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4 results on '"DIVERSE (INRIA - IRISA) '

1. Scapegoat: an Adaptive monitoring framework for Component-based systems

Author

DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, Adèle ; DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA - Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, Antony Tang, European Project : 264840, PEOPLE, FP7-PEOPLE-2010-ITN, RELATE(2011), Gonzalez-Herrera, Inti, Bourcier, Johann, Daubert, Erwan, Rudametkin, Walter, Barais, Olivier, Fouquet, François, Jézéquel, Jean-Marc, DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, Adèle ; DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA - Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, Antony Tang, European Project : 264840, PEOPLE, FP7-PEOPLE-2010-ITN, RELATE(2011), Gonzalez-Herrera, Inti, Bourcier, Johann, Daubert, Erwan, Rudametkin, Walter, Barais, Olivier, Fouquet, François, and Jézéquel, Jean-Marc

Abstract

International audience, Modern component frameworks support continuous deployment and simultaneous execution of multiple software components on top of the same virtual machine. However, isolation between the various components is limited. A faulty version of any one of the software components can compromise the whole system by consuming all available resources. In this paper, we address the problem of efficiently identifying faulty software components running simultaneously in a single virtual machine. Current solutions that perform permanent and extensive monitoring to detect anomalies induce high overhead on the system, and can, by themselves, make the system unstable. In this paper we present an optimistic adaptive monitoring system to determine the faulty components of an application. Suspected components are finely instrumented for deeper analysis by the monitoring system, but only when required. Unsuspected components are left untouched and execute normally. Thus, we perform localized just-in-time monitoring that decreases the accumulated overhead of the monitoring system. We evaluate our approach against a state-of-the-art monitoring system and show that our technique correctly detects faulty components, while reducing overhead by an average of 80%.

2. MPLM -- MaTeLo Product Line Manager

Author

DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, ALL4TEC RD [Laval] ; ALL4TEC, Airbus ; Airbus Group [Germany] ; AIRBUS - AIRBUS, ALL4TEC, Airbus defence and space, European Project : 269335, SP1-JTI-ARTEMIS-2010-1, MBAT(2011), Samih, Hamza, Bogusch, Ralf, DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, ALL4TEC RD [Laval] ; ALL4TEC, Airbus ; Airbus Group [Germany] ; AIRBUS - AIRBUS, ALL4TEC, Airbus defence and space, European Project : 269335, SP1-JTI-ARTEMIS-2010-1, MBAT(2011), Samih, Hamza, and Bogusch, Ralf

Abstract

International audience, The diversity of requirements elicited from different customers leads to the development of many variants. Furthermore, compliance with safety standards as mandated for safety-critical systems requires high test efforts for each variant. Model-based testing aims to reduce test efforts by automatically generating test cases from test models. In this paper, we introduce variability management to usage models, a widely used model-based testing formalism. We present an approach that allows to derive usage model variants from a desired set of features and thus generate test cases for each variant. The approach is integrated in the industrial model-based testing tool chain MaTeLo and exemplified using an industrial case study from the aerospace domain.

3. An Approach to Derive Usage Models Variants for Model-based Testing

Author

DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, ALL4TEC RD [Laval] ; ALL4TEC, Airbus ; Airbus Group [Germany] ; AIRBUS - AIRBUS, ALL4TEC, Airbus defence and space, INRIA, European Project : 269335, SP1-JTI-ARTEMIS-2010-1, MBAT(2011), Samih, Hamza, Le Guen, Hélène, Bogusch, Ralf, Acher, Mathieu, Baudry, Benoit, DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, ALL4TEC RD [Laval] ; ALL4TEC, Airbus ; Airbus Group [Germany] ; AIRBUS - AIRBUS, ALL4TEC, Airbus defence and space, INRIA, European Project : 269335, SP1-JTI-ARTEMIS-2010-1, MBAT(2011), Samih, Hamza, Le Guen, Hélène, Bogusch, Ralf, Acher, Mathieu, and Baudry, Benoit

Abstract

International audience, Testing techniques in industry are not yet adapted for product line engineering (PLE). In particular, Model-based Testing (MBT), a technique that allows to automatically generate test cases from requirements, lacks support for managing variability (differences) among a set of related product. In this paper, we present an approach to equip usage models, a widely used formalism in MBT, with variability capabilities. Formal correspondences are established between a variability model, a set of functional requirements, and a usage model. An algorithm then exploits the traceability links to automatically derive a usage model variant from a desired set of selected features. The approach is integrated into the professional MBT tool MaTeLo and is currently used in industry.

4. A Prediction-Driven Adaptation Approach for Self-Adaptive Sensor Networks

Author

DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, Karlsruhe Institute of Technology (KIT) ; Forschungszentrum Karlsruh - Universität of Karlsruhe, Nelly Bencomo, European Project : 264840, PEOPLE, FP7-PEOPLE-2010-ITN, RELATE(2011), Paez Anaya, Ivan Dario, Simko, Viliam, Bourcier, Johann, Plouzeau, Noël, Jézéquel, Jean-Marc, DIVERSE (INRIA - IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - INRIA, Karlsruhe Institute of Technology (KIT) ; Forschungszentrum Karlsruh - Universität of Karlsruhe, Nelly Bencomo, European Project : 264840, PEOPLE, FP7-PEOPLE-2010-ITN, RELATE(2011), Paez Anaya, Ivan Dario, Simko, Viliam, Bourcier, Johann, Plouzeau, Noël, and Jézéquel, Jean-Marc

Abstract

International audience, Engineering self-adaptive software in unpredictable environments such as pervasive systems, where network's ability, remaining battery power and environmental conditions may vary over the lifetime of the system is a very challenging task. Many current software engineering approaches leverage run-time architectural models to ease the design of the autonomic control loop of these self-adaptive systems. While these approaches perform well in reacting to various evolutions of the runtime environment, implementations based on reactive paradigms have a limited ability to anticipate problems, leading to transient unavailability of the system, useless costly adaptations, or resources waste. In this paper, we follow a proactive self-adaptation approach that aims at overcoming the limitation of reactive approaches. Based on predictive analysis of internal and external context information, our approach regulates new architecture recon figurations and deploys them using models at runtime. We have evaluated our approach on a case study where we combined hourly temperature readings provided by National Climatic Data Center (NCDC) with re reports from Moderate Resolution Imaging Spectroradiometer (MODIS) and simulated the behavior of multiple systems. The results confirm that our proactive approach outperforms a typical reactive system in scenarios with seasonal behavior.

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