The increasing reliance on Open Source Software (OSS) in organizations’ software supply chains necessitates robust mechanisms in the intake process to ensure sourced components’ long-term viability and maintenance. Assessing OSS project health in the intake process is complex due to the wide range of socio-technical factors involved. This study aims to explore how the health of OSS projects may be assessed by practitioners from organizations’ intake perspective. We conducted a qualitative interview survey with 17 industry experts to identify aspects and related metrics of OSS health. These were mapped against literature and two existing industry frameworks. A subset was identified and applied through a case study at a large international automotive manufacturer. 21 health aspects with 72 connected metrics were identified covering community productivity and stability, orchestration, production processes, and outputs. Many metrics map against industry frameworks, while qualitative aspects are missing support. Special consideration is needed when assessing and comparing the health of OSS projects, including their life-cycle stage, complexity, governance concentration, and strategic importance for the focal organization. The case study shows that not all aspects and metrics may be leveraged due to resource constraints and complexity. Instead, subsets of metrics need to be prioritized, and applied in a structured approach using qualitative and quantitative means. The study provides a foundation and a starting point for developers in introducing health assessments of OSS components in their intake processes, while also pushing convergence towards a common corpus of health assessment in practice.

Abstract Context The adoption of Open Source Software (OSS) in Public Sector Organizations (PSOs) is on the rise, driven by benefits such as enhanced interoperability and transparency. However, PSOs encounter challenges stemming from limited technical capabilities and regulatory constraints in public procurement. Objective This study, based on a registered report, explores the organizational aspects of development in public sector OSS projects, i.e., projects initiated, developed, and governed by PSOs. We conjecture that the development diverges significantly from the commonly adopted bazaar model, wherein development is carried out collaboratively within a broader community. Method A purposefully sampled set of six public sector OSS projects was investigated using mixed-methods and compared with previously reported cases of bazaar OSS projects. Results Among the cases, we note that most (80%) of development efforts typically involve a small group of developers (<15) and rely on formalised processes. Developers are commonly procured from national and local service suppliers. Projects are planned top-down by involved PSOs with funding and contributions to development enabled through centralized or decentralized sponsorship. Projects with a centralized sponsorship have one or a few main PSOs funding the major part of the development. Decentralized sponsorship implies multiple PSOs being mutually dependent on each other to pool the necessary resources for the development. All OSS are reported as being of high quality despite limited size and contributions from their communities. Conclusions Findings suggest that public sector OSS projects deviate from the typical bazaar model, highlighting the need for tailored approaches to address challenges and solutions specific to their context.

Background: Open Source Software (OSS) fuels our global digital infrastructure but is commonly maintained by small groups of people whose time and labor represent a depletable resource. For the OSS projects to stay sustainable, i.e., viable and maintained over time without interruption or weakening, maintenance labor requires an underlying infrastructure to be supported and secured. Aims: Using the construct of human infrastructure, our study aims to investigate how maintenance labor can be supported and secured to enable the creation and maintenance of sustainable OSS projects, viewed from the maintainers’ perspective. Method: In our exploration, we interviewed ten maintainers from nine well-adopted OSS projects. We coded the data in two steps using investigator-triangulation. Results: We constructed a framework of infrastructure design that provide insight for OSS projects in the design of their human infrastructure. The framework specifically highlight the importance of human factors, e.g., securing a work-life balance and proactively managing social pressure, toxicity, and diversity. We also note both differences and overlaps in how the infrastructure needs to support and secure maintenance labor from maintainers and the wider OSS community, respectively. Funding is specifically highlighted as an important enabler for both types of resources. Conclusions: The study contributes to the qualitative understanding of the importance, sensitivity, and risk for depletion of the maintenance labor required to build and maintain healthy OSS projects. Human infrastructure is pivotal in ensuring that maintenance labor is sustainable, and by extension the OSS projects on which we all depend.

