Pattern matching for design concept localization

The effective synergy of a number of different techniques is the key to the successful development of an efficient reverse engineering environment. Compiler technology, pattern matching techniques, visualization tools, and software repositories play an important role for the identification of procedural, data, and abstract-data-type related concepts in the source code. This paper describes a number of techniques used for the development of a distributed reverse engineering environments. Design recovery is investigated through code-to-code and abstract-descriptions-to-code pattern matching techniques used to locate code that may implement a particular plan or algorithm. The code-to-code matching uses dynamic programming techniques to locate similar code fragments and is targeted for large software systems (1MLOC). Patterns are specified either as source code or as a sequence of abstract statements written in an concept language developed for this purpose. Markov models are used to compute similarity measures between an abstract description and or code fragment in terms of the probability that a given abstract statement can generate a given code fragment. The abstract-description-to-code matcher is under implementation and early experiments show it is a promising technique.