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Regression Testing Prioritization, Selection and Reduction using Hybrid Criteria

Nitika Sharma, Neha Malhotra
<span title="2014-06-18">2014</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
Tasks of regression testing are: Test Case Prioritization, Test Suite Selection, Test case reduction which give the guarantee that no intended fault is produced while modifying the code.  ...  Initial seed value for hybrid criteria's is taken randomly. This research will lead to give better efficiency in regression testing using hybrid criteria.  ...  The proposed regression test selection and prioritization technique is efficient in regression testing and thereby reduce process of selecting the priority.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/16609-6445">doi:10.5120/16609-6445</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sncops7mcnbbvdkd3kvwgs35he">fatcat:sncops7mcnbbvdkd3kvwgs35he</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602091505/https://research.ijcaonline.org/volume95/number7/pxc3896445.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2f/56/2f5670f91ee67c5a3afbfa0e268e27a1c711f756.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/16609-6445"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

HYBRID DATA APPROACH FOR SELECTING EFFECTIVE TEST CASES DURING THE REGRESSION TESTING

M. Mohan, Tarun Shrimali
<span title="">2017</span> <i title="Exeley, Inc."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hw2mrqep5ffbzot5ist4jgvge4" style="color: black;">International Journal on Smart Sensing and Intelligent Systems</a> </i> &nbsp;
In the STLC of Regression testing, test case selection is one of the most important concerns for effective testing as well as cost of the testing process.  ...  This paper proposes new Hybrid approach that consists of modified Greedy approach for handling the test case selection and Genetic Algorithm uses effective parameter like Initial Population, Fitness Value  ...  Finally result of Hybrid approach has compared with Basic Greedy approach and this research proved that performance of Hybrid approach is better than Basic Greedy approach for effective test case selection  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21307/ijssis-2017-233">doi:10.21307/ijssis-2017-233</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7efflzslwvdjvgmkheyy6uc5ie">fatcat:7efflzslwvdjvgmkheyy6uc5ie</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720174241/https://www.exeley.com/exeley/journals/in_jour_smart_sensing_and_intelligent_systems/10/4/pdf/10.21307_ijssis-2017-233.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/28/68/28685f89f8d0841d898ec12d258a9e77bcc6d8ae.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21307/ijssis-2017-233"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

A Program Model Based Regression Test Selection Technique For D Programming Language

Nitesh Chouhan, Maitreyee Dutta, Mayank Singh
<span title="2015-06-30">2015</span> <i title="Science and Engineering Research Support Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rebsgv7gbjechhypg6np633rcu" style="color: black;">International Journal of Hybrid Information Technology</a> </i> &nbsp;
The test cases that exercise the affected model elements in the program model are selected for regression testing.  ...  regression test suite size. .  ...  We have presented an approach for regression test selection of object-oriented programs that selects test cases by analyzing source code.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijhit.2015.8.6.33">doi:10.14257/ijhit.2015.8.6.33</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nzkbd2crnfbmvc4taaxbbytpau">fatcat:nzkbd2crnfbmvc4taaxbbytpau</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180604045954/http://www.sersc.org/journals/IJHIT/vol8_no6_2015/33.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e3/b4/e3b441da772f91e420c21f8cf19fc08f61efabaf.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijhit.2015.8.6.33"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

HSP: A Hybrid Selection and Prioritisation of Regression Test Cases based on Information Retrieval and Code Coverage applied on an Industrial Case Study

Claudio Magalhães, João Andrade, Lucas Perrusi, Alexandre Mota, Flávia Barros, Eliot Maia
<span title="">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kqzhqyka2ffqdlbon77fd6trwm" style="color: black;">Journal of Systems and Software</a> </i> &nbsp;
A Regression testing selection tool, named Ekstazi, was proposed in the work Gligoric et al. [2015] to adopt the Regression Test Selection (RTS) in industry.  ...  HSP: A HYBRID STRATEGY FOR TCS SELECTION AND PRIORITISATION According to the related literature, regression Test Cases selection is more precisely performed using code related artifacts (modified source  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jss.2019.110430">doi:10.1016/j.jss.2019.110430</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zkvfxmsktzaxpil6tcpqwqfu54">fatcat:zkvfxmsktzaxpil6tcpqwqfu54</a> </span>
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Yield and stability factors associated with hybrid wheat [chapter]

