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An approach to clone detection in sequence diagrams and its application to security analysis.

Authors :
Alalfi, Manar H.
Antony, Elizabeth P.
Cordy, James R.
Source :
Software & Systems Modeling; Oct2018, Vol. 17 Issue 4, p1287-1309, 23p
Publication Year :
2018

Abstract

Duplication in software systems is an important issue in software quality assurance. While many methods for software clone detection in source code and structural models have been described in the literature, little has been done on similarity in the dynamic behaviour of interactive systems. In this paper, we present an approach to identifying near-miss interaction clones in reverse-engineered UML sequence diagrams. Our goal is to identify patterns of interaction (“conversations”) that can be used to characterize and abstract the run-time behaviour of web applications and other interactive systems. In order to leverage existing robust near-miss code clone technology, our approach is text-based, working on the level of XMI, the standard interchange serialization for UML. Clone detection in UML behavioural models, such as sequence diagrams, presents a number of challenges—first, it is not clear how to break a continuous stream of interaction between lifelines (representing the objects or actors in the system) into meaningful conversational units. Second, unlike programming languages, the XMI text representation for UML is highly non-local, using attributes to reference-related elements in the model file remotely. In this work, we use a set of contextualizing source transformations on the XMI text representation to localize related elements, exposing the hidden hierarchical structure of the model and allowing us to granularize behavioural interactions into conversational units. Then we adapt NICAD, a robust near-miss code clone detection tool, to help us identify conversational clones in reverse-engineered behavioural models. These conversational clones are then analysed to find worrisome interactions that may indicate security access violations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16191366
Volume :
17
Issue :
4
Database :
Complementary Index
Journal :
Software & Systems Modeling
Publication Type :
Academic Journal
Accession number :
131641285
Full Text :
https://doi.org/10.1007/s10270-016-0557-6