and data sources can serve as a starting point for practitioners to include quality measurement into their decision-making processes. Researchers could benefit from the identified similarities to start building a common framework for quality measurement. In addition, this could help researchers identify what quality aspects need more focus, e.g., security and usability with few metrics reported.This work has been funded by the European Union’s Horizon 2020 research and innovation program through the Q-Rapids project (grant no. 732253). This research was also partially supported by the Spanish Ministerio de Economía, Industria y Competitividad through the DOGO4ML project (grant PID2020-117191RB-I00). Silverio Martínez-Fernández worked in Fraunhofer IESE before January 2020.Peer ReviewedPostprint (published version

Lessons Learned from Developing a Sustainability Awareness Framework for Software Engineering using Design Science

[Context and Motivation] To foster a sustainable society within a sustainable environment, we must dramatically reshape our work and consumption activities, most of which are facilitated through software. Yet, most software engineers hardly consider the effects on the sustainability of the IT products and services they deliver. This issue is exacerbated by a lack of methods and tools for this purpose.[Question/Problem] Despite the practical need for methods and tools that explicitly support consideration of the effects that IT products and services have on the sustainability of their intended environments, such methods and tools remain largely unavailable. Thus, urgent research is needed to understand how to design such tools for the IT community properly.[Principal Ideas/Results] In this paper, we describe our experience using design science to create the Sustainability Awareness Framework (SusAF), which supports software engineers in anticipating and mitigating the potential sustainability effects during system development. More specifically, we identify and present the challenges faced during this process.[Contribution] The challenges that we have faced and addressed in the development of the SusAF are likely to be relevant to others who aim to create methods and tools to integrate sustainability analysis into their IT Products and Service development. Thus, the lessons learned in SusAF development are shared for the benefit of researchers and other professionals who design tools for that end

Regulatory Compliance-oriented Impediments and Associated Effort Estimation Metrics in Requirements Engineering for Contractual Systems Engineering Projects

Large-scale contractual systems engineering projects often need to comply with a myriad of government regulations and standards as part of contractual fulfillment. A key activity in the requirements engineering (RE) process for such a project is to elicit appropriate requirements from the regulations and standards that apply to the target system. However, there are impediments in achieving compliance due to such factors as: the voluminous contract and its high-level specifications, large number of regulatory documents, and multiple domains of the system. Little empirical research has been conducted on developing a shared understanding of the compliance-oriented complexities involved in such projects, and identifying and developing RE support (such as processes, tools, metrics, and methods) to improve overall performance for compliance projects. Through three studies on an industrial RE project, we investigated a number of issues in RE concerning compliance, leading to the following novel results:(i) a meta-model that captures artefacts-types and their compliance-oriented inter-relationships that exist in RE for contractual systems engineering projects; (ii) discovery of key impediments to requirements-compliance due to: (a) contractual complexities (e.g., regulatory requirements specified non-contiguously with non-regulatory requirements in the contract at the ratio of 1:19), (b) complexities in regulatory documents (e.g., over 300 regulatory documents being relevant to the subject system), and (c) large and complex system (e.g., 40% of the contractual regulatory requirements are cross-cutting); (iii) a method for deriving base metrics for estimating the effort needed to do compliance work during RE and demonstrate how a set of derived metrics can be used to create an effort estimation model for such work; (iv) a framework for structuring diverse regulatory documents and requirements for global product developments. These results lay a foundation in RE research on compliance issues with anticipation for its impact in real-world projects and in RE research