Motivation, Design, and Ubiquity: A Discussion of Research Ethics and Computer Science

Modern society is permeated with computers, and the software that controls them can have latent, long-term, and immediate effects that reach far beyond the actual users of these systems. This places researchers in Computer Science and Software Engineering in a critical position of influence and responsibility, more than any other field because computer systems are vital research tools for other disciplines. This essay presents several key ethical concerns and responsibilities relating to research in computing. The goal is to promote awareness and discussion of ethical issues among computer science researchers. A hypothetical case study is provided, along with questions for reflection and discussion.Comment: Written as central essay for the Computer Science module of the LANGURE model curriculum in Research Ethic

Towards a Structural Equation Model of Open Source Blockchain Software Health

The widespread use of GitHub among software developers as a communal platform for coordinating software development has led to an abundant supply of publicly accessible data. Ever since the inception of Bitcoin, blockchain teams have incorporated the concept of open source code as a fundamental principle, thus making the majority of blockchain-based projects' code and version control data available for analysis. We define health in open source software projects to be a combination of the concepts of sustainability, robustness, and niche occupation. Sustainability is further divided into interest and engagement. This work uses exploratory factor analysis to identify latent constructs that are representative of general public interest or popularity in software, and software robustness within open source blockchain projects. We find that interest is a combination of stars, forks, and text mentions in the GitHub repository, while a second factor for robustness is composed of a criticality score, time since last updated, numerical rank, and geographic distribution. Cross validation of the dataset is carried out with good support for the model. A structural model of software health is proposed such that general interest positively influences developer engagement, which, in turn, positively predicts software robustness. The implications of structural equation modelling in the context of software engineering and next steps are discussed.Comment: 26 pages, 6 figure

The RISCOSS platform for risk management in open source software adoption

Managing risks related to OSS adoption is a must for organizations that need to smoothly integrate OSS-related practices in their development processes. Adequate tool support may pave the road to effective risk management and ensure the sustainability of such activity. In this paper, we present the RISCOSS platform for managing risks in OSS adoption. RISCOSS builds upon a highly configurable data model that allows customization to several types of scopes. It implements two different working modes: exploration, where the impact of decisions may be assessed before making them; and continuous assessment, where risk variables (and their possible consequences on business goals) are continuously monitored and reported to decision-makers. The blackboard-oriented architecture of the platform defines several interfaces for the identified techniques, allowing new techniques to be plugged in.Peer ReviewedPostprint (author’s final draft

QuESo: A quality model for open source software ecosystems

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Open source software has witnessed an exponential growth in the last two decades and it is playing an increasingly important role in many companies and organizations leading to the formation of open source software ecosystems. In this paper we present a quality model that will allow the evaluation of those ecosystems in terms of their relevant quality characteristics such as health or activeness. To design this quality model we started by analysing the quality measures found during the execution of a systematic literature review on open source software ecosystems and, then, we classified and reorganized the set of measures in order to build a solid quality model.Peer ReviewedPostprint (author's final draft

