1,796 research outputs found
Developing a distributed electronic health-record store for India
The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India
Fault-tolerant computer study
A set of building block circuits is described which can be used with commercially available microprocessors and memories to implement fault tolerant distributed computer systems. Each building block circuit is intended for VLSI implementation as a single chip. Several building blocks and associated processor and memory chips form a self checking computer module with self contained input output and interfaces to redundant communications buses. Fault tolerance is achieved by connecting self checking computer modules into a redundant network in which backup buses and computer modules are provided to circumvent failures. The requirements and design methodology which led to the definition of the building block circuits are discussed
Mathematics in Software Reliability and Quality Assurance
This monograph concerns the mathematical aspects of software reliability and quality assurance and consists of 11 technical papers in this emerging area. Included are the latest research results related to formal methods and design, automatic software testing, software verification and validation, coalgebra theory, automata theory, hybrid system and software reliability modeling and assessment
Agents and Robots for Reliable Engineered Autonomy
This book contains the contributions of the Special Issue entitled "Agents and Robots for Reliable Engineered Autonomy". The Special Issue was based on the successful first edition of the "Workshop on Agents and Robots for reliable Engineered Autonomy" (AREA 2020), co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020). The aim was to bring together researchers from autonomous agents, as well as software engineering and robotics communities, as combining knowledge from these three research areas may lead to innovative approaches that solve complex problems related to the verification and validation of autonomous robotic systems
Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications
Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance
Formal Specification and Verification for Automated Production Systems
Complex industrial control software often drives safety- and mission-critical
systems, like automated production plants or control units embedded into devices in automotive systems. Such controllers have in common that they are reactive systems, i.e., that they periodically read sensor stimuli and cyclically execute the same program to produce actuator signals.
The correctness of software for automated production is rarely verified using
formal techniques. Although, due to the Industrial Revolution 4.0 (IR4.0), the
impact and importance of software have become an important role in industrial automation.
What is used instead in industrial practice today is testing and simulation,
where individual test cases are used to validate an automated production system.
Three reasons why formal methods are not popular are: (a) It is difficult to
adequately formulate the desired temporal properties. (b) There is a lack of
specification languages for reactive systems that are both sufficiently
expressive and comprehensible for practitioners. (c) Due to the lack of an
environment model the obtained results are imprecise. Nonetheless, formal
methods for automated production systems are well studied academically---mainly on the verification of safety properties via model checking.
In this doctoral thesis we present the concept of (1) generalized test tables
(GTTs), a new specification language for functional properties, and their
extension (2) relational test tables (RTTs) for relational properties. The
concept includes the syntactical notion, designed for the intuition of
engineers, and the semantics, which are based on game theory. We use RTTs for a novel confidential property on reactive systems, the provably forgetting of information. Moreover, for regression verification, an important relational
property, we are able to achieve performance improvements by (3) creating
a decomposing rule which splits large proofs into small sub-task. We implemented the verification procedures and evaluated them against realistic case studies, e.g., the Pick-and-Place-Unit from the Technical University of Munich.
The presented contribution follows the idea of lowering the obstacle of
verifying the dependability of reactive systems in general, and automated
production systems in particular for the engineer either by introducing a new
specification language (GTTs), by exploiting existing programs for the
specification (RTTs, regression verification), or by improving the verification
performance
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