Fuzzy based Schematic Component Selection Decision Search with OPAM-Ocaml Engine

Author(s): Iqbaldeep Kaur*, Rajesh Kumar Bawa.

Journal Name: Recent Patents on Computer Science

Volume 12 , Issue 3 , 2019

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Graphical Abstract:


Background: With an exponential increase in software online as well as offline, through each passing day, the task of digging out precise and relevant software components has become the need of the hour. There is no dearth of techniques used for the retrieval of software component from the available online and offline repositories in the conceptual as well as the empirical literature. However each of these techniques has its own set of limitations and suitability.

Objective: The proposed technique gives concrete decision using schematic based search that gives better result and higher precision and recall values.

Methods: In this paper, a component decision and retrieval engine called SR-SCRS (Schematic and Refinement based Software Component Retrieval System) has been presented using OPAM. OPAM is a github repository containing software components (packages), designed by OcamlPro. This search engine employs two retrieval techniques for a robust decision vis-o-vis Schematic-based search with fuzzy logic and Refinement-based search. The Schematic based search is based on matching the attribute values and the threshold of those values as given by the user. Thereafter the results are optimized to achieve the level of relevance using fuzzy logic. Refinement based search works on one particular attribute value. The experiments have been conducted and validated on OPAM dataset.

Results: Precisely, the average precision of Schematic based search and Refinement based search is 60% and 27.86% which shows robust results.

Conclusion: Hence, the performance and efficiency of the proposed work has been evaluated and compared with the other retrieval technique.

Keywords: Software component retrieval system, schematic based search, refinement based search, retrieval technique, empirical literature, efficiency.

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Article Details

Year: 2019
Page: [224 - 232]
Pages: 9
DOI: 10.2174/2213275912666181210104742
Price: $58

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