Discusses our approach to the problem of refining high-level simulation specifications. Our domain is simulated combat training for tank platoon members. Our input is a high-level specification for a training scenario and our output is an executable specification for the behavior of a network-based combat simulator. Our approach combines a detailed model of the tank training domain with nonlinear planning and constraint satisfaction techniques. Our initial implementation is successful in large part because of our use of domain knowledge to limit the branching factor of the planner and the constraint satisfaction engine.

The large size and high-percentage of domain-specific code in most legacy systems makes it unlikely that automated tools will be able to extract a complete underlying design. Yet automated tools can clearly recognize portions of the design. This suggests exploring environments in which programmer and system work together to understand legacy software. DECODE is such an environment. It supports programmer and system co-operation to extract design information from legacy software systems. DECODE's automated program understanding component recognizes standard implementations of domain independent plans to produce an initial knowledge base of object-orientated design elements. DECODE's structured notebook component provides the user with a graphical view of the initial understanding, which the user can extend by linking arbitrary source code fragments to either existing or new design elements, and then uses this design information to support conceptual queries about the program's code and design.

This paper addresses the question of whether the reverse engineering of legacy systems is doomed to failure.Our position is that the answer is highly dependent on the specific goals of the reverse engineering process.We argue that while most reverse engineering efforts may well fail to achieve the traditional goal of automatically extracted complete specifications suitable for forward engineering, they are likely to succeed on the more modest goal of automatically extracting partial specifications that can augmented by system-assisted human understanders.

The authors present a knowledge-based approach to encouraging the reuse of existing simulation and modeling programs. To get around the problems of poor interfaces and minimal documentation, they are: treating each existing program as an operator in a planning system; creating a knowledge base describing the goals each program achieves, the pre- and post-conditions of running the program, and its I/O behavior; and developing several tools that make use of this knowledge to automate the development of new interfaces, to assist the creation of scripts that achieve high-level user goals, and to allow potential reusers to view a graphical representation of the component's role in solving high-level domain problems.>