R. Bruns, C. J. Peterson
<span title="">1997</span> <i title="Springer Netherlands"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xmph7lt4hjai7gjecqxo6b2bl4" style="color: black;">Developments in Plant Breeding</a> </i> &nbsp;
The enhanced responsiveness of hybrids, as indicated by higher slopes in regression analyses, was combined with similar deviations from regression response.  ...  This data set (13,739 points) reveals an average 0.454 t ha -1 or 10.8% hybrid yield advantage over purelines in preliminary regional testing.  ...  , selection intensity, selection criteria, and yield testing scope.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-94-011-4896-2_4">doi:10.1007/978-94-011-4896-2_4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tlhzbxeikjebfbzogrnp7j6k6q">fatcat:tlhzbxeikjebfbzogrnp7j6k6q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170923184225/https://naldc.nal.usda.gov/naldc/download.xhtml?id=12945&amp;content=PDF" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a0/71/a07178ea9467f4a60e5c447558e8c542d06a59c1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-94-011-4896-2_4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

A New Hybrid Method Logistic Regression and Feedforward Neural Network for Lung Cancer Data

Taner Tunç
<span title="">2012</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wpareqynwbgqdfodcyhh36aqaq" style="color: black;">Mathematical Problems in Engineering</a> </i> &nbsp;
It was seen that the proposed hybrid approach was superior to logistic regression and feedforward artificial neural networks with respect to many criteria.  ...  In this study, a hybrid approach of model-based logistic regression technique and data-based artificial neural network was proposed for classification purposes.  ...  Figure 9 : 9 ROC Curve for test data in Proposed Hybrid LR-ANN Method. Table 1 : 1 Estimation results of logistic regression.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2012/241690">doi:10.1155/2012/241690</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xn7k4k5qxffwhltg7y2ik2p43e">fatcat:xn7k4k5qxffwhltg7y2ik2p43e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190426094713/http://downloads.hindawi.com/journals/mpe/2012/241690.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/63/f8/63f8cb8269d9d503b9152008471daf412d427f11.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2012/241690"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> hindawi.com </button> </a>

Stability evaluation of oilseed rape hybrids in unreplicated trials carried out in different locations

Bogna Zawieja, Sylwia Lewandowska, Tomasz Mikulski, Wiesław Pilarczyk
<span title="2019-03-11">2019</span> <i title="Walter de Gruyter GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/x2uvou4qyzaw5ewq42mggkfo4y" style="color: black;">Biometrical Letters</a> </i> &nbsp;
The methods applied enabled selection of the most promising hybrids for further yield testing.  ...  Additional characterization of the tested hybrids was performed by regressing hybrid yield on the mean yields of the experiment, as described by Finlay and Wilkinson and by Eberhart and Russel.  ...  Only hybrids yielding higher than the mean yield of standard varieties and with yield stable over locations may be considered for selection for further testing.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2478/bile-2019-0005">doi:10.2478/bile-2019-0005</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xpzzfnn44zgubkgjoltyvo227q">fatcat:xpzzfnn44zgubkgjoltyvo227q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200210004913/https://content.sciendo.com/downloadpdf/journals/bile/56/1/article-p59.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f8/c3/f8c3a1f5d9ce4057ce54f1cad5425f48632dce40.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2478/bile-2019-0005"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Hybrid Prediction Method for Solar Power Using Different Computational Intelligence Algorithms

