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Value-Based Test Case Prioritization for Regression Testing Using Genetic Algorithms

Computers, Materials & Continua 2023年第1期74卷 2211-2238页

作者： Farrukh Shahzad Ahmed awais majeed Tamim Ahmed Khan Department of Software Engineering Bahria UniversityIslamabadCapitalPakistan

Test Case Prioritization(TCP)techniques perform better than other regression test optimization techniques including Test Suite Reduction(TSR)and Test Case Selection(TCS).Many TCP techniques are available,and their performance is usually measured through a metric Average Percentage of Fault Detection(APFD).This metric is value-neutral because it only works well when all test cases have the same cost,and all faults have the same *** APFD for performance evaluation of test case orders where test cases cost or faults severity varies is prone to produce false ***,using the right metric for performance evaluation of TCP techniques is very important to get reliable and correct *** this paper,two value-based TCP techniques have been introduced using Genetic Algorithm(GA)including Value-Cognizant Fault Detection-Based TCP(VCFDB-TCP)and Value-Cognizant Requirements Coverage-Based TCP(VCRCB-TCP).Two novel value-based performance evaluation metrics are also introduced for value-based TCP including Average Percentage of Fault Detection per value(APFDv)and Average Percentage of Requirements Coverage per value(APRCv).Two case studies are performed to validate proposed techniques and performance evaluation *** proposed GA-based techniques outperformed the existing state-of-the-art TCP techniques including Original Order(OO),Reverse Order(REV-O),Random Order(RO),and Greedy algorithm.

关键词： Average percentage of fault detection test case prioritization regression testing and value-based testing value-based test case prioritization genetic algorithms

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Ontology-Based Crime News Semantic Retrieval System

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Computers, Materials & Continua 2023年第10期77卷 601-614页

作者： Fiaz majeed Afzaal Ahmad Muhammad awais Hassan Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Information Technology University of GujratGujrat50700Pakistan Department of Computer Science University of Engineering&TechnologyLahore54890Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular *** news exists on the Internet in unstructured formats such as books,websites,documents,and *** such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement ***-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant *** are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given ***,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the *** ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal *** semantic system retrieves information in view of the similarity of the semantics among indexed data and user *** this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two *** the first experiment,we implemented a keyword-based textual IR systemusing Apache *** the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL *** keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.

关键词： Web 3.0 crime ontology semantic web knowledge representation

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