Businesses across different areas of interest are increasingly depending on data, particularly for machine learning (ML) applications. To ensure data provisioning, inter-organizational data sharing is proposed, e.g. in the form of data ecosystems. The aim of this study was to perform an exploratory investigation into the data sharing practices that exist in business-to-business (B2B) and business-to-customers (B2C) relations, in order to shape a knowledge foundation for future research. We launched a qualitative survey, using interviews as data collection method. We conducted and analyzed eleven interviews with representatives from seven different companies across several industries with the aim of finding key practices, differences and similarities between approaches, so we could formulate the future research goals and questions. We grouped the core findings of this study into three categories: organizational aspects of data sharing, where we noticed the importance of data sharing and data ownership as business driver; technical aspects of data sharing, related to data types, formats, maintenance and infrastructures; and challenges, with privacy being the highest concern along with the data volumes and cost of data.

Abstract Context Free and Open Source Software (FOSS) communities’ ability to stay viable and productive over time is pivotal for society as they maintain the building blocks that digital infrastructure, products, and services depend on. Sustainability may, however, be characterized from multiple aspects, and less is known how these aspects interplay and impact community outputs, and software quality specifically. Objective This study, therefore, aims to empirically explore how the different aspects of FOSS sustainability impact software quality. Method 16 sustainability metrics across four categories were sampled and applied to a set of 217 OSS projects sourced from the Apache Software Foundation Incubator program. The impact of a decline in the sustainability metrics was analyzed against eight software quality metrics using Bayesian data analysis, which incorporates probability distributions to represent the regression coefficients and intercepts. Results Findings suggest that selected sustainability metrics do not significantly affect defect density or code coverage. However, a positive impact of community age was observed on specific code quality metrics, such as risk complexity, number of very large files, and code duplication percentage. Interestingly, findings show that even when communities are experiencing sustainability, certain code quality metrics are negatively impacted. Conclusion Findings imply that code quality practices are not consistently linked to sustainability, and defect management and prevention may be prioritized over the former. Results suggest that growth, resulting in a more complex and large codebase, combined with a probable lack of understanding of code quality standards, may explain the degradation in certain aspects of code quality.

Motivation: Society’s dependence on Open Source Software (OSS) and the communities that maintain the OSS is ever-growing. So are the potential risks of, e.g., vulnerabilities being introduced in projects not actively maintained. By assessing an OSS project’s capability to stay viable and maintained over time without interruption or weakening, i.e., the OSS health, users can consider the risk implied by using the OSS as is, and if necessary, decide whether to help improve the health or choose another option. However, such assessment is complex as OSS health covers a wide range of sub-topics, and existing support is limited. Aim: We aim to create an overview of characteristics that affect the health of an OSS project and enable the assessment thereof. Method: We conduct a snowball literature review based on a start set of 9 papers, and identify 146 relevant papers over two iterations of forward and backward snowballing. Health characteristics are elicited and coded using structured and axial coding into a framework structure. Results: The final framework consists of 107 health characteristics divided among 15 themes. Characteristics address the socio-technical spectrum of the community of actors maintaining the OSS project, the software and other deliverables being maintained, and the orchestration facilitating the maintenance. Characteristics are further divided based on the level of abstraction they address, i.e., the OSS project-level specifically, or the project’s overarching ecosystem of related OSS projects. Conclusion: The framework provides an overview of the wide span of health characteristics that may need to be considered when evaluating OSS health and can serve as a foundation both for research and practice.

Motivation. Digital commons is an emerging phenomenon and of increasing importance, as we enter a digital society. Open data is one example that makes up a pivotal input and foundation for many of today’s digital services and applications. Ensuring sustainable provisioning and maintenance of the data, therefore, becomes even more important. Aim. We aim to investigate how such provisioning and maintenance can be collaboratively performed in the community surrounding a common. Specifically, we look at Open Data Ecosystems (ODEs), a type of community of actors, openly sharing and evolving data on a technological platform. Method. We use Elinor Ostrom’s design principles for Common Pool Resources as a lens to systematically analyze the governance of earlier reported cases of ODEs using a theory-oriented software engineering framework. Results. We find that, while natural commons must regulate consumption, digital commons such as open data maintained by an ODE must stimulate both use and data provisioning. Governance needs to enable such stimulus while also ensuring that the collective action can still be coordinated and managed within the frame of available maintenance resources of a community. Subtractability is, in this sense, a concern regarding the resources required to maintain the quality and value of the data, rather than the availability of data. Further, we derive empirically-based recommended practices for ODEs based on the design principles by Ostrom for how to design a governance structure in a way that enables a sustainable and collaborative provisioning and maintenance of the data. Conclusion. ODEs are expected to play a role in data provisioning which democratize the digital society and enables innovation from smaller commercial actors. Our empirically based guidelines intend to support this development.

Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public licenses in software ecosystems, similar to Open Source Software (OSS). It has certain similarities to Open Government Data (OGD), where public agencies share data for innovation and transparency. We aimed to explore open data ecosystems involving commercial actors. Thus, we organized five focus groups with 27 practitioners from 22 companies, public organizations, and research institutes. Based on the outcomes, we surveyed three cases of emerging ODE practice to further understand the concepts and to validate the initial findings. The main outcome is an initial conceptual model of ODEs’ value, intrinsics, governance, and evolution, and propositions for practice and further research. We found that ODE must be value driven. Regarding the intrinsics of data, we found their type, meta-data, and legal frameworks influential for their openness. We also found the characteristics of ecosystem initiation, organization, data acquisition and openness be differentiating, which we advise research and practice to take into consideration.

Background: By creating ecosystems around platforms of Open Source Software (OSS) and Open Data (OD), and adopting open collaborative development practices, platform providers may exploit open innovation benefits. However, adopting such practices in a traditionally closed organization is a maturity process that we hypothesize cannot be undergone without friction.

Abstract Context: Software-intensive organizations’ rationale for sharing Open Source Software (OSS) may be driven by both idealistic, strategic and commercial objectives, and include both monetary as well as non-monetary benefits. To gain the potential benefits, an organization may need to consider what they share and how, while taking into account risks, costs and other complexities. Objective: This study aims to empirically investigate objectives and complexities organizations need to consider and balance between when deciding on what software to share as OSS, when to share it, and whether to create a new or contribute to an existing community. Method: A multiple-case study of three case organizations was conducted in two research cycles, with data gathered from interviews with 20 practitioners from these organizations. The data was analyzed qualitatively in an inductive and iterative coding process. Results: 12 contribution objectives and 15 contribution complexities were found. Objectives include opportunities for improving reputation, managing suppliers, managing partners and competitors, and exploiting externally available knowledge and resources. Complexities include risk of loosing control, risk of giving away competitive advantage, risk of creating negative exposure, costs of contributing, and the possibility and need to contribute to an existing or new community. Conclusions: Cross-case analysis and interview validation show that the identified objectives and complexities offer organizations a possibility to reflect on and adapt their contribution strategies based on their specific contexts and business goals.

For a firm in an open source software (OSS) ecosystem, the requirements engineering (RE) process is rather multifaceted. Apart from its typical RE process, there is a competing process, external to the firm and inherent to the firm’s ecosystem. When trying to impose an agenda in competition with other firms, and aiming to align internal product planning with the ecosystem’s RE process, firms need to consider who and how influential the other stakeholders are, and what their agendas are. The aim of the presented research is to help firms identify and analyze stakeholders in OSS ecosystems, in terms of their influence and interactions, to create awareness of their agendas, their collaborators, and how they invest their resources. To arrive at a solution artifact, we applied a design science research approach where we base artifact design on the literature and earlier work. A stakeholder influence analysis (SIA) method is proposed and demonstrated in terms of applicability and utility through a case study on the Apache Hadoop OSS ecosystem. SIA uses social network constructs to measure the stakeholders’ influence and interactions and considers the special characteristics of OSS RE to help firms structure their stakeholder analysis processes in relation to an OSS ecosystem. SIA adds a strategic aspect to the stakeholder analysis process by addressing the concepts of influence and interactions, which are important to consider while acting in collaborative and meritocratic RE cultures of OSS ecosystems.

