Bachelor Thesis BCLR-2017-51

BibliographyRadic, Marco: Transformation of TOSCA to natural language texts.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Bachelor Thesis (2017).
53 pages, english.
CR-SchemaI.2.7 (Natural Language Processing)
K.6.2 (Installation Management)
D.2.7 (Software Engineering Distribution, Maintenance, and Enhancement)
Abstract

Cloud computing changes the way businesses plan, use and manage their IT systems and resources. Different cloud providers offer distinctive interfaces for the deployment and management of applications in their respective cloud environments. The organization OASIS addresses these circumstances with the Topology and Orchestration Specification for Cloud Applications (TOSCA). This standard offers a language to express applications as directed graphs and their management behavior in a standardized and vendor-independent manner. In numerous roles in the development, a textual description of the application, its entities and their relationships, for instance to serve as textual documentation, is of use. The TOSCA standard places no restriction on the complexity of a topology graph. Therefore, a textual representation of the graph can also get arbitrarily large and complex. Additionally, every change has to be reflected in the documentation accordingly. Consequently, an automated approach to the generation of such textual representations is preferable. This work describes a concept for the automated generation of textual descriptions of TOSCA topology graphs. This is accomplished by combining typical tasks from natural language generation with domain-specific information in order to generate appropriate textual descriptions. The concept is implemented in a prototype and validated in a use-case scenario.

Full text and
other links
PDF (733439 Bytes)
Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Superviser(s)Leymann, Prof. Frank; Guth, Jasmin
Entry dateSeptember 28, 2018
   Publ. Computer Science