Md Rahat Hossain, Amanullah Maung Than Oo, A. B. M. Shawkat Ali
<span title="">2013</span> <i title="Scientific Research Publishing, Inc,"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/t6frbvobdfgh7ool7v42karx3m" style="color: black;">Smart Grid and Renewable Energy</a> </i> &nbsp;
This research investigates the applicability of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia.  ...  This potential hybrid model is applicable as a local predictor for any proposed hybrid method in real life application for 6 hours in advance prediction to ensure constant solar power supply in the smart  ...  These tests are done in order ensure the potentiality of those selected heterogeneous regression algorithms for the suggested hybrid method.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4236/sgre.2013.41011">doi:10.4236/sgre.2013.41011</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/prwbjamjjrdxzk4sq4whchn3o4">fatcat:prwbjamjjrdxzk4sq4whchn3o4</a> </span>
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Coverage DB: A Tool for Intelligent Selection of Tests

Aditya Akotkar, M. S.
<span title="2017-10-17">2017</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
Regression testing is an expensive testing procedure utilized to validate modified software. Tester struggles to selectively run the relevant tests for pre-testing defects in software.  ...  'Hybrid' technique selects optimal and relevant number of tests that would provide maximum test coverage with minimal number of tests.  ...  Intersect This is hybrid approach of solving regression test selection problem. This method is combination of By Line and Max Min.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/ijca2017915593">doi:10.5120/ijca2017915593</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n3vzfhh74fh57i5sqfpacznlba">fatcat:n3vzfhh74fh57i5sqfpacznlba</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180603213601/https://www.ijcaonline.org/archives/volume175/number6/akotkar-2017-ijca-915593.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ec/87/ec872fcbc42fb9015170146e917fd761f58586b1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/ijca2017915593"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Page 2147 of Genetics Vol. 168, Issue 4 [page]

<span title="">2004</span> <i title="Genetics Society of America"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_genetics" style="color: black;">Genetics </a> </i> &nbsp;
MAXR stepwise regression: Model selection for multi- ple regression proceeded according to the following steps: a.  ...  Single-marker regressions: A single-marker regression analysis was performed for each of 440 markers in both the hybrid and inbred data.  ... 
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EVALUATION OF GENOTYPE BY ENVIRONMENT INTERACTIONS FROM UNREPLICATED MULTI-ENVIRONMENTAL TRIALS OF HYBRID MAIZE

Ani A. Elias, Kelly R. Robbins, Dev Niyogi, James J. Camberato, R. W. Doerge, Mitchell R. Tuinstra
<span title="2012-04-29">2012</span> <i title="New Prairie Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/avievh33yza7lcwsxj2z6qwryu" style="color: black;">Conference on Applied Statistics in Agriculture</a> </i> &nbsp;
Augmented designs are resource efficient; however, these designs do not efficiently quantify or test GEI variation in the test hybrids.  ...  Modern maize breeding experiments utilize multilocation trials with augmented field designs to evaluate the performance of unreplicated test hybrids.  ...  After comparison, 60 models were selected for predictability test. B) Correlation test of 60 selected NRRMs-3.1.1.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4148/2475-7772.1024">doi:10.4148/2475-7772.1024</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3ohdkz4j5zfkrk6uvgf2tnlvyi">fatcat:3ohdkz4j5zfkrk6uvgf2tnlvyi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719203346/http://newprairiepress.org/cgi/viewcontent.cgi?article=1024&amp;context=agstatconference" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0d/b7/0db7748744194733dd3d61183e8ac3aa6c2e2095.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4148/2475-7772.1024"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

An Effective HFFA Algorithm with K-means Clustering Prioritization Method for Regression Test Case Optimization

