Timing-Failure Risk Assessment of UML Design Using Time Petri Net Bound Techniques

Software systems that do not meet their timing constraints can cause risks. In this work, we propose a comprehensive method for assessing the risk of timing failure by evaluating the software design. We show how to apply best practises in software engineering and well-known Time Petri Net (TPN) modeling and analysis techniques, and we demonstrate the effectiveness of the method with reference to a case study in the domain of real-time embedded systems. The method customizes the Australian standard risk management process, where the system context is the UML-based software specification, enriched with standard MARTE profile annotations to capture nonfunctional system properties. During the risk analysis, a TPN is derived, via model transformation, from the software design specification and TPN bound techniques are applied to estimate the probability of timing failure. TPN bound techniques are also exploited, within the risk evaluation and treatment steps, to identify the risk causes in the software design.

[1]  Paola Inverardi,et al.  Model-based performance prediction in software development: a survey , 2004, IEEE Transactions on Software Engineering.

[2]  Hany H. Ammar,et al.  Architectural-Level Risk Analysis Using UML , 2003, IEEE Trans. Software Eng..

[3]  Simona Bernardi,et al.  Computation of Performance Bounds for Real-Time Systems Using Time Petri Nets , 2009, IEEE Transactions on Industrial Informatics.

[4]  J. Cardoso,et al.  Ordering actions in sequence diagrams of UML , 2001, Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001..

[5]  John A. McDermid,et al.  Hierarchically Performed Hazard Origin and Propagation Studies , 1999, SAFECOMP.

[6]  Simona Bernardi,et al.  Performance evaluation of UML design with Stochastic Well-formed Nets , 2007, J. Syst. Softw..

[7]  Peter Neumann,et al.  Safeware: System Safety and Computers , 1995, SOEN.

[8]  Marco Gribaudo,et al.  ITPN-PerfBound: A Performance Bound Tool for Interval Time Petri Nets , 2009, TACAS.

[9]  O. Ribeiro,et al.  Designing Tool Support for Translating Use Cases and UML 2.0 Sequence Diagrams into a Coloured Petri Net , 2007, Sixth International Workshop on Scenarios and State Machines (SCESM'07: ICSE Workshops 2007).

[10]  Simona Bernardi,et al.  On performance bounds for interval time petri nets , 2004, First International Conference on the Quantitative Evaluation of Systems, 2004. QEST 2004. Proceedings..

[11]  Dianxiang Xu,et al.  Compositional schedulability analysis of real-time systems using time Petri nets , 2002 .

[12]  C. Murray Woodside,et al.  An intermediate metamodel with scenarios and resources for generating performance models from UML designs , 2007, Software & Systems Modeling.

[13]  Hiromitsu Ogata Uncertainty in risk analysis , 2009 .

[14]  Roland Meyer,et al.  Compositional Semantics for UML 2.0 Sequence Diagrams Using Petri Nets , 2005, SDL Forum.

[15]  Susanna Donatelli,et al.  From UML sequence diagrams and statecharts to analysable petri net models , 2002, WOSP '02.

[16]  M. Diaz,et al.  Modeling and Verification of Time Dependent Systems Using Time Petri Nets , 1991, IEEE Trans. Software Eng..

[17]  I. Hogganvik,et al.  Model-based security analysis in seven steps — a guided tour to the CORAS method , 2007 .

[18]  Edward D. Lazowska,et al.  Quantitative system performance - computer system analysis using queueing network models , 1983, Int. CMG Conference.

[19]  Rob Pooley,et al.  Derivation of Petri Net Performance Models from UML Specifications of Communications Software , 2000, Computer Performance Evaluation / TOOLS.

[20]  Rajeev Alur,et al.  A Theory of Timed Automata , 1994, Theor. Comput. Sci..

[21]  Guiseppe Mauri,et al.  Integrating safety analysis techniques, supporting identification of common cause failures , 2000 .

[22]  Homayoon Dezfuli,et al.  Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners (Second Edition) , 2011 .

[23]  Enrico Vicario,et al.  Static Analysis and Dynamic Steering of Time-Dependent Systems , 2001, IEEE Trans. Software Eng..

[24]  R. B. Kearfott,et al.  Interval Computations: Introduction, Uses, and Resources , 2000 .

[25]  Laura Carnevali,et al.  Using Stochastic State Classes in Quantitative Evaluation of Dense-Time Reactive Systems , 2009, IEEE Transactions on Software Engineering.

[26]  Iulian Ober,et al.  Validating timed UML models by simulation and verification , 2006, International Journal on Software Tools for Technology Transfer.

[27]  Marco Ajmone Marsan,et al.  Modelling with Generalized Stochastic Petri Nets , 1995, PERV.

[28]  Carl Eklund,et al.  National Institute for Standards and Technology , 2009, Encyclopedia of Biometrics.

[29]  P. Merlin,et al.  Recoverability of Communication Protocols - Implications of a Theoretical Study , 1976, IEEE Transactions on Communications.

[30]  Hany H. Ammar,et al.  Model-based performance risk analysis , 2005, IEEE Transactions on Software Engineering.

[31]  Pieter H. Hartel,et al.  Model-based qualitative risk assessment for availability of IT infrastructures , 2010, Software & Systems Modeling.

[32]  Carl E. Landwehr,et al.  Basic concepts and taxonomy of dependable and secure computing , 2004, IEEE Transactions on Dependable and Secure Computing.

[33]  José Merseguer,et al.  Performance by unified model analysis (PUMA) , 2005, WOSP '05.

[34]  Simona Bernardi,et al.  A dependability profile within MARTE , 2011, Software & Systems Modeling.

[35]  Sébastien Gérard,et al.  SOPHIA: a Modeling Language for Model-Based Safety Engineering , 2009, ACES-MB@MoDELS.

[36]  Giuliana Franceschinis,et al.  The PSR Methodology: Integrating Hardware and Software Models , 1996, Application and Theory of Petri Nets.