A Theoretical and Empirical Evaluation of Software Component Search Engines, Semantic Search Engines and Google Search Engine in the Context of COTS-Based Development
This addresses the problem of efficiently finding suitable COTS components for developers, but it is incremental as it compares existing search engines without introducing new methods.
The paper evaluated the performance of 18 search engines, including software component, semantic, and Google, in identifying COTS components for reuse, finding variations in precision and normalized recall based on ten defined queries.
COTS-based development is a component reuse approach promising to reduce costs and risks, and ensure higher quality. The growing availability of COTS components on the Web has concretized the possibility of achieving these objectives. In this multitude, a recurrent problem is the identification of the COTS components that best satisfy the user requirements. Finding an adequate COTS component implies searching among heterogeneous descriptions of the components within a broad search space. Thus, the use of search engines is required to make more efficient the COTS components identification. In this paper, we investigate, theoretically and empirically, the COTS component search performance of eight software component search engines, nine semantic search engines and a conventional search engine (Google). Our empirical evaluation is conducted with respect to precision and normalized recall. We defined ten queries for the assessed search engines. These queries were carefully selected to evaluate the capability of each search engine for handling COTS component identification.