Open source software ecosystems quality analysis from data sources

Background: Open source software (OSS) and software ecosystems (SECOs) are two consolidated research areas in software engineering. The adoption of OSS by firms, governments, researchers and practitioners has been increasing rapidly in the last decades, and in consequence, they find themselves in a new kind of ecosystem composed by software communities,foundations, developers and partners, namely Open Source Software Ecosystem (OSSECO). In order to perform a systematic quality evaluation of a SECO, it is necessary to define certain types of concrete elements. This means that measures and evaluations should be described (e.g., through thresholds or expert judgment). The quality evaluation of an OSSECO may serve several purposes, for example: adopters of the products of the OSSECO may want to know about the liveliness of the OSSECO (e.g., recent updates); software developers may want to know about the activeness (e.g., how many collaborators are involved and how active they are); and the OSSECO community itself to know about the OSSECO health (e.g., evolving in the right direction). However, the current approaches for evaluating software quality (even those specific for open source software) do not cover all the aspects relevant in an OSSECO from an ecosystem perspective. Goal: The main goal of this PhD thesis is to support the OSSECO quality evaluation by designing a framework that supports the quality evaluation of OSSECOs. Methods: To accomplish this goal, we have used and approach based on design science methodology by Wieringa [1] and the characterization of software engineering proposed by M. Shaw [2], in order to produce a set of artefacts to contribute in thequality evaluation of OSSECOs and to learn about the effects of using these artefacts in practice. Results: We have conducted a systematic mapping to characterize OSSECOs and designed the QuESo framework (a framework to evaluate the OSSECO quality) composed by three artifacts: (i) QuESo-model, a quality model for OSSECOs; (ii) QuESoprocess, a process for conducting OSSECO quality evaluations using the QuESo-model; and (iii) QuESo-tool, a software component to support semi-automatic quality evaluation of OSSECOs. Furthermore, this framework has been validated with a case study on Eclipse. Conclusions: This thesis has contributed to increase the knowledge and understanding of OSSECOs, and to support the qualityevaluation of OSSECOs. [ntecedentes: el software de código abierto (OSS, por sus siglas en inglés) y los ecosistemas de software (SECOs, por sus siglas en inglés) son dos áreas de investigación consolidadas en ingeniería de software. La adopción de OSS por parte de empresas, gobiernos, investigadores y profesionales se ha incrementado rápidamente en las últimas décadas, y, en consecuencia, todos ellos hacen parte de un nuevo tipo de ecosistema formado por comunidades de software, fundaciones, desarrolladores y socios denominado ecosistema de software de código abierto. (OSSECO, por sus siglas en inglés)). Para realizar una evaluación sistemática de la calidad de un SECO, es necesario definir ciertos tipos de elementos concretos. Esto significa que tanto las métricas como las evaluaciones deben ser descritos (por ejemplo, a través de datos históricos o el conocimiento de expertos). La evaluación de la calidad de un OSSECO puede ser de utilidad desde diferentes perspectivas, por ejemplo: los que adoptan los productos del OSSECO pueden querer conocer la vitalidad del OSSECO (por ejemplo, el número de actualizaciones recientes); los desarrolladores de software pueden querer saber sobre la actividad del OSSECO (por ejemplo, cuántos colaboradores están involucrados y qué tan activos son); incluso la propia comunidad del OSSECO para conocer el estado de salud del OSSECO (por ejemplo, si está evolucionando en la dirección correcta). Sin embargo, los enfoques actuales para evaluar la calidad del software (incluso aquellos específicos para el software de código abierto) no cubren todos los aspectos relevantes en un OSSECO desde una perspectiva ecosistémica. Objetivo: El objetivo principal de esta tesis doctoral es apoyar la evaluación de la calidad de OSSECO mediante el diseño de un marco de trabajo que ayude a la evaluación de la calidad de un OSSECO. Métodos: Para lograr este objetivo, hemos utilizado un enfoque basado en la metodología design science propuesta por Wieringa [1]. Adicionalmente, nos hemos basado en la caracterización de la ingeniería de software propuesta por M. Shaw [2], con el fin de construir un conjunto de artefactos que contribuyan en la evaluación de la calidad de un OSSECO y para conocer los efectos del uso de estos artefactos en la práctica. Resultados: Hemos realizado un mapeo sistemático para caracterizar los OSSECOs y hemos diseñado el marco de trabajo denominado QuESo (es un marco de trabajo para evaluar la calidad de los OSSECOs). QuESo a su vez está compuesto por tres artefactos: (i) QuESo-model, un modelo de calidad para OSSECOs; (ii) QuESo-process, un proceso para llevar a cabo las evaluaciones de calidad de OSSECOs utilizando el modelo QuESo; y (iii) QuESo-tool, un conjunto de componentes de software que apoyan la evaluación de calidad de los OSSECOs de manera semiautomática. QuESo ha sido validado con un estudio de caso sobre Eclipse. Conclusiones: esta tesis ha contribuido a aumentar el conocimiento y la comprensión de los OSSECOs, y tambien ha apoyado la evaluación de la calidad de los OSSECOsPostprint (published version

