Check Constraints Trees ) Advice Graph Parse Attributes

Recognizing commonly used data structures and algorithms is a key activity in reverse engineering. Systems developed to automate this recognition process have been isolated, stand-alone systems, usually targeting a speciic task. We are interested in applying recognition to multiple tasks requiring reverse engineering , such as inspecting, maintaining, and reusing software. This requires a exible, adaptable recognition architecture, since the tasks vary in the amount and accuracy of knowledge available about the program , the requirements on recognition power, and the resources available. We have developed a recognition system based on graph parsing. It has a exible, adaptable control structure that can accept advice from external agents. Its exibility arises from using a chart parsing algorithm. We are studying this graph parsing approach to determine what types of advice can enhance its capabilities, performance, and scalability.