Meta-evaluation of Actors with Side-effects

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N000-14-74-C-0643.Meta-evaluation is a process which symbolically evaluates an actor and checks to see whether the actor fulfills its contract (specification). A formalism for writing contracts for actors with side-effects which allow sharing of data is presented. Typical examples of actors with side-effects are the cell, actor counterparts of the LISP function rplaca and rplacd, and procedures whose computation depends upon their input history. Meta-evaluation of actors with side-effects is carried out by using situational tags which denotes a situation (local state of an actor systems at the moment of the transmissions of messages). It is illustrated how the situational tags are used for proving the termination of the activation of actors.MIT Artificial Intelligence Laborator

Plan Verification in a Programmer's Apprentice

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under the Office of Naval Research contract N00014-75-C-0643.Brief Statement of the Problem: An interactive programming environment called the Programmer's Apprentice is described. Intended for use by the expert programmer in the process of program design and maintenance, the apprentice will be capable of understanding, explaining and reasoning about the behavior of real-world LISP programs with side effects on complex data-structures. We view programs as engineered devices whose analysis must be carried out at many level of abstraction. This leads to a set of logical dependencies between modules which explains how and why modules interact to achieve an overall intention. Such a network of dependencies is a teleological structure which we call a plan; the process of elucidating such a plan stucture and showing that it is coherent and that it achieves its overall intended behavior we call plan verification. This approach to program verification is sharply contrasted with the traditional Floyd-Hoare systems which overly restrict themselves to surface features of the programming language. More similar in philosophy is the evolving methodology of languages like CLU or ALPHARD which stress conceptual layering.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

Symbol IC-Evaluation as an Aid to Program Synthesis

This report describes research done at the Artificial Intelligence laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advance Research Projects Agency of the Department of Defence under Office of Naval Research contract N00014-75-C0522.Symbolic-evaluation is the process which abstractly evaluates an actor program and checks to see whether the program fulfills its contract (specification). In this paper, a formalism based on the conceptual representation is proposed as a specification language and a proof system for programs which may include change of behavior (side-effects). The relation between algebraic specifications and the specifications based on the conceptual representation is discussed and the limitation of the current algebraic specifications is pointed out. The proposed formalism can deal with problems of side-effects which have been beyond the scope of Floyd-Hoare proof rules. Symbolic-evaluation is carried out with explicit use of the notion of situation (local state of an actor system). Uses of situational tags in assertions make it possible to state relations holding between objects in different situations. As an illustrative example, an impure actors which behave like a queue is extensively examined. The verification of a procedure which deals with the queue-actors and the correctness of its implementations are demonstrated by the symbolic-evaluation. Furthermore how the symbolic-evaluation serves as an aid to program synthesis is illustrated using two different implementations of the queue-actor.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

Derivation of logic programs

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