A similarity measure for retrieving software artifacts

presents the mechanism for query processing and retrieval with the measures used for the similarity analysis of the indexing structures. Section 6 describes an experiment conducted to evaluate the effectiveness of the proposed approach. Section 7 summarizes related work in the area of re-use systems. Section 8 concludes the paper with some remarks on planned experiments with the system and further research. Figure 1 shows an overview of the current version of the re-use system. The system consists of a classification mechanism and a retrieval mechanism. The classification system catalogues the software components in a software base through their descriptions in natural language. An acquisition mechanism automatically extracts from software descriptions the knowledge needed to catalogue them in the software base. The system extracts lexical, syntactic and semantic information and this knowledge is used to create a frame-like internal representation for the software component. The interpretation mechanism used for the analysis of a description does not pretend to understand the meaning of a description but to automatically acquire enough information to construct useful indexing units for software components. Semantic analysis of descriptions follows the rules of a semantic formalism. The formalism consists of a case system , constraints and heuristics to perform the translation of the description into an internal representation. Both syntactic and semantic rules are implemented in a grammar to parse descriptions into a set of frames. The semantic formalism is based on some semantic relationships between noun phrases and the verb in a sentence. These semantic relationships provide that similar software descriptions have similar internal representations. A classification scheme for software components derives from the semantic formalism, through a set of generic frames. The internal representation of a description constitutes the indexing unit for the software component, constructed as an instance of these generic frames. The WordNet [8] lexicon is used to obtain morphological information, grammatical categories of terms and lexical relationships between terms. Abstract This paper introduces the main features and the retrieval mechanism of ROSA, a software reuse system based on the processing of the natural language descriptions of software artifacts. The system supports the automatic indexing of components by acquiring lexical, syntactic and semantic knowledge from software descriptions. The retrieval mechanism is based on a similarity analysis that provides good retrieval effectiveness through partial matching of descriptions , processing of synonyms, generalizations and special-izations of terms and considering the syntactic and semantic information available …