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In computer science, an abstract state machine (ASM) is a state machine operating on states that are arbitrary data structures (structure in the sense of mathematical logic, that is a nonempty set together with a number of functions (operations) and relations over the set).
The ASM Method is a practical and scientifically well-founded systems engineering method that bridges the gap between the two ends of system development:
The method builds upon three basic concepts:
In the original conception of ASMs, a single agent executes a program in a sequence of steps, possibly interacting with its environment. This notion was extended to capture distributed computations, in which multiple agents execute their programs concurrently.
Since ASMs model algorithms at arbitrary levels of abstraction, they can provide high-level, low-level and mid-level views of a hardware or software design. ASM specifications often consist of a series of ASM models, starting with an abstract ground model and proceeding to greater levels of detail in successive refinements or coarsenings.
Due to the algorithmic and mathematical nature of these three concepts, ASM models and their properties of interest can be analyzed using any rigorous form of verification (by reasoning) or validation (by experimentation, testing model executions).
The concept of ASMs is due to Yuri Gurevich, who first proposed it in the mid-1980s as a way of improving on Turing's thesis that every algorithm is simulated by an appropriate Turing machine. He formulated the ASM Thesis: every algorithm, no matter how abstract, is step-for-step emulated by an appropriate ASM. In 2000, Gurevich axiomatized the notion of sequential algorithms, and proved the ASM thesis for them. Roughly stated, the axioms are as follows:
The axiomatization and characterization of sequential algorithms have been extended to parallel and interactive algorithms.
In the 1990s, through a community effort, [1] the ASM method was developed, using ASMs for the formal specification and analysis (verification and validation) of computer hardware and software. Comprehensive ASM specifications of programming languages (including Prolog, C, and Java) and design languages (UML and SDL) have been developed.
A detailed historical account can be found elsewhere. [2] [3]
A number of software tools for ASM execution and analysis are available.
(in historical order since 2000)
In computer science, static program analysis is the analysis of computer programs performed without executing them, in contrast with dynamic program analysis, which is performed on programs during their execution in the integrated environment.
In computer science, an abstract machine is a theoretical model that allows for a detailed and precise analysis of how a computer system functions. It is similar to a mathematical function in that it receives inputs and produces outputs based on predefined rules. Abstract machines vary from literal machines in that they are expected to perform correctly and independently of hardware. Abstract machines are "machines" because they allow step-by-step execution of programs; they are "abstract" because they ignore many aspects of actual (hardware) machines. A typical abstract machine consists of a definition in terms of input, output, and the set of allowable operations used to turn the former into the latter. They can be used for purely theoretical reasons as well as models for real-world computer systems. In the theory of computation, abstract machines are often used in thought experiments regarding computability or to analyse the complexity of algorithms. This use of abstract machines is fundamental to the field of computational complexity theory, such as finite state machines, Mealy machines, push-down automata, and Turing machines.
In computer science, formal methods are mathematically rigorous techniques for the specification, development, analysis, and verification of software and hardware systems. The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design.
In the context of hardware and software systems, formal verification is the act of proving or disproving the correctness of a system with respect to a certain formal specification or property, using formal methods of mathematics. Formal verification is a key incentive for formal specification of systems, and is at the core of formal methods. It represents an important dimension of analysis and verification in electronic design automation and is one approach to software verification. The use of formal verification enables the highest Evaluation Assurance Level (EAL7) in the framework of common criteria for computer security certification.
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Logic in computer science covers the overlap between the field of logic and that of computer science. The topic can essentially be divided into three main areas:
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Egon Börger is a German-born computer scientist based in Italy.
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CoreASM is an open source project that focuses on the design of a lean executable ASM language, in combination with a supporting tool environment for high-level design, experimental validation, and formal verification of abstract system models.
Yuri Gurevich, Professor Emeritus at the University of Michigan, is an American computer scientist and mathematician and the inventor of abstract state machines.
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