Design of framework for ontological component retrieval from software component repositories

2020 ◽  
Vol 1 (2/3) ◽  
pp. 260
Author(s):  
Iqbaldeep Kaur ◽  
Rajesh Kumar Bawa
Keyword(s):  
Software Component ◽  
Component Retrieval

NEURO-FUZZY BASED SEARCH ROBOT FOR SOFTWARE COMPONENTS

1999 ◽  
Vol 08 (02) ◽  
pp. 119-135
Author(s):  
YAU-HWANG KUO ◽  
JANG-PONG HSU ◽  
MONG-FONG HORNG
Keyword(s):  
Retrieval System ◽  
Software Component ◽  
Software Components ◽  
Personalized Search ◽  
Component Retrieval ◽  
Reusable Software ◽  
Major Mechanism ◽  
Fuzzy Models ◽  
Neuro Fuzzy

A personalized search robot is developed as one major mechanism of a personalized software component retrieval system. This search robot automatically finds out the Web servers providing reusable software components, extracts needed software components from servers, classifies the extracted components, and finally establishes their indexing information for local component retrieval in the future. For adaptively tuning the performance of software component extraction and classification, an adaptive thesaurus and an adaptive classifier, realized by neuro-fuzzy models, are embedded in this search robot, and their learning algorithms are also developed. A prototype of the personalized software component retrieval system including the search robot has been implemented to confirm its validity and evaluate the performance. Furthermore, the framework of proposed personalized search robot could be extended to the search and classification of other kinds of Internet documents.

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

2019 ◽  
Vol 12 (3) ◽  
pp. 224-232
Author(s):  
Iqbaldeep Kaur ◽  
Rajesh Kumar Bawa
Keyword(s):  
Fuzzy Logic ◽  
Retrieval System ◽  
Software Component ◽  
Empirical Literature ◽  
Software Components ◽  
Component Retrieval ◽  
Component Selection ◽  
Retrieval Technique ◽  
Selection Decision ◽  
Retrieval Engine

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.

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