Evidence-based Software Process Recovery

Developing a large software system involves many complicated, varied, and inter-dependent tasks, and these tasks are typically implemented using a combination of defined processes, semi-automated tools, and ad hoc practices. Stakeholders in the development process --- including software developers, managers, and customers --- often want to be able to track the actual practices being employed within a project. For example, a customer may wish to be sure that the process is ISO 9000 compliant, a manager may wish to track the amount of testing that has been done in the current iteration, and a developer may wish to determine who has recently been working on a subsystem that has had several major bugs appear in it. However, extracting the software development processes from an existing project is expensive if one must rely upon manual inspection of artifacts and interviews of developers and their managers. Previously, researchers have suggested the live observation and instrumentation of a project to allow for more measurement, but this is costly, invasive, and also requires a live running project. In this work, we propose an approach that we call software process recovery that is based on after-the-fact analysis of various kinds of software development artifacts. We use a variety of supervised and unsupervised techniques from machine learning, topic analysis, natural language processing, and statistics on software repositories such as version control systems, bug trackers, and mailing list archives. We show how we can combine all of these methods to recover process signals that we map back to software development processes such as the Unified Process. The Unified Process has been visualized using a time-line view that shows effort per parallel discipline occurring across time. This visualization is called the Unified Process diagram. We use this diagram as inspiration to produce Recovered Unified Process Views (RUPV) that are a concrete version of this theoretical Unified Process diagram. We then validate these methods using case studies of multiple open source software systems

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

Creative freedom in the digital age

This thesis is particularly concerned with everyday creativity as a social practice that is taking place within the digital environment. Web 2.0 made it much easier for laypersons to produce and publish digital content and to participate in online communities. Through participation community members can acquire domain-relevant knowledge as well as develop their digital competency. In some areas, online communities of highly motivated amateurs (Pro-Ams) work to professional standards and even achieve better results than their professional colleagues. Open Source software projects or Wikis are among areas that rely on committed amateurs and the strength of a community. The empirical stage of the research comprises two studies that aim to investigate the role of ICT and the Internet in everyday creative activities and how the use of digital tools for creativity can be facilitated and improved. An exploratory online survey revealed that the majority of participants are involved in everyday creative activities many of which are performed with the use of digital tools. However, the lack of digital competency and skills has been proved to be among the main barriers to using software tools for everyday creativity and participation in the digital environment. Taking into account the survey data that revealed digital photo-editing and manipulation to be the most popular creative activity among participants, a powerful, free, image-editing program - the GIMP - was chosen for the experiment. A group of people with no professional knowledge of using image editing programs participated in a single-day workshop where they learned how to do basic image processing with a free software editor, the GIMP. Data collection methods involved questionnaires, observation and follow-up telephone interviews. The GIMP tutorial and practice session proved to be successful in engaging non-professionals in image manipulation with the GIMP and facilitating further use and learning through individual effort

Developing a Framework for Stigmergic Human Collaboration with Technology Tools: Cases in Emergency Response

Information and Communications Technologies (ICTs), particularly social media and geographic information systems (GIS), have become a transformational force in emergency response. Social media enables ad hoc collaboration, providing timely, useful information dissemination and sharing, and helping to overcome limitations of time and place. Geographic information systems increase the level of situation awareness, serving geospatial data using interactive maps, animations, and computer generated imagery derived from sophisticated global remote sensing systems. Digital workspaces bring these technologies together and contribute to meeting ad hoc and formal emergency response challenges through their affordances of situation awareness and mass collaboration. Distributed ICTs that enable ad hoc emergency response via digital workspaces have arguably made traditional top-down system deployments less relevant in certain situations, including emergency response (Merrill, 2009; Heylighen, 2007a, b). Heylighen (2014, 2007a, b) theorizes that human cognitive stigmergy explains some self-organizing characteristics of ad hoc systems. Elliott (2007) identifies cognitive stigmergy as a factor in mass collaborations supported by digital workspaces. Stigmergy, a term from biology, refers to the phenomenon of self-organizing systems with agents that coordinate via perceived changes in the environment rather than direct communication. In the present research, ad hoc emergency response is examined through the lens of human cognitive stigmergy. The basic assertion is that ICTs and stigmergy together make possible highly effective ad hoc collaborations in circumstances where more typical collaborative methods break down. The research is organized into three essays: an in-depth analysis of the development and deployment of the Ushahidi emergency response software platform, a comparison of the emergency response ICTs used for emergency response during Hurricanes Katrina and Sandy, and a process model developed from the case studies and relevant academic literature is described

Winter 2011 Vol. 12 No. 2

https://surface.syr.edu/ischool_news/1000/thumbnail.jp

Ernst Denert Award for Software Engineering 2020

This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan Brachthäuser (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha’s (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan’s (FAU Erlangen-Nürnberg) work on Open Source Software Governance, Dominic Henze’s (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess’s (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren’s (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller’s (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel’s (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter Wägemann’s (FAU Erlangen-Nürnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern’s (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris’s (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics – which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work