Automatic generation of software behavioral models

Dynamic analysis of software systems produces behavioral models that are useful for analysis, verification and testing. The main techniques for extracting models of functional behavior generate either models of constraints on data, usually in the form of Boolean expressions, or models of interaction...

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Vydané v:2008 ACM/IEEE 30th International Conference on Software Engineering Ročník 2008; číslo 24; s. 501 - 510
Hlavní autori: Lorenzoli, D., Mariani, L., Pezze, M.
Médium: Konferenčný príspevok.. Journal Article
Jazyk:English
Vydavateľské údaje: IEEE 01.01.2008
Predmet:
Automata
Data mining
dynamic analysis
gk-tail
Informatics
Information analysis
Law
Legal factors
model synthesis
Permission
Software systems
Software testing
System testing
ISBN:1424444861, 9781424444861, 1605580791, 9781605580791
ISSN:0270-5257
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Abstract Dynamic analysis of software systems produces behavioral models that are useful for analysis, verification and testing. The main techniques for extracting models of functional behavior generate either models of constraints on data, usually in the form of Boolean expressions, or models of interactions between components, usually in the form of finite state machines. Both data and interaction models are useful for analyzing and verifying different aspects of software behavior, but none of them captures the complex interplay between data values and components interactions. Thus related analysis and testing techniques can miss important information. In this paper, we focus on the generation of models of relations between data values and component interactions, and we present GK-tail, a technique to automatically generate extended finite state machines (EFSMs) from interaction traces. EFSMs model the interplay between data values and component interactions by annotating FSM edges with conditions on data values. We show that EFSMs include details that are not captured by either Boolean expressions or (classic) FSM alone, and allow for more accurate analysis and verification than separate models, even if considered jointly.
AbstractList Dynamic analysis of software systems produces behavioral models that are useful for analysis, verification and testing. The main techniques for extracting models of functional behavior generate either models of constraints on data, usually in the form of Boolean expressions, or models of interactions between components, usually in the form of finite state machines. Both data and interaction models are useful for analyzing and verifying different aspects of software behavior, but none of them captures the complex interplay between data values and components interactions. Thus related analysis and testing techniques can miss important information. In this paper, we focus on the generation of models of relations between data values and component interactions, and we present GK-tail, a technique to automatically generate extended finite state machines (EFSMs) from interaction traces. EFSMs model the interplay between data values and component interactions by annotating FSM edges with conditions on data values. We show that EFSMs include details that are not captured by either Boolean expressions or (classic) FSM alone, and allow for more accurate analysis and verification than separate models, even if considered jointly.
Dynamic analysis of software systems produces behavioral models that are useful for analysis, verification and testing.
Author Lorenzoli, D.
Pezze, M.
Mariani, L.
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  organization: Dept. of Inf., Syst. & Commun., Univ. of Milano Bicocca, Milan
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Snippet Dynamic analysis of software systems produces behavioral models that are useful for analysis, verification and testing. The main techniques for extracting...
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SubjectTerms Automata
Data mining
dynamic analysis
gk-tail
Informatics
Information analysis
Law
Legal factors
model synthesis
Permission
Software systems
Software testing
System testing
Title Automatic generation of software behavioral models
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