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The strength of random search on automated program repair

Yuhua Qi, Xiaoguang Mao, Yan Lei, Ziying Dai, Chengsong Wang
2014 Proceedings of the 36th International Conference on Software Engineering - ICSE 2014  
) and efficiency (requiring fewer test case executions), justifying the stronger strength of random search over genetic programming.  ...  Although GenProg and Par have shown their strong ability of fixing real-life bugs in nontrivial programs, to what extent GenProg and Par can benefit from genetic programming, used by them to guide the  ...  Specifically for GenProg, the fitness of each candidate patch is computed by counting the weighted number of passing test cases; the number is used to measure how close a candidate patch is to the valid  ... 
doi:10.1145/2568225.2568254 dblp:conf/icse/QiMLDW14 fatcat:ypziwjbktjfmhdikmhurxqex2y

Genetic Synthesis of Concurrent Code Using Model Checking and Statistical Model Checking [chapter]

Lei Bu, Doron Peled, Dachuan Shen, Yuan Zhuang
2018 Lecture Notes in Computer Science  
A deficiency of model checking based GP is that it uses a rather limited number of fitness values, based on a small number of modes for each verified specification property (e.g., satisfies, does not satisfy  ...  We describe here the use of a combination of model checking and statistical model checking for calculating the fitness required by GP, where the fitness is calculated based on statistical model checking  ...  We used a hybrid approach, where we used statistical model checking for most of the duration of the genetic process, but involved model checking at the later part of the genetic process to certify the  ... 
doi:10.1007/978-3-319-94111-0_16 fatcat:tcyyg6sjnncwbaz6ngzh4kswpu

A genetic approach to statistical disclosure control

Jim E. Smith, Alistair R. Clark, Andrea T. Staggemeier
2009 Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09  
The analysis of the results presented in Table III have clearly shown that in this case using a genetic algorithm outperforms using local search.  ...  However even though the number of groups was reduced to 20 and it was allowed to run for up to 24 hours it was only able to make a limited number of calls to the fitness function which in turn limited  ... 
doi:10.1145/1569901.1570118 dblp:conf/gecco/SmithCS09 fatcat:hwsmvkka3nas7e7cwhz7iuw7fm

A Genetic Approach to Statistical Disclosure Control

Jim E. Smith, Alistair R. Clark, Andrea T. Staggemeier, Martin C. Serpell
2012 IEEE Transactions on Evolutionary Computation  
The analysis of the results presented in Table III have clearly shown that in this case using a genetic algorithm outperforms using local search.  ...  However even though the number of groups was reduced to 20 and it was allowed to run for up to 24 hours it was only able to make a limited number of calls to the fitness function which in turn limited  ... 
doi:10.1109/tevc.2011.2159271 fatcat:4jggzcap4rfavmmxpqe63bm7e4

Bounded rationality in agent‐based models: experiments with evolutionary programs

S. M. Manson
2006 International Journal of Geographical Information Science  
This paper examines the use of evolutionary programming in agent-based modeling to implement the theory of bounded rationality.  ...  This paper reports on how changing parameters in one variant of evolutionary programming, genetic programming, affects the representation of bounded rationality in software agents.  ...  In this case, a population in the range of 200 to 300 programs is the lowest realistic number, as smaller populations do not converge well on useful strategies.  ... 
doi:10.1080/13658810600830566 fatcat:qhveuvej6veijoagxraub7l254

Gene Expression Synthesis

Alo Allik
2014 Proceedings of the SMC Conferences  
Acknowledgments This research was partly funded by the University of Hull 80th Anniversary PhD Scholarship.  ...  The persistence of relatively high but static maximum scores also underlines the limitations of the statistical fitness functions used in the experiments.  ...  As in any other evolutionary programming model, the most important and challenging component in GEP is the design of the fitness cases as this is what drives the fitness of the population and ultimately  ... 
doi:10.5281/zenodo.850872 fatcat:emgx4llpevasffoz4uqk5swqdu

A Quantitative Analysis of Memory