Open source software ecosystems quality analysis from data sources

Background: Open source software (OSS) and software ecosystems (SECOs) are two consolidated research areas in software engineering. The adoption of OSS by firms, governments, researchers and practitioners has been increasing rapidly in the last decades, and in consequence, they find themselves in a new kind of ecosystem composed by software communities,foundations, developers and partners, namely Open Source Software Ecosystem (OSSECO). In order to perform a systematic quality evaluation of a SECO, it is necessary to define certain types of concrete elements. This means that measures and evaluations should be described (e.g., through thresholds or expert judgment). The quality evaluation of an OSSECO may serve several purposes, for example: adopters of the products of the OSSECO may want to know about the liveliness of the OSSECO (e.g., recent updates); software developers may want to know about the activeness (e.g., how many collaborators are involved and how active they are); and the OSSECO community itself to know about the OSSECO health (e.g., evolving in the right direction). However, the current approaches for evaluating software quality (even those specific for open source software) do not cover all the aspects relevant in an OSSECO from an ecosystem perspective. Goal: The main goal of this PhD thesis is to support the OSSECO quality evaluation by designing a framework that supports the quality evaluation of OSSECOs. Methods: To accomplish this goal, we have used and approach based on design science methodology by Wieringa [1] and the characterization of software engineering proposed by M. Shaw [2], in order to produce a set of artefacts to contribute in thequality evaluation of OSSECOs and to learn about the effects of using these artefacts in practice. Results: We have conducted a systematic mapping to characterize OSSECOs and designed the QuESo framework (a framework to evaluate the OSSECO quality) composed by three artifacts: (i) QuESo-model, a quality model for OSSECOs; (ii) QuESoprocess, a process for conducting OSSECO quality evaluations using the QuESo-model; and (iii) QuESo-tool, a software component to support semi-automatic quality evaluation of OSSECOs. Furthermore, this framework has been validated with a case study on Eclipse. Conclusions: This thesis has contributed to increase the knowledge and understanding of OSSECOs, and to support the qualityevaluation of OSSECOs. [ntecedentes: el software de código abierto (OSS, por sus siglas en inglés) y los ecosistemas de software (SECOs, por sus siglas en inglés) son dos áreas de investigación consolidadas en ingeniería de software. La adopción de OSS por parte de empresas, gobiernos, investigadores y profesionales se ha incrementado rápidamente en las últimas décadas, y, en consecuencia, todos ellos hacen parte de un nuevo tipo de ecosistema formado por comunidades de software, fundaciones, desarrolladores y socios denominado ecosistema de software de código abierto. (OSSECO, por sus siglas en inglés)). Para realizar una evaluación sistemática de la calidad de un SECO, es necesario definir ciertos tipos de elementos concretos. Esto significa que tanto las métricas como las evaluaciones deben ser descritos (por ejemplo, a través de datos históricos o el conocimiento de expertos). La evaluación de la calidad de un OSSECO puede ser de utilidad desde diferentes perspectivas, por ejemplo: los que adoptan los productos del OSSECO pueden querer conocer la vitalidad del OSSECO (por ejemplo, el número de actualizaciones recientes); los desarrolladores de software pueden querer saber sobre la actividad del OSSECO (por ejemplo, cuántos colaboradores están involucrados y qué tan activos son); incluso la propia comunidad del OSSECO para conocer el estado de salud del OSSECO (por ejemplo, si está evolucionando en la dirección correcta). Sin embargo, los enfoques actuales para evaluar la calidad del software (incluso aquellos específicos para el software de código abierto) no cubren todos los aspectos relevantes en un OSSECO desde una perspectiva ecosistémica. Objetivo: El objetivo principal de esta tesis doctoral es apoyar la evaluación de la calidad de OSSECO mediante el diseño de un marco de trabajo que ayude a la evaluación de la calidad de un OSSECO. Métodos: Para lograr este objetivo, hemos utilizado un enfoque basado en la metodología design science propuesta por Wieringa [1]. Adicionalmente, nos hemos basado en la caracterización de la ingeniería de software propuesta por M. Shaw [2], con el fin de construir un conjunto de artefactos que contribuyan en la evaluación de la calidad de un OSSECO y para conocer los efectos del uso de estos artefactos en la práctica. Resultados: Hemos realizado un mapeo sistemático para caracterizar los OSSECOs y hemos diseñado el marco de trabajo denominado QuESo (es un marco de trabajo para evaluar la calidad de los OSSECOs). QuESo a su vez está compuesto por tres artefactos: (i) QuESo-model, un modelo de calidad para OSSECOs; (ii) QuESo-process, un proceso para llevar a cabo las evaluaciones de calidad de OSSECOs utilizando el modelo QuESo; y (iii) QuESo-tool, un conjunto de componentes de software que apoyan la evaluación de calidad de los OSSECOs de manera semiautomática. QuESo ha sido validado con un estudio de caso sobre Eclipse. Conclusiones: esta tesis ha contribuido a aumentar el conocimiento y la comprensión de los OSSECOs, y tambien ha apoyado la evaluación de la calidad de los OSSECO

