Enhancing Software Project Outcomes: Using Machine Learning and Open Source Data to Employ Software Project Performance Determinants

Many factors can influence the ongoing management and execution of technology projects. Some of these elements are known a priori during the project planning phase. Others require real-time data gathering and analysis throughout the lifetime of a project. These real-time project data elements are often neglected, misclassified, or otherwise misinterpreted during the project execution phase resulting in increased risk of delays, quality issues, and missed business opportunities. The overarching motivation for this research endeavor is to offer reliable improvements in software technology management and delivery. The primary purpose is to discover and analyze the impact, role, and level of influence of various project related data on the ongoing management of technology projects. The study leverages open source data regarding software performance attributes. The goal is to temper the subjectivity currently used by project managers (PMs) with quantifiable measures when assessing project execution progress. Modern-day PMs who manage software development projects are charged with an arduous task. Often, they obtain their inputs from technical leads who tend to be significantly more technical. When assessing software projects, PMs perform their role subject to the limitations of their capabilities and competencies. PMs are required to contend with the stresses of the business environment, the policies, and procedures dictated by their organizations, and resource constraints. The second purpose of this research study is to propose methods by which conventional project assessment processes can be enhanced using quantitative methods that utilize real-time project execution data. Transferability of academic research to industry application is specifically addressed vis-à-vis a delivery framework to provide meaningful data to industry practitioners

Modeling the Effects of Diversity and Corporations on Participation Dynamics in FLOSS Ecosystems

A multitude of societal issues associated with the development of technology have emerged over the years including, but not limited to: insufficient personnel for maintenance; a lack of accessibility; the spread of harmful tools; and bias and discrimination against marginalized groups. I propose that a systems perspective is necessary to identify potential leverage points in technology production systems to influence them towards increased social good and evaluate their effectiveness for intervention. Toward this end, I conducted a mixed-methods study of a widely-adopted approach in tech production, free/libre and open source software (FLOSS) development. A survey was distributed to elicit responses from FLOSS project contributors to characterize their perceptions of diversity and corporate involvement as they relate to participation decisions and information gathering activities in online platforms. To complement this, an analysis of data from FLOSS projects on GitHub was completed to model participation dynamics. Survey results indicate that contributors attend to information that is used to infer group diversity and information about corporate decision making related to FLOSS systems. Furthermore, the influence of this information on participation decisions varies on the basis of economic needs and sociopolitical beliefs. Analyses of eighteen project ecosystems, with over 9,000 contributors, reveal that projects with no to some corporate involvement generally have broader contributor and user bases than those that are owned by a company. Taken together, these findings suggest that the internal practices of companies involved in FLOSS can be perceived as opaque and controlling which is detrimental to both the expansion of a project\u27s contributor base and for increasing diversity across FLOSS ecosystems. This research highlights the need to differentiate projects on the basis of corporate involvement and community ethos to design appropriate interventions. A set of recommendations and research propositions are offered to improve inclusivity, equity, and sustainability in tech development

Factors Influencing Participant Satisfaction with Free/Libre and Open Source Software Projects

The purpose of this research was to identify factors that affect participants’ satisfaction with their experience of a free/libre open source software (FLOSS) project. The research built on existing models of user satisfaction from the information systems literature, and also incorporated two characteristics of FLOSS projects first identified by Ye, Nakakoji, Yamamoto, and Kishida (2005), product openness and process openness. The central research question it answered was, What factors influence participant satisfaction with a free/libre and open source application software project? Richard Stallman’s reasons for setting up the GNU project and the Free Software Foundation arose from his frustration at being forced to be a passive user of software used for a Xerox printer. These suggest that being able to be an active participant in a FLOSS project is one factor that should be examined, and therefore the first sub-question this project answers is, What types of contributions do participants make to free/libre and open source software projects? Several studies have shown that the extent of participation in a FLOSS project varies from individual to individual, and this variation leads to the second sub-question, Do the factors that influence satisfaction vary for different types of participation? If so, in what way? A preliminary conceptual model of factors affecting participant satisfaction was developed, reflecting the key concepts identified in the literature. The main theoretical goal of this research was to test the model using empirical data. The research used a sequential, mixed methods approach. The first, qualitative stage involved reviewing documents from selected projects and interviewing a purposive sample of FLOSS project participants. The second, quantitative stage involved an online survey of FLOSS project participants, and the data gathered were used to test the conceptual model. The results of the first stage showed that participation in FLOSS projects was a more complex construct than previously reported in the literature. Seven distinct categories of activities were identified: • use; • interaction with code; • supporting the community; • outreach; • sponsorship; • management; and • governance. Four attributes that modified these categories were also identified: organisational focus, role formality, remuneration, and time commitment. Data from 154 responses to the online survey were used to test the model using stepwise multiple regression, which determined the effect of each of the variables on overall participant satisfaction. Moderated regression analysis was used to test the effects of three potential moderating variables. The results showed that that perceived system complexity had the largest effect, decreasing satisfaction if respondents perceived that the software was complex, while project openness and perceived developer communication quality accounted for the most variance in satisfaction. The main theoretical contribution of this research lies in its extension of satisfaction studies to FLOSS communities, showing that communication and openness are more important than in conventional software projects. Its practical contribution will help people involved in the management and governance of FLOSS projects to identify ways of increasing their participants’ satisfaction, which may in turn encourage them to contribute more

