Generation and Evaluation of Business Continuity Processes using Algebraic Graph Transformation and the mCRL2 Process Algebra.
Saved in:
| Title: | Generation and Evaluation of Business Continuity Processes using Algebraic Graph Transformation and the mCRL2 Process Algebra. |
|---|---|
| Authors: | Brandt, Christoph1 christoph.brandt@uni.lu, Hermann, Frank2 frank@cs.tu-berlin.de, Groote, Jan Friso3 J.F.Groote@tue.nl |
| Source: | Journal of Research & Practice in Information Technology. Feb2011, Vol. 43 Issue 1, p65-85. 21p. |
| Subjects: | BPEL (Computer program language), Programming languages, Credit Suisse AG, Software engineering, Computer software |
| Abstract: | Critical business processes can fail. Therefore, continuity processes are needed as back-up solutions. Today, those continuity processes are set up and maintained manually. They are mostly based on best practices that focus on specific continuity scenarios. Nevertheless, failures can occur in new and unforeseen combinations. As a consequence, a given business continuity plan needs to handle such situations as well. For this purpose, we present a technique for the generation and validation of the universe of continuity processes given a critical business process at Credit Suisse. The presented approach uses a combination of formal methods in the area of algebraic graph transformation and process algebra encompassing modal logic. The overall approach prepares for a sound evaluation of the effectiveness and efficiency of such plans. It uses formal tools, not standard software engineering solutions, to benefit from formal guarantees that facilitate the implementation of local and global security requirements. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Research & Practice in Information Technology is the property of Australian Computer Society Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!