Self-aware computing systems:from psychology to engineering

At the current time, there are several fundamental changes in the way computing systems are being developed, deployed and used. They are becoming increasingly large, heterogeneous, uncertain, dynamic and decentralised. These complexities lead to behaviours during run time that are difficult to understand or predict. One vision for how to rise to this challenge is to endow computing systems with increased self-awareness, in order to enable advanced autonomous adaptive behaviour. A desire for self-awareness has arisen in a variety of areas of computer science and engineering over the last two decades, and more recently a more fundamental understanding of what self-awareness concepts might mean for the design and operation of computing systems has been developed. This draws on self-awareness theories from psychology and other related fields, and has led to a number of contributions in terms of definitions, architectures, algorithms and case studies. This paper introduces some of the main aspects of self-awareness from psychology, that have been used in developing associated notions in computing. It then describes how these concepts have been translated to the computing domain, and provides examples of how their explicit consideration can lead to systems better able to manage trade-offs between conflicting goals at run time in the context of a complex environment, while reducing the need for a priori domain modelling at design or deployment time

Co-evolutionary automatic programming for software development

AbstractSince the 1970s the goal of generating programs in an automatic way (i.e., Automatic Programming) has been sought. A user would just define what he expects from the program (i.e., the requirements), and it should be automatically generated by the computer without the help of any programmer. Unfortunately, this task is much harder than expected. Although transformation methods are usually employed to address this problem, they cannot be employed if the gap between the specification and the actual implementation is too wide. In this paper we introduce a novel conceptual framework for evolving programs from their specification. We use genetic programming to evolve the programs, and at the same time we exploit the specification to co-evolve sets of unit tests. Programs are rewarded by how many tests they do not fail, whereas the unit tests are rewarded by how many programs they make to fail. We present and analyse seven different problems on which this novel technique is successfully applied

Using negative correlation to evolve fault-tolerant circuits

Abstract. In this paper, we show how artificial evolution can be used to improve the fault-tolerance of electronic circuits. We show that evolution is able to improve the fault tolerance of a digital circuit, given a known fault model. Evolution is also able to create sets of different circuits that, when combined into an ensemble of circuits, have reduced correlation in their fault pattern, and therefore improved fault tolerance. An important part of the algorithm used to create the circuits is a measure of the correlation between the fault patterns of different circuits. Using this measure in the fitness, the circuits evolve towards different, highly fault-tolerant circuits. The measure also proves very useful for fitness sharing purposes. We have evolved a number of circuits for a simple 2 × 3 multiplier problem, and use these to demonstrate the performance under different simulated fault models. 1

Computing system reliability modeling, analysis, and optimization

Ph.DDOCTOR OF PHILOSOPH

Robust design of deep-submicron digital circuits

Avec l'augmentation de la probabilité de fautes dans les circuits numériques, les systèmes développés pour les environnements critiques comme les centrales nucléaires, les avions et les applications spatiales doivent être certifies selon des normes industrielles. Cette thèse est un résultat d'une cooperation CIFRE entre l'entreprise Électricité de France (EDF) R&D et Télécom Paristech. EDF est l'un des plus gros producteurs d'énergie au monde et possède de nombreuses centrales nucléaires. Les systèmes de contrôle-commande utilisé dans les centrales sont basés sur des dispositifs électroniques, qui doivent être certifiés selon des normes industrielles comme la CEI 62566, la CEI 60987 et la CEI 61513 à cause de la criticité de l'environnement nucléaire. En particulier, l'utilisation des dispositifs programmables comme les FPGAs peut être considérée comme un défi du fait que la fonctionnalité du dispositif est définie par le concepteur seulement après sa conception physique. Le travail présenté dans ce mémoire porte sur la conception de nouvelles méthodes d'analyse de la fiabilité aussi bien que des méthodes d'amélioration de la fiabilité d'un circuit numérique.The design of circuits to operate at critical environments, such as those used in control-command systems at nuclear power plants, is becoming a great challenge with the technology scaling. These circuits have to pass through a number of tests and analysis procedures in order to be qualified to operate. In case of nuclear power plants, safety is considered as a very high priority constraint, and circuits designed to operate under such critical environment must be in accordance with several technical standards such as the IEC 62566, the IEC 60987, and the IEC 61513. In such standards, reliability is treated as a main consideration, and methods to analyze and improve the circuit reliability are highly required. The present dissertation introduces some methods to analyze and to improve the reliability of circuits in order to facilitate their qualification according to the aforementioned technical standards. Concerning reliability analysis, we first present a fault-injection based tool used to assess the reliability of digital circuits. Next, we introduce a method to evaluate the reliability of circuits taking into account the ability of a given application to tolerate errors. Concerning reliability improvement techniques, first two different strategies to selectively harden a circuit are proposed. Finally, a method to automatically partition a TMR design based on a given reliability requirement is introduced.PARIS-Télécom ParisTech (751132302) / SudocSudocFranceF

Automatic software generation and improvement through search based techniques

Writing software is a difficult and expensive task. Its automation is hence very valuable. Search algorithms have been successfully used to tackle many software engineering problems. Unfortunately, for some problems the traditional techniques have been of only limited scope, and search algorithms have not been used yet. We hence propose a novel framework that is based on a co-evolution of programs and test cases to tackle these difficult problems. This framework can be used to tackle software engineering tasks such as Automatic Refinement, Fault Correction and Improving Non-functional Criteria. These tasks are very difficult, and their automation in literature has been limited. To get a better understanding of how search algorithms work, there is the need of a theoretical foundation. That would help to get better insight of search based software engineering. We provide first theoretical analyses for search based software testing, which is one of the main components of our co-evolutionary framework. This thesis gives the important contribution of presenting a novel framework, and we then study its application to three difficult software engineering problems. In this thesis we also give the important contribution of defining a first theoretical foundation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo