Software-Defined Networking (SDN) is attractive as an efficient and flexible networking architecture to realize automatic network management and high level services. However, users require efficient developing method and reliable software for SDN/OpenFlow. Recently, researchers in software verification started to verify correctness and security properties of networks in the SDN architecture by applying formal methods. We show the research field of SDN/OpenFlow as a new stage for applying formal methods, and discuss its problems and future works．
We introduce physiological mechanisms and characteristics of electric taste for utilizing it in gustatory media. We usually apply chemical and multimodal scientific knowledge for developing gustatory media. In addition, recent studies utilize electric taste which occurred by electrical stimulus, to evoke a gustatory sensation. Engineering researches about electric taste is still groundbreaking years, in contrast, physiological researches has been studied over 250 years. Hence physiological knowledge reference which may utilize in engineering discipline supports designing and improving interactive gustatory media. First, we introduce the mechanism and the taste quality of electric taste. After introducing the history of electrogustometry and the electrogustometer, we describe an analysis of electric taste by neuroscience. Finally, we discuss the future vision of electric taste.
The subject of applications of MDE is vast and rapidly evolving. Usually one may consider three important areas: generation of software artifacts, discovery of models from structured systems and interoperability between heterogeneous systems. As the third part of this series of tutorial, this article will show these three areas of increasing complexity are constantly evolving. Another classification of MDE applications may consider various domains like health care, military operations, automotive engineering, aeronautics, embedded systems, information systems, Web engineering, etc. We will instead take a typological approach and show how the typology of applications may be related to a classification of models and metamodels.
This paper extends our previous study (letter paper), which quantifies the difficulty of program comprehension based on brain activation measured by NIRS (Near Infra-Red Spectroscopy) during source code reading. We performed controlled experiments with 20 subjects. 3 of 20 subjects could not complete the measurement. We found that: (1) 16 of 17 shows strong brain activation during reading of obfuscated program (binomial test, p < 0.01) and (2) subjective evaluation of difficulty is correlated with brain activation (Spearman's correlation coefficient = 0.46, p < 0.01).
Live virtual machine (VM) migration (simply live migration) is a powerful tool for managing data center resources. Live migration moves a running VM between different physical machines without losing any states such as network conditions and CPU status. Live migration has attracted the attention of academic and industrial researchers since replacing running VMs inside data centers by live migration makes it easier to manage data center resources. This paper summarizes live migration basics and techniques for improving them. Specifically, this survey focuses on software mechanisms for realizing basic live migration, improving its performance, and expanding its applicability. Also, this paper shows research opportunities that the state-of-the-art live migration techniques have not covered yet.
We propose subtle foot-based gestures named foot plantar-based (FPB) gestures that are used with sock-style pressure sensors. In this system, the user can control a computing device by changing his or her foot plantar distributions, e.g., pressing the floor with his or her toe. Because such foot movement is subtle, it is suitable for use especially in a public space such as a crowded train. In this work, we focus on a user-defined gesture that is designed by the end-users, not developers of this system. We first conduct a guessability study that asks people what is the appropriate gesture for a specific command to control the computing device. Then, we implement a gesture recognizer with a machine learning technique. To avoid unexpected gesture activations, we also collect foot plantar pressure patterns made during daily activities such as walking, as negative training data. Finally, we conclude with several applications to further illustrate the utility of FPB gestures.
We introduced an interactive extension mechanism, which allows us to extend programs and systems verified with Coq. In the mechanism, only adding new constructors into existing inductive types are allowed, but adding parameters into functions or constructors are not. In this paper, we introduce a novel mechanism, which allows us to add new fields into record types. We also show the limitations of the mechanism arising from the type system of Coq. The method used in the mechanism is also applicable for adding parameters to existing constructors and functions. We explain problems occurring when we apply the method into them.
In this paper we propose a method to support Personal Software Process (PSP), which is a well known software process improvement framework for individual developers. The proposed method estimates developer's purposes (aims) from time-series data about developer's tasks, given by an execution history of software applications. We implemented the method by a machine learning algorithm, Random Forests. The experiment result shows the prediction with the time-series data is more accurate than the prediction without the time-series data. Especially, when using longer time-series data, accuracy of estimation became 97 %. It can be expected that the proposed method can help developers' process improvement as they become aware of how much time they spent on a specific aim such as implementation and testing.