Hideyuki Kanuka

AOJS: aspect-oriented javascript programming framework for web development

JavaScript is a popular scripting language that is particularly useful for client-side programming together with HTML /XML on the Web. As JavaScript programs become more complex and large, separation of concerns at the implementation level is a significant challenge. Aspect orientation has been a well known concept to realize improved separation; however, existing mechanisms require modifications in the target modules for aspect weaving in JavaScript (i.e., not complete separation). In this paper, we propose an Aspect-Oriented JavaScript framework, named AOJS, which realizes the complete separation of aspects and other core modules in JavaScript. AOJS can specify function executions, variable assignments and file initializations in JavaScript programs as the joinpoints of aspects. Moreover, AOJS guarantees the complete separation of aspects and core program modules by adopting a proxy-based architecture for aspect weaving. By utilizing these features, we confirmed that AOJS offers improved modifiability and extendability for JavaScript programming.

A Metamodel for Security and Privacy Knowledge in Cloud Services

We propose a metamodel for handling security and privacy in cloud service development and operation. The metamodel is expected to be utilized for building a knowledge base to accumulate, classify and reuse existing cloud security and privacy patterns and practices in a consistent and uniform way. Moreover the metamodel and knowledge base are expected to be utilized for designing and maintaining architectures for cloud service systems incorporating security and privacy.

Improved searchability of bug reports using content-based labeling with machine learning of sentences

Most stakeholders refer to past bug reports when they encounter a problem since bug reports contain useful information. However, searching for specific content is difficult because there are many bug reports. The desired content depends on the viewpoint of the stakeholder. A full text search includes unwanted content, which is costly. Although this problem has been previously noted, a solution has yet to be proposed. Herein we propose Content-based Labeling Method as a solution. This method organizes information in a bug report by labeling each sentence based on its contents, allowing stakeholders’ viewpoints to be considered. We evaluate the improvement in searchability. The Content-based Labeling Method improves the searchability according to the F-measure and precision of the experimental results.

Cloud Security and Privacy Metamodel - Metamodel for Security and Privacy Knowledge in Cloud Services.

Security and privacy are important in cloud services. Numerous security and privacy patterns as well as nonpattern-based knowledge such as practices and principles exist in cloud services. Selecting and combining the appropriate knowledge is difficult due to numerous options and the nature of the layered cloud stack. Herein we propose a metamodel called the Cloud Security and Privacy Metamodel (CSPM) to handle security and privacy in cloud service development and operations. CSPM can classify and support existing cloud security and privacy patterns and practices in a consistent and uniform manner. Moreover, we propose a security and privacy aware process to develop cloud system utilizing CSPM. Several case studies verify the effectiveness and usability of our approach. As a result, we confirmed effectiveness and usability of CSPM, as well as some possible future work.