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Software extensibility, the capability of adding new functions to a software system, is established based on software architecture. Therefore, developers need to evaluate the capability when designing software architecture. To support the evaluation, researchers have proposed metrics based on quality models or scenarios. However, those metrics are vague or subjective, depending on specific systems and evaluators. We propose the extensibility metric for software architecture (EMSA), which represents the degree of extensibility of a software system based on its architecture. To reduce the subjectivity of the metric, we first identify a typical task of adding new functions to a software system. Second, we define the metrics based on the characteristics of software architecture and its changes and finally combine them into a single metric. The originality of EMSA comes from defining metrics based on software architecture and extensibility tasks and integrating them into one. Furthermore, we made an effort to translate the degree into effort estimation expressed as person-hours. To evaluate EMSA, we conducted two types of user studies, obtaining measurements in both a laboratory and a real-world project. The results show that the EMSA estimation is reasonably accurate [6.6% MMRE and 100% PRED(25%)], even in a real-world project (93.2% accuracy and 8.5% standard deviation).

Program understanding can be enhanced using reverse engineering technologies. The understanding process is heavily dependent on both individuals and their specific cognitive abilities, and on the set of facilities provided by the program understanding environment. Unfortunately, most reverse engineering tools provide a fixed palette of extraction, selection, and organization techniques. This paper describes a programmable approach to reverse engineering. The approach uses a scripting language that enables users to write their own routines for common reverse engineering activities, such as graph layout, metrics, and subsystem decomposition, thereby extending the capabilities of the reverse engineering toolset to better suit their needs. A programmable environment supported by this approach subsumes existing reverse engineering systems by being able to simulate facets of each one.

The Oracle relational database management system, with object-oriented extensions and numerous application-driven enhancements, plays a critical role worldwide in managing the exploding volumes of bioinformatics data. There are many features of the Oracle product which support the bioinformatics community directly already and there are several features which could be exploited more thoroughly by users, service vendors, and Oracle itself to extend that level of support. This paper will present an overview of Oracle features which support storage of bioinformatics data and will discuss extensibility features which give the product room to grow. Some attention will be given to Oracle's own efforts to use that extensibility to exploit emerging standardization of many of the complex data and computation requirements of the life sciences.

In this paper we describe an approach to manage multimedia data in the framework of an advanced information and knowledge management system based on the terminological representation model Back. The guide-lines of the approach are based on using Back to provide conceptual descriptions of multimedia data, and on providing a multimedia object multimedia supporting all functionalities related to the physical organization. The usage of Back as conceptual tool for multimedia data has several advantages, such as adequate expressive power and reasoning capabilities. The multimedia object manager has been designed following an object-oriented approach. The main advantage is to provide extensibility, thus allowing new types of media to dynamically added to the system.