Software developers communicate and interact with each other in order to solve complex problems. Such communication often includes emotional displays that have been shown to influence team processes and performance. Yet, little is known about the evolution of team emotional displays. Hence, we investigate a sample of 1121 Open Source Software (OSS) projects from GitHub, using longitudinal data analysis. The results from growth curve analysis shows that the team emotional display decrease over time. This negative linear trend decelerates mid-term as suggested by a positive quadratic trend of time. Such deceleration diminishes toward the end as a negative cubic trend suggests.

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In every larger-scale endeavor, or at least in most larger-scale endeavors, there comes a time to evaluate progress, solicit opinion, ask your public, survey your customers -- in short, to find out if what you are doing is actually worth doing. In some cases, this step may be omitted, or the results ignored: it is possible that if Herman Melville had shown people Moby Dick when he was half-done with it, everyone except Nathaniel Hawthorne would have said "Er, we're not sure what this is all about. Where's the nice adventure of Omoo? Just what are you up to, Sir?" He should not have therefore ditched the manuscript and gone on to something else; also, Nathaniel Hawthorne gets 50,000 votes. However, in general, you (and I) are not Melville writing Moby Dick. Scientific projects tend to publish some papers before they are "complete" and if these are universally derided and rejected, or receive no citations, it is often the case that they are doing nothing of much interest. There are exceptions, but they are rarer, perhaps, than we might think. Most things that are ignored are ignored for a good reason.

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Technology transfer is an important form of collaboration between software engineering researchers and industrial practitioners. Despite benefits to both parties, it remains a huge challenge to carry out a technology transfer successfully. Based on the experiences at Microsoft, this talk discusses some key aspects in technology transfer, including technology readiness, partnership building, and one team as collaboration model.

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The networking of multi-physics (mechanical, electical, hydraulic, biochemical, ...) with computational systems (control systems, signal processing, logical inferencing, planning, ...) processes, interacting with often uncertain environments, with human actors, in a socio-economic context, leads to so-called Cyber-Physical Systems (CPS).

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A System-of-Systems (SoS) is a large-scale complex system that integrates multiple constituent systems, which have managerial and operational independence. In order to achieve higher-level common goals of an SoS, it is important to systematically integrate independent constituent systems by thoroughly analyzing and designing the target SoS as a whole. But before conducting these engineering activities, a number of various SoS stakeholders and engineers should be able to understand their SoS. In order to provide a holistic view as a common knowledge base, this paper focuses on developing a conceptual meta-model that represents SoS ontologies. By investigating several documents for Mass Casualty Incident (MCI) response systems, we identified essential objects and required features for SoS descriptions. Based on the investigation, we generalized the objects into SoS entities, and we develop a meta-model, called M2SoS (Meta-model for System-of-Systems). To design our M2SoS, we borrowed organizational concepts from meta-models for multi-agent systems, and entities and relationships are redefined to specify SoS concepts in M2SoS. Finally, M2SoS is analyzed with respect to SoS characteristics, and we evaluate if M2SoS can represent high-level ontologies for two SoS case scenarios.

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The Linux Kernel is one of the most successful open source projects to date. After 26 years, the rate of code contribution continues to be high, new developers are still being attracted to participating, and the code is in widespread use. By analyzing the contributions, we can see how individuals impact the kernel's evolution as a whole, as do the organizations in the kernel ecosystem. So what lessons can we learn from this information? What information is relevant to software community health in general that is not being caught in traditional health metrics? This keynote will discuss how the insights from the Linux kernel are being applied to other Linux Foundation open source projects to create healthy vibrant communities producing useful code for us all.

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