The paper focuses on investigating the combined use of semantic and structural information of programs to support the comprehension tasks involved in the maintenance and reengineering of software systems. Here, semantic refers to the domain specific issues (both problem and development domains) of a software system. The other dimension, structural, refers to issues such as the actual syntactic structure of the program along with the control and data flow that it represents. An advanced information retrieval method, latent semantic indexing, is used to define a semantic similarity measure between software components. Components within a software system are then clustered together using this similarity measure. Simple structural information (.e., file organization) of the software system is then used to assess the semantic cohesion of the clusters and files, with respect to each other. The measures are formally defined for general application. A set of experiments is presented which demonstrates how these measures can assist in the understanding of a nontrivial software system, namely a version of NCSA Mosaic.

The paper describes the results of applying Latent Semantic Analysis (LSA), an advanced information retrieval method, to program source code and associated documentation. Latent Semantic Analysis is a corpus-based statistical method for inducing and representing aspects of the meanings of words and passages (of natural language) reflective in their usage. This methodology is assessed for application to the domain of software components (i.e., source code and its accompanying documentation). Here LSA is used as the basis to cluster software components. This clustering is used to assist in the understanding of a nontrivial software system, namely a version of Mosaic. Applying Latent Semantic Analysis to the domain of source code and internal documentation for the support of program understanding is a new application of this method and a departure from the normal application domain of natural language. 1. Introduction The tasks of maintenance and reengineering of an existing software sy...

The paper describes the results of applying semantic (versus structural) methods to the problems of software maintenance and program comprehension. Here, the focus is on tools to assist programmer to understand large legacy software systems. The method applied, Latent Semantic Analysis, is a corpus-based statistical method for inducing and representing aspects of the meanings of words and passages (of natural language) reflective in their usage. This methodology is assessed for application to the domain of software components (i.e., source code and its accompanying documentation). The intent of applying Latent Semantic Analysis to software components is to automatically induce a specific semantic meaning of a given component. Here, LSA is used as the basis to group software components, across files, to assist in program comprehension. This clustering is used in the understanding of a nontrivial software system, namely a version of Mosaic. KEYWORDS Software Maintenance, Program Unders...