Traceability in Software Engineering - Past, Present and Future

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.

Call for Papers: International Workshop on Semantic Technologies in System Maintenance (STSM 2008)

Together with Jürgen Rilling, Dragan Gaševi?, and Jeff Z. Pan I'm organizing the first International Workshop on Semantic Technologies in System Maintenance (STSM 2008), which will be co-located with the 16th IEEE International Conference on Program Comprehension (ICPC 2008) in Amsterdam, The Netherlands.

Detailed information on the workshop, submission guidelines, and other news are now available from the workshop's webpage.

Workshop on Semantic Technologies in System Maintenance at ICPC 2008

It's official: I'm co-organizing the (first) International Workshop on Semantic Technologies in System Maintenance (STSM) at the next IEEE International Conference on Program Comprehension (ICPC 2008) in Amsterdam, The Netherlands. Some preliminary information are available on the ICPC website. A call for papers and more details are coming soon!

A Unified Ontology-Based Process Model for Software Maintenance and Comprehension

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.

An Ontological Software Comprehension Process Model

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

An Ontology-based Approach for the Recovery of Traceability Links

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.

Ontology-based Program Comprehension Tool Supporting Website Architectural Evolution

Abstract

A challenge of existing program comprehension approaches is to provide consistent and flexible representations for software systems. Maintainers have to match their mental models with the different representations these tools provide. In this paper, we present a novel approach that addresses this issue by providing a consistent ontological representation for both source code and documentation. The ontological representation unifies information from various sources, and therefore reduces the maintainers’ comprehension efforts. In addition, representing software artifacts in a formal ontology enables maintainers to formulate hypotheses about various properties of software systems. These hypotheses can be validated through an iterative exploration of information derived by our ontology inference engine. The implementation of our approach is presented in detail, and a case study is provided to demonstrate the applicability of our approach during the architectural evolution of a website content management system.

Keywords: Program Comprehension, Software Evolution, Ontology, Automated Reasoning

Tutorial: Applications for the Semantic Web

Description

The Semantic Web vision is considered the next generation of the Web that enables sharing data, resources and knowledge between parties that belong to different organizations, different cultures, and/or different communities. Ontologies and rules play the main role in the Semantic Web for publishing community vocabularies and policies, for annotating resources and for turning Web applications into inference-enabled collaboration platforms. After a short introduction into the basic concepts, standards, and tools of the Semantic Web, we present how today's Semantic Web tools, languages, and techniques can be used in various application. We first start from the use of the Semantic Web technologies for providing online educators with feedback about how their students use online courses in learning management systems. Next, we demonstrate the use of the Semantic Web technologies and text mining techniques to improve software development process and software maintenance. Finally, we explain the use of the Semantic Web technologies in multimedia-enhanced applications.

Tutorial: Introduction to Text Mining

Tutorial Description

Do you have a lack of information? Or do you rather feel overwhelmed by the sheer amount of (online) available content, like emails, news, web pages, and electronic documents? The rather young field of Text Mining developed from the observation that most knowledge today - more than 80% of the data stored in databases - is hidden within documents written in natural languages and thus cannot be automatically processed by traditional information systems.

Text Mining, "also known as intelligent text analysis, text data mining or knowledge-discovery in text (KDT), refers generally to the process of extracting interesting and non-trivial information and knowledge from unstructured text." Text Mining is a highly interdisciplinary field, drawing on foundations and technologies from fields like computational linguistics, database systems, and artificial intelligence, but applying these in new and often unconventional ways.

Text Mining: Wissensgewinnung aus natürlichsprachigen Dokumenten

(This webpage is about a technical report on Text Mining, written in German. Try Google Translate for an English version.)
Text Mining Bericht Titelseite

Interner Bericht 2006-5, Fakultät für Informatik, Universität Karlsruhe (TH), Germany

Herausgegeben von René Witte und Jutta Mülle

ISSN 1432-7864

200 Seiten, 75 Abbildungen

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