Understanding contributor behaviour within Free/Libre/Open Source Software communities: A socialization perspective

Attracting a large number of new contributors has been seen as a way to ensure the survival, long-term success, and sustainability of Free/Libre/Open Source Software (FLOSS) communities. However, this appears to be a necessary, but not a sufficient condition, as the well-being of FLOSS communities also relies on members performing behaviours that nurture and protect the community. Despite a large body of research on FLOSS communities, few studies have been undertaken to explore the influence of a participant’s socialization experience on their contribution behaviour. In addition, there has been relatively little research that has adopted a community-level view of FLOSS community participants’ contribution that goes beyond the mere notion of writing lines of code. The purpose of this study is to develop and rigorously test a socialization model that predicts contributor behaviour in the FLOSS community context. Drawing upon theories of socialization and citizenship behaviours from organizational behaviour research, this research develops and tests two separate but related research models. The first model proposes the direct impact of socialization factors on two performance-related dependent variables: task performance and community citizenship behaviours. The second model hypothesizes a mediating effect of two proximal socialization variables, social identification and social integration, between the socialization factors and the dependent variables. An exploratory study involving eleven FLOSS community leaders, managers, and experienced members was first conducted, to investigate the key variables that characterize FLOSS community newcomer socialization experience as well as the various instances of citizenship behaviours that are specific to the FLOSS community context. The analysis of the interview data revealed the existence of six socialization variables: task segregation, task purposefulness, interaction intensity, mentoring, joining structuredness, and supportiveness. Two sets of FLOSS community citizenship behaviours (CCB) were identified drawing on the citizenship behaviour literature. The first set, labelled CCB-I, comprised citizenship behaviours directed towards the benefit of individuals. The second set, CCB-P, included citizenship behaviours directed towards the benefit of the project. The findings were integrated in the two conceptual models. Subsequently, a research instrument was developed, following an extensive purification process that consisted of card sorting and expert review rounds, and a survey pretest. A pilot study assessed responses from 46 FLOSS contributors from two large FLOSS communities. Overall, the scales demonstrated high reliability and showed adequate construct validity. The analysis of the pilot study suggested the existence of a third CCB dimension, named CCB-C, that characterizes citizenship behaviours that are oriented towards the benefit of a project’s community. The main study was based on an online survey involving 327 respondents from twelve large FLOSS communities. Using Partial Least Squares (PLS), the collected data was used to test the two models. The results showed the overall superior predictive capability of the model hypothesizing the mediating effect of both social identification and social integration. Task performance was found to be directly predicted by task purposefulness as well as by interaction intensity and supportiveness through the mediation of social identification. Meanwhile, CCB was found to be impacted by the direct effect of task segregation and task purposefulness, and by interaction intensity and supportiveness through the mediation of both social identification and social integration. The existence of the third CCB dimension, CCB-C, was confirmed

The Validity of the General Intellectual Humility Scale as a Measure of Intellectual Humility

Early intellectual humility research has largely relied on questionnaires that require individuals to self-evaluate their own intellectual humility, despite concerns that people low in intellectual humility may lack awareness of their degree of intellectual humility. Because of this potential source of error, it is important that self-report measures of intellectual humility are thoroughly tested for validity. In Chapter 1, I conducted a systematic literature review of measures of intellectual humility. For each measure, validity evidence is summarized and critically evaluated. Validity evidence was found lacking with respect to addressing potentially serious problems with self-report. This finding points to a need for additional validity testing for self-report measures of intellectual humility. In Chapter 2, I conducted a set of pointed tests of validity for one such measure, the General Intellectual Humility Scale (GIHS). In a sample recruited from Prolific (N = 481), GIHS scores were weakly associated with or unassociated with endorsement of epistemically unwarranted beliefs, unassociated with endorsing such beliefs as certainly true, and unassociated with endorsing such beliefs despite claiming to have carefully researched the issue. Additionally, GIHS scores predicted greater bias blind spot, and this effect remained significant when controlling for science intelligence. Finally, GIHS scores predicted belief in anthropogenic global warming when controlling for political orientation but did not attenuate political polarization about global warming. I argue that these findings are clear departures from theory yet are consistent with suspected problems with direct self-report. I conclude by discussing limitations and implications for future research

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