Ms. Kale Sanjivani
<span title="2018-05-31">2018</span> <i title="International Journal for Research in Applied Science and Engineering Technology (IJRASET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hsp44774azcezeyiq4kuzpfh5a" style="color: black;">International Journal for Research in Applied Science and Engineering Technology</a> </i> &nbsp;
In our proposed study we introduce a hybrid firefly algorithm based regression test case prioritization.  ...  One of the most critical activities of software development and maintenance, known as regression testing. Regression testing has been proved to be crucial stage of software testing.  ...  In the regression testing we get already designed test suite for reuse and regression test selection technique may help us to select appropriate test cases from these test suite.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2018.5216">doi:10.22214/ijraset.2018.5216</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fmw5j3crxna65k67misc5e5tj4">fatcat:fmw5j3crxna65k67misc5e5tj4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209181445/http://ijraset.com/fileserve.php?FID=17268" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d0/47/d047d093504b7fcab3d1bdc038a73bbb89102c6f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2018.5216"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Solar Thermal Collector Output Temperature Prediction by Hybrid Intelligent Model for Smartgrid and Smartbuildings Applications and Optimization

José-Luis Casteleiro-Roca, Pablo Chamoso, Esteban Jove, Alfonso González-Briones, Héctor Quintián, María-Isabel Fernández-Ibáñez, Rafael Alejandro Vega Vega, Andrés-José Piñón Pazos, José Antonio López Vázquez, Santiago Torres-Álvarez, Tiago Pinto, Jose Luis Calvo-Rolle
<span title="2020-07-05">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
A hybrid intelligent model has been developed by combining clustering and regression methods such as neural networks, polynomial regression, and support vector machines.  ...  Moreover, combining different regression methods for each cluster provides better results than when a global model of the whole dataset is used.  ...  Validation Results With the aim of selecting the best hybrid configuration (the optimal clusters number), a test has been performed using the testing dataset.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10134644">doi:10.3390/app10134644</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oyb6gomnjbdijgln42v4omgnmm">fatcat:oyb6gomnjbdijgln42v4omgnmm</a> </span>
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Efficient Model Selection for Moisture Ratio Removal of Seaweed Using Hybrid Of Sparse And Robust Regression Analysis

Anam Javaid, Mohd. Tahir Ismail, M.K.M. Ali
<span title="2021-09-03">2021</span> <i title="Pakistan Journal of Statistics and Operation Research"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xoyy36qwhrh3vexanflvx76xia" style="color: black;">Pakistan Journal of Statistics and Operation Research</a> </i> &nbsp;
Comparison of proposed techniques are made with ridge regression and OLS (ordinary least square) after multicollinearity test and coefficient test.  ...  MAPE (mean absolute percentage error) is calculated for the efficient selected model to forecast.  ...  Efficient Model Selection For Moisture Ratio Removal Of Seaweed Using Hybrid Of Sparse And Robust Regression Analysis 673 Selection For Moisture Ratio Removal Of Seaweed Using Hybrid Of Sparse And Robust  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18187/pjsor.v17i3.3641">doi:10.18187/pjsor.v17i3.3641</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tg4hfvzf7vbybnbxllggtraney">fatcat:tg4hfvzf7vbybnbxllggtraney</a> </span>
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A systematic literature study of regression test case prioritization approaches

Omdev Dahiya, Kamna Solanki
<span title="2018-09-16">2018</span> <i title="Science Publishing Corporation"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/piy2nrvrjrfcfoz5nmre6zwa4i" style="color: black;">International Journal of Engineering &amp; Technology</a> </i> &nbsp;
For it, studies related to test case prioritization in regression testing from the year 2004 to 2018 are analyzed by dividing this time period into three slots of five years each. 36 studies were selected  ...  Regression testing is about running the entire test ensemble again to ensure that amendments do not negatively affect the system.  ...  Silva et al. have proposed a hybrid approach for regression test case selection and prioritization.  ... 
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<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190429021552/https://sciencepubco.com/index.php/ijet/article/download/15805/9168" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/69/35/6935cf9322679085c5bfbc673bf88693578890e0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14419/ijet.v7i4.15805"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>
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