Abstract

Semantic Assistants Workflow OverviewToday's knowledge workers have to spend a large amount of time and manual effort on creating, analyzing, and modifying textual content. While more advanced semantically-oriented analysis techniques have been developed in recent years, they have not yet found their way into commonly used desktop clients, be they generic (e.g., word processors, email clients) or domain-specific (e.g., software IDEs, biological tools). Instead of forcing the user to leave his current context and use an external application, we propose a ``Semantic Assistants'' approach, where semantic analysis services relevant for the user's current task are offered directly within a desktop application. Our approach relies on an OWL ontology model for context and service information and integrates external natural language processing (NLP) pipelines through W3C Web services.

Abstract

From a maintenance perspective, only software that is well understood can evolve in a controlled and high-quality manner. Software evolution itself is a knowledge-driven process that requires the use and integration of different knowledge resources. The authors present a formal representation of an existing process model to support the evolution of software systems by representing knowledge resources and the process model using a common representation based on ontologies and description logics. This formal representation supports the use of reasoning services across different knowledge resources, allowing for the inference of explicit and implicit relations among them. Furthermore, an interactive story metaphor is introduced to guide maintainers during their software evolution activities and to model the interactions between the users, knowledge resources and process model.

Abstract

Traceability links provide support for software engineers in understanding relations and dependencies among software artefacts created during the software development process. The authors focus on re-establishing traceability links between existing source code and documentation to support software maintenance. They present a novel approach that addresses this issue by creating formal ontological representations for both documentation and source code artefacts. Their approach recovers traceability links at the semantic level, utilising structural and semantic information found in various software artefacts. These linked ontologies are supported by ontology reasoners to allow the inference of implicit relations among these software artefacts.

Abstract

Despite impressive advances in the development of generic NLP frameworks, content-specific text mining algorithms, and NLP services, little progress has been made in enhancing existing end-user clients with text analysis capabilities. To overcome this software engineering gap between desktop environments and text analysis frameworks, we developed an open service-oriented architecture, based on Semantic Web ontologies and W3C Web services, which makes it possible to easily integrate any NLP service into client applications.

Abstract

This paper gives a brief overview of the International Workshop on Semantic Technologies in System Maintenance. It describes a number of semantic technologies (e.g., ontologies, text mining, and knowledge integration techniques) and identifies diverse tasks in software maintenance where the use of semantic technologies can be beneficial, such as traceability, system comprehension, software artifact analysis, and information integration.

CASCON 2007 Workshop Report

IBM Technical Report: TR-74-211

October 25, 2007

Abstract

Many changes have occurred in software engineering research and practice since 1968, when software engineering as a research domain was established. One of these research areas is traceability, a key aspect of any engineering discipline, enables engineers to understand the relations and dependencies among various artifacts in a system.

Abstract

In this paper, we present a formal process model to support the comprehension and maintenance of software systems. The model provides a formal ontological representation that supports the use of reasoning services across different knowledge resources. In the presented approach, we employ our Description Logic knowledge base to support the maintenance process management, as well as detailed analyses among resources, e.g., the traceability between various software artifacts. The resulting unified process model provides users with active guidance in selecting and utilizing these resources that are context-sensitive to a particular comprehension task. We illustrate both, the technical foundation based on our existing SOUND environment, as well as the general objectives and goals of our process model.

Keywords: Software maintenance, process modeling, ontological reasoning, software comprehension, traceability, text mining.

Abstract

Comprehension is an essential part of software maintenance. Only software that is well understood can evolve in a controlled manner. In this paper, we present a formal process model to support the comprehension of software systems by using Ontology and Description Logic. This formal representation supports the use of reasoning services across different knowledge resources and therefore, enables us to provide users with guidance during the comprehension process that is context sensitive to their particular comprehension task.

Keywords: Software maintenance, program comprehension, process modeling, ontological reasoning

Abstract

Traceability links provide support for software engineers in understanding the relations and dependencies among software artifacts created during the software development process. In this research, we focus on re-establishing traceability links between existing source code and documentation to support reverse engineering. We present a novel approach that addresses this issue by creating formal ontological representations for both the documentation and source code artifacts.

Abstract

Comprehension is an essential part of software evolution. Only software that is well understood can evolve in a controlled manner. In this paper, we present a formal process model to support the comprehension of software systems by using Ontology and Description Logic. This formal representation supports the use of reasoning services across different knowl- edge resources and therefore, enables us to provide users with guidance during the comprehension process that is context sensitive to their particular comprehension task. As part of the process model, we also adopt a new interactive story metaphor, to represent the interactions between users and the comprehension process.

Keywords: Software evolution, program comprehension, process modeling, story metaphor, ontological reasoning