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Limits to Evaluation of Software Dependability
 in Software Reliability and Metrics (Proceedings of 7th Annual CSR Conference, GarmischPartenkirchen
, 1991
"... inherent uncertainty It has been said that the term software engineering is an aspiration not a description. We would like to be able to claim that we engineer software, in the same sense that we engineer an aeroengine, but most of us would agree that this is not currently an accurate description o ..."
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Cited by 15 (3 self)
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inherent uncertainty It has been said that the term software engineering is an aspiration not a description. We would like to be able to claim that we engineer software, in the same sense that we engineer an aeroengine, but most of us would agree that this is not currently an accurate description of our activities. My suspicion is that it never will be. From the point of view of this essay i.e. dependability evaluation a major difference between software and other engineering artefacts is that the former is pure design. Its unreliability is always the result of design faults, which in turn arise as a result of human intellectual failures. The unreliability of hardware systems, on the other hand, has tended until recently to be dominated by random physical failures of components the consequences of the ‘perversity of nature’. Reliability theories have been developed over the years which have successfully allowed systems to be built to high reliability requirements, and the final system reliability to be evaluated accurately. Even for pure hardware systems, without software, however, the very success of these theories has more recently highlighted the importance of design faults in determining
Dependable Systems Integration using Measurement Theory and Decision Analysis
, 1998
"... Modern computer systems are becoming increasingly complex ensembles of hardware and software. This complexity has many facets, such as the number and diversity of the constituent components, the range of technologies employed, and the complex interactions between the components. If these interaction ..."
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Cited by 12 (0 self)
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Modern computer systems are becoming increasingly complex ensembles of hardware and software. This complexity has many facets, such as the number and diversity of the constituent components, the range of technologies employed, and the complex interactions between the components. If these interactions are unexpected, they may lead to system failures that could result in undesirable or even catastrophic consequences. This is especially of concern in the large, increasingly sophisticated, systems that are being used to control critical services in application areas such as medicine, transport, defence, and finance. Many properties of a system become visible only upon integration (when the components are assembled)  these are called `emergent' properties. They are particularly difficult to control and predict during the development process. The dependability of a system is one such property which we study in detail in this thesis. For systems to be dependable, their behaviour must be pr...
Availability modeling of modular software
 IEEE Transactions on Reliability
, 1999
"... Summary & Conclusions – Dependability evaluation is a basic component in the assessment of the quality of repairable systems. We develop here a general model specifically designed for software systems that allows the evaluation of different dependability metrics, in particular, of availability measu ..."
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Cited by 8 (3 self)
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Summary & Conclusions – Dependability evaluation is a basic component in the assessment of the quality of repairable systems. We develop here a general model specifically designed for software systems that allows the evaluation of different dependability metrics, in particular, of availability measures. The model is of the structural type, based on Markov process theory. In particular, it can be viewed as a attempt to overcome some limitations of the wellknown Littlewood’s reliability model for modular software. We give both the mathematical results necessary to the transient analysis of this general model and the algorithms that allow to evaluate it efficiently. More specifically, from the hal00852656, version 1parameters describing: the evolution of the execution process when there is no failure, the failure processes together with the way they affect the execution, and the recovery process, we obtain the distribution function of the number of failures on a fixed mission period. In fact, we obtain dependability metrics which are much more informative than the usual ones given in a whitebox approach. We briefly discuss the estimation procedures of the parameters of the model. From simple examples, we illustrate the interest in such a structural view and we explain how to take into account reliability growth of part of the software with the transformation approach developed by Laprie and al. Finally, the complete transient analysis of our model allows to discuss in our context the Poissonian approximation reported by Littlewood for its model. 1
Simple formulae for counting processes in reliability models
 Adv. in Appl. Probab
, 1997
"... Dependability evaluation is a basic component in the assessment of the quality of repairable systems. We develop a model taking simultaneously into account the occurrence of failures and repairs, together with the observation of userdefined success events. The model is built from a Markovian descri ..."
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Cited by 6 (5 self)
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Dependability evaluation is a basic component in the assessment of the quality of repairable systems. We develop a model taking simultaneously into account the occurrence of failures and repairs, together with the observation of userdefined success events. The model is built from a Markovian description of the behavior of the system. We obtain the distribution function of the joint number of observed failures and of delivered services on a fixed mission period of the system. In particular, the marginal distribution of the number of failures can be directly related to the distribution of the Markovian Arrival Process extensively used in queueing theory. We give both
A Counting Model for Software Reliability Analysis
 IASTED Journal on Simulation
, 1993
"... : Structural reliability models suffer from some drawbacks mainly related to the assumptions necessary to apply them. We propose a model which intends to overcome some of these limitations appearing in previous published works. We discuss on an approach that can make more realistic the usual Markovi ..."
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Cited by 5 (1 self)
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: Structural reliability models suffer from some drawbacks mainly related to the assumptions necessary to apply them. We propose a model which intends to overcome some of these limitations appearing in previous published works. We discuss on an approach that can make more realistic the usual Markovian assumptions when considering the structural modeling of the execution process. Moreover, we define a failure process allowing to model different and general situations and we give analytic results and algorithmic methods to perform the corresponding quantitative evaluations. We show that our model and the obtained results include as particular cases some previous proposed models. We also discuss about some interesting asymptotic properties of the model. Keywords: Software Reliability, Markov Processes, Counting Processes, Uniformization Technique. (R'esum'e : tsvp) This work was partially supported by the grant 290C2010031305061 of the French Region Bretagne. Part of this report will be...
