Inspection Methods in Programming

The work reported here lies in the area of overlap between artificial intelligence software engineering. As research in artificial intelligence, it is a step towards a model of problem solving in the domain of programming. In particular, this work focuses on the routine aspects of programming which involve the application of previous experience with similar programs. I call this programming by inspection. Programming is viewed here as a kind of engineering activity. Analysis and synthesis by inspection area prominent part of expert problem solving in many other engineering disciplines, such as electrical and mechanical engineering. The notion of inspections methods in programming developed in this work is motivated by similar notions in other areas of engineering. This work is also motivated by current practical concerns in the area of software engineering. The inadequacy of current programming technology is universally recognized. Part of the solution to this problem will be to increase the level of automation in programming. I believe that the next major step in the evolution of more automated programming will be interactive systems which provide a mixture of partially automated program analysis, synthesis and verification. One such system being developed at MIT, called the programmer's apprentice, is the immediate intended application of this work. This report concentrates on the knowledge are of the programmer's apprentice, which is the form of a taxonomy of commonly used algorithms and data structures. To the extent that a programmer is able to construct and manipulate programs in terms of the forms in such a taxonomy, he may relieve himself of many details and generally raise the conceptual level of his interaction with the system, as compared with present day programming environments. Also, since it is practical to expand a great deal of effort pre-analyzing the entries in a library, the difficulty of verifying the correctness of programs constructed this way is correspondingly reduced. The feasibility of this approach is demonstrated by the design of an initial library of common techniques for manipulating symbolic data. This document also reports on the further development of a formalism called the plan calculus for specifying computations in a programming language independent manner. This formalism combines both data and control abstraction in a uniform framework that has facilities for representing multiple points of view and side effects.

Electrical Design: A Problem for Artificial Intelligence Research

This report outlines the problem of intelligent failure recovery in a problem-solver for electrical design. We want our problem solver to learn as much as it can from its mistakes. Thus we cast the engineering design process on terms of Problem Solving by Debugging Almost-Right Plans, a paradigm for automatic problem solving based on the belief that creation and removal of "bugs" is an unavoidable part of the process of solving a complex problem. The process of localization and removal of bugs called for by the PSBDARP theory requires an approach to engineering analysis in which every result has a justification which describes the exact set of assumptions it depends upon. We have developed a program based on Analysis by Propagation of Constraints which can explain the basis of its deductions. In addition to being useful to a PSBDARP designer, these justifications are used in Dependency-Directed Backtracking to limit the combinatorial search in the analysis routines. Although the research we will describe is explicitly about electrical circuits, we believe that similar principles and methods are employed by other kinds of engineers, including computer programmers.