Agile software companies applying the DevOps approach require collaboration and information sharing between practitioners in various roles to produce value. Adopting new development practices affects how practitioners collaborate, requiring companies to form a closer connection between business strategy and software development. However, the types of information management, sales, and development needed to plan, evaluate features, and reconcile their expectations with each other need to be clarified. To support practitioners in collaborating and realizing changes to their practices, we investigated what information is needed and how it should be represented to support different stakeholders in their tasks. Compared to earlier research, we adopted a holistic approach—by including practitioners throughout the development process—to better understand the information needs from a broader viewpoint. We conducted six workshops and 12 semi-structured interviews at three Finnish small and medium-sized enterprises from different software domains. Thematic analysis was used to identify information-related issues and information and visualization needs for daily tasks. Three themes were constructed as the result of our analysis. Visual information representation catalyzes stakeholder discussion, and supporting information exchange between stakeholder groups is vital for efficient collaboration in software product development. Additionally, user-centric data collection practices are needed to understand how software products are used and to support practitioners’ daily information needs. We also found that a passive way of representing information, such as a dashboard that would disturb practitioners only when attention is needed, was preferred for daily information needs. The software engineering community should consider reviewing the information needs of practitioners from a more holistic view to better understand how tooling support can benefit information exchange between stakeholder groups when making product development decisions and how those tools should be built to accommodate different stakeholder views.

Data science projects have become commonplace over the last decade. During this time, the practices of running such projects, together with the tools used to run them, have evolved considerably. Furthermore, there are various studies on data science workflows and data science project teams. However, studies looking into both workflows and teams are still scarce and comprehensive works to build a holistic view do not exist. This study bases on a prior case study on roles and processes in data science. The goal here is to create a deeper understanding of data science projects and development processes. We conducted a survey targeted at experts working in the field of data science (n=50) to understand data science projects’ team structure, roles in the teams, utilized project management practices and the challenges in data science work. Results show little difference between big data projects and other data science. The found differences, however, give pointers for future research on how agile data science projects are, and how important is the role of supporting project management personnel. The current study is work in progress and attempts to spark discussion and new research directions.

Understanding users, their requirements and usage patterns helps building better software. To continuously improve operations, user-interaction (U-I) data can provide developers with interesting new possibilities. This study aims at gaining an understanding of how software teams can start the use of U-I data and what challenges they face with it. In this paper, we describe three cases from different organizations. This includes explaining the activities, objectives, and challenges of each team in their efforts to begin using U-I data. We conducted the study with Action Design Research (ADR) method, resulting in findings from each case by intervening in the work of these teams. As a contribution, we designed a U-I data utilization method that summarizes teams' activities. Secondly, we refined and validated the categorizations of U-I data analysis and utilization objectives, and finally we categorized the challenges that the case teams faced. Together, these contributions lay out clear steps also for other software teams in starting the utilization of U-I data.

Modern software organizations invest substantial effort in building and automating their tool chain. The goal is to maximize both the speed of development, and how rapidly new software is deployed. This paper presents results from a descriptive and exploratory single case study from an ongoing project of Finnish company Solita. Based on data from version control and production logs, we investigate the feature flow in the project to study the effect of lean processes and the continuous deployment tool chain to waste produced by the deployment pipeline. We find that flow efficiency can be improved simply by minimizing the idle time the feature waits in the production process after its implementation has been finalized. This reduction of waste benefits both end users and developers -- the users get access to new features, and the developers receive timely feedback.

Software development is today done in teams of software developers who may be distributed all over the world. Software development has also become to contain more social aspects and the need for collaboration has become more evident. The importance of teaching development methods used in collaborative development is of importance, as skills beyond traditional software development are needed in this modern setting. A novel, student centric approach was tried out at Tampere University of Technology where a new environment called KommGame was introduced. This environment includes a reputation system to support the social aspect of the environment and thus supporting the learners collaboration with each other. In this paper, we present the KommGame environment and how it was applied on a course for practical results.