Despite growing interest of Open Innovation (OI) in Software Engineering (SE), little is known about what triggers software organizations to adopt it and how this affects SE practices. OI can be realized in numerous of ways, including Open Source Software (OSS) involvement. Outcomes from OI are not restricted to product innovation but also include process innovation, e.g. improved SE practices and methods. This study explores the involvement of a software organization (Sony Mobile) in OSS communities from an OI perspective and what SE practices (requirements engineering and testing) have been adapted in relation to OI. It also highlights the innovative outcomes resulting from OI. An exploratory embedded case study investigates how Sony Mobile use and contribute to Jenkins and Gerrit; the two central OSS tools in their continuous integration tool chain. Quantitative analysis was performed on change log data from source code repositories in order to identify the top contributors and triangulated with the results from five semi-structured interviews to explore the nature of the commits. The findings of the case study include five major themes: i) The process of opening up towards the tool communities correlates in time with a general adoption of OSS in the organization. ii) Assets not seen as competitive advantage nor a source of revenue are made open to OSS communities, and gradually, the organization turns more open. iii) The requirements engineering process towards the community is informal and based on engagement. iv) The need for systematic and automated testing is still in its infancy, but the needs are identified. v) The innovation outcomes included free features and maintenance, and were believed to increase speed and quality in development. Adopting OI was a result of a paradigm shift of moving from Windows to Linux. This shift enabled Sony Mobile to utilize the Jenkins and Gerrit communities to make their internal development process better for its software developers and testers.

Open Source Software (OSS) ecosystems have reshaped the ways how software-intensive firms develop products and deliver value to customers. However, firms still need support for strategic product planning in terms of what to develop internally and what to share as OSS. Existing models accurately capture commoditization in software business, but lack operational support to decide what contribution strategy to employ in terms of what and when to contribute. This study proposes a Contribution Acceptance Process (CAP) model from which firms can adopt contribution strategies that align with product strategies and planning. In a design science influenced case study executed at Sony Mobile, the CAP model was iteratively developed in close collaboration with the firm’s practitioners. The CAP model helps classify artifacts according to business impact and control complexity so firms may estimate and plan whether an artifact should be contributed or not. Further, an information meta-model is proposed that helps operationalize the CAP model at the organization. The CAP model provides an operational OI perspective on what firms involved in OSS ecosystems should share, by helping them motivate contributions through the creation of contribution strategies. The goal is to help maximize return on investment and sustain needed influence in OSS ecosystems.

There has been a significant interest in the estimation of time and effort in fixing defects among both software practitioners and researchers over the past two decades. However, most of the focus has been on prediction of time and effort in resolving bugs, without much regard to predicting time needed to complete high-level requirements, a critical step in release planning. In this paper, we describe a mixed-method empirical study on three large IBM projects in which we developed and evaluated a process of training a predictive model constituting a set of 29 features in nine categories in order to predict if a requirement will be completed within its planned iteration. We conducted feature engineering through iterative interviews with IBM practitioners as well as analysis of large development repositories of these three projects. Using machine learning techniques, we were able to make predictions on completion time of requirements at four different stages of their lifetime. Using our industrial partner's interest in high precision over recall, we then adopted a cost sensitive learning method and maximized precision of predictions (ranging from 0.8 to 0.97) while maintaining an acceptable recall. We also ranked the features based on their relative importance to the optimized predictive model. We show that although satisfying predictions can be made at early stages, performance of predictions improves over time by taking advantage of requirements' progress data. Furthermore, feature importance ranking results show that although importance of features are highly dependent on project and prediction stage, there are certain features (e.g. requirement creator, time remained to the end of iteration, time since last requirement summary change and number of times requirement has been replanned for a new iteration) that emerge as important across most projects and stages, implying future worthwhile research directions for both researchers and practitioners.

In recent years Open Innovation (OI) has gained much attention and made firms aware that they need to consider the open environment surrounding them. To facilitate this shift Requirements Engineering (RE) needs to be adapted in order to manage the increase and complexity of new requirements sources as well as networks of stakeholders. In response we build on and advance an earlier proposed software engineering framework for fostering OI, focusing on stakeholder management, when to open up, and prioritization and release planning. Literature in open source RE is contrasted against recent findings of OI in software engineering to establish a current view of the area. Based on the synthesized findings we propose a research agenda within the areas under focus, along with a framing-model to help researchers frame and break down their research questions to consider the different angles implied by the OI model.