Measuring and promoting the success of an Open Science discovery platform through “compass indicators”:the GoTriple case

Previous research on indicators for measuring the success of Open Science tends to operate at a macro/global level and very rarely addresses the need to measure success at the level of a single project. However, this previous research has the merit of arguing for the definition of indicators that offer an alternative to more traditional bibliometric measures or indicators that focus on mere performance. This paper is the outcome of work conducted for a specific project that aims to build a discovery platform for social sciences and humanities, the platform GoTriple. GoTriple is designed taking inspiration from Open Science principles and has been built through a user-centered approach. The paper details the practice-led work conducted by the GoTriple team for assessing the meaning of the term success for the project and to identify indicators. To this end, this paper proposes the concept of compass indicators and presents how the project team arrived at the definition of this concept. The paper also highlights a distinction between compass indicators, which are modest measures, and key performance indicators, which tend to be tied up with measurable objectives. Compass indicators are defined as indicators that do not aim to achieve a specified numerical target of success but rather explain the journey of a project toward achieving certain desirable outcomes and offer insights to take action. Compass indicators defined for the project embrace areas such as diversity, inclusivity, collaboration, and the general use of the platform. In the final discussion, the paper offers reflections on the potential relevance of the notion of compass indicators and closes with a discussion of the next steps for this work

Trust and Reputation for Successful Software Self-Organisation

Abstract An increasing number of dynamic software evolution approaches is com- monly based on integrating or utilising new pieces of software. This requires reso- lution of issues such as ensuring awareness of newly available software pieces and selection of most appropriate software pieces to use. Other chapters in this book dis- cuss dynamic software evolution focusing primarily on awareness, integration and utilisation of new software pieces, paying less attention on how selection among different software pieces is made. The selection issue is quite important since in the increasingly dynamic software world quite a few new software pieces occur over time, some of which being of lower utility, lower quality or even potentially harmful and malicious (for example, a new piece of software may contain hidden spyware or it may be a virus). In this chapter, we describe how computational trust and reputation can be used to avoid choosing new pieces of software that may be malicious or of lower quality. We start by describing computational models of trust and reputation and subsequently we apply them in two application domains. Firstly, in quality assessment of open source software, discussing the case where different trustors have different understandings of trust and trust estimation methods. Sec- ondly, in protection of open collaborative software, such as Wikipedia

An Event-based Analysis Framework for Open Source Software Development Projects

The increasing popularity and success of Open Source Software (OSS) development projects has drawn significant attention of academics and open source participants over the last two decades. As one of the key areas in OSS research, assessing and predicting OSS performance is of great value to both OSS communities and organizations who are interested in investing in OSS projects. Most existing research, however, has considered OSS project performance as the outcome of static cross-sectional factors such as number of developers, project activity level, and license choice. While variance studies can identify some predictors of project outcomes, they tend to neglect the actual process of development. Without a closer examination of how events occur, an understanding of OSS projects is incomplete. This dissertation aims to combine both process and variance strategy, to investigate how OSS projects change over time through their development processes; and to explore how these changes affect project performance. I design, instantiate, and evaluate a framework and an artifact, EventMiner, to analyze OSS projects’ evolution through development activities. This framework integrates concepts from various theories such as distributed cognition (DCog) and complexity theory, applying data mining techniques such as decision trees, motif analysis, and hidden Markov modeling to automatically analyze and interpret the trace data of 103 OSS projects from an open source repository. The results support the construction of process theories on OSS development. The study contributes to literature in DCog, design routines, OSS development, and OSS performance. The resulting framework allows OSS researchers who are interested in OSS development processes to share and reuse data and data analysis processes in an open-source manner