Extracting Domain Ontologies from Domain Specific APIs

Abstract Domain specific APIs offer their clients ready-to-use implementations of domain concepts. Beside being interfaces between the worlds of humans and computers, domain specific APIs contain a considerable amount of domain knowledge. Due to the big abstraction gap between the real world and today's programming languages, in addition to the knowledge about their domain, these APIs are cluttered with a considerable amount of noise in form of implementation detail. Furthermore, an API offers a particular view on its domain and different APIs regard their domains from different perspectives. In this paper we propose an approach for building domain ontologies by identifying commonalities between domain specific APIs that target the same domain. Besides our ontology extraction algorithm, we present a methodology for eliminating the noise and we sketch possible usage-scenarios of the ontologies for program analysis and understanding. We evaluate our approach through a set of case-studies on extracting domain ontologies from well-known domain specific APIs

Feature Profiling for Evolving Systems

sion focuses on understanding the inner workings of software systems. However, for many software maintenance tasks, not only a sound understanding of a system’s implementation but also comprehensive and accurate information about the way users actually use a system’s features is of crucial importance. Such information e. g., helps to determine the impact that a specific change has on the users of a system. In practice, however, this information is often not available. We propose an approach called feature profiling as a means to efficiently gather usage information to support maintenance tasks that affect the user interface of a software system. Furthermore, we present tool support for feature profiling and report on a case study in the insurance domain. In this study, we profiled the features of an application that is used by 150 users in 10 countries over a period of five months. Keywords-Usage Analysis, Software Maintenance I

A system for seamless abstraction layers for model-based development of embedded software

Abstract: Model-based development aims at reducing the complexity of software development by the pervasive use of adequate models throughout the whole development process starting from early phases up to implementation. In this paper we present a conceptual framework to holistically classify developed models along different levels of abstraction. We do this by defining adequate abstractions for different development stages while ignoring the information that is not relevant at a particular development step or for a certain stakeholder. The abstraction is achieved in terms of the granularity level of the system under study (e. g. system, sub-system, sub-sub-system) and in terms of the information that the models contain (e. g. specification of functionality, description of architecture, deployment on specific hardware). We also present the relation between models that describe different perspectives of the system or are at different granularity levels. However, we do not address the process to be followed for building these models.