Extracting Test Sequences from a Markov Software Usage Model by
 ACO”, LNCS
, 2003
"... Abstract. The aim of the paper is to investigate methods for deriving a suitable set of test paths for a software system. The design and the possible uses of the software system are modelled by a Markov Usage Model which reflects the operational distribution of the software system and is enriched by ..."
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Cited by 4 (0 self)
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Abstract. The aim of the paper is to investigate methods for deriving a suitable set of test paths for a software system. The design and the possible uses of the software system are modelled by a Markov Usage Model which reflects the operational distribution of the software system and is enriched by estimates of failure probabilities, losses in case of failure and testing costs. Exploiting this information, we consider the tradeoff between coverage and testing costs and try to find an optimal compromise between both. For that purpose, we use a heuristic optimization procedure inspired by nature, Ant Colony Optimization, which seems to fit very well to the problem structure under consideration. A real world software system is studied to demonstrate the applicability of our approach and to obtain first experimental results. 1
FlowServiceQuality (FSQ) Engineering: Foundations for Network System Analysis and Development
, 2002
"... v 1 Network System Realities.................................................................................1 2 FlowServiceQuality Engineering ................................................................... 5 3 Flow Structure Semantics ......................................................... ..."
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v 1 Network System Realities.................................................................................1 2 FlowServiceQuality Engineering ................................................................... 5 3 Flow Structure Semantics .............................................................................. 11 3.1 The Semantic Model ................................................................................. 11 3.2 FSQ Theorems.......................................................................................... 15 4 Flow Structure Engineering Operations ....................................................... 19 4.1 Flow Engineering for Uncertainty Factors ................................................. 19 4.2 Flow Abstraction and Refinement ............................................................. 20 4.3 Flow Verification ........................................................................................ 22 4.4 Flow Transitivity Analysis .......................................................................... 23 4.5 FlowSets in LargeScale Systems ............................................................ 24 4.6 Flow Security and Survivability Analysis ................................................... 25 5 Computational Quality Attributes .................................................................. 27 5.1 The CQA approach ................................................................................... 27 5.2 CQA Definition .......................................................................................... 29 5.3 Flow Request Analysis .................................................................
Modular Test Plans for Certification of Software Reliability
"... This paper considers the problem of certifying the reliability of a software system that can be decomposed into a finite number of modules. It uses a Markovian model for the transfer of control between modules in order to develop the system reliability expression in terms of the module reliabilities ..."
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This paper considers the problem of certifying the reliability of a software system that can be decomposed into a finite number of modules. It uses a Markovian model for the transfer of control between modules in order to develop the system reliability expression in terms of the module reliabilities. A test procedure is considered in which only the individual modules are tested and the system is certified if, and only if, no failures are observed. The minimum number of tests required of each module is determined such that the probability of certifying a system whose reliability falls below a specified value R 0 is less than a specified small fraction b. This sample size determination problem is formulated as a twostage mathematical program and an algorithm is developed for solving this problem. Two examples from the literature are considered to demonstrate the procedure. Keywords: Software reliability; Modular Tests; Sample Size Determination; Mathematical Programming 1 1. Introduc...
FSQ) Engineering: Foundations for Network System Analysis and Development
"... v 1 Network System Realities ............................................................................... 1 2 FlowServiceQuality Engineering.................................................................. 5 3 Flow Structure Semantics............................................................ ..."
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v 1 Network System Realities ............................................................................... 1 2 FlowServiceQuality Engineering.................................................................. 5 3 Flow Structure Semantics............................................................................. 11 3.1 The Semantic Model ............................................................................... 11 3.2 FSQ Theorems........................................................................................ 15 4 Flow Structure Engineering Operations ...................................................... 19 4.1 Flow Engineering for Uncertainty Factors ................................................ 19 4.2 Flow Abstraction and Refinement ............................................................ 20 4.3 Flow Verification ...................................................................................... 22 4.4 Flow Transitivity Analysis......................................................................... 23 4.5 FlowSets in LargeScale Systems ........................................................... 24 4.6 Flow Security and Survivability Analysis .................................................. 25 5 Computational Quality Attributes................................................................. 27 5.1 The CQA approach.................................................................................. 27 5.2 CQA Definition......................................................................................... 29 5.3 Flow Request Analysis ............................................................................ 29 5.4 A C...
Reliability of Module Based Software System
, 710
"... This paper consider the problem of determining the reliability of a software system which can be decomposed in a number of modules. We have derived the expression of the reliability of a system using the Markovian model for the transfer of control between modules in order. We have given the expressi ..."
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This paper consider the problem of determining the reliability of a software system which can be decomposed in a number of modules. We have derived the expression of the reliability of a system using the Markovian model for the transfer of control between modules in order. We have given the expression of reliability by considering both benign and catastrophic failure. The expression of reliability presented in this work is applicable for some control software which are designed to detect its own internal errors. 1