Model generation for legacy systems

Hardi Hungar, Tiziana Margaria, Bernhard Steffen

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

We propose the use of (semi-) automatically extrapolated models as a means for coping with legacy systems: a focused way of testing systems for their behavioral properties allows the construction of expressive behavioral hypothesis models, and therefore extends the range of formal methods to 'black box' scenarios, which are dominant in industrial practice. Keeping these models up to date by continuous adaptation may provide an ideal way for controlling the evolution of large systems during their whole life cycles. Bottleneck of this approach is the size of the extrapolated models: particularly for distributed systems the state explosion problem strikes back. This paper focusses on a particularly promising cure: view-oriented model construction allows a new way of size control that complements other powerful techniques, which together have the potential to scale to systems of realistic size. This is illustrated by considering small instance views in the context of Computer Telephony Integrated Systems.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMartin Wirsing, Alexander Knapp, Simonetta Balsamo
PublisherSpringer Verlag
Pages167-183
Number of pages17
ISBN (Print)3540211799, 9783540211792
DOIs
Publication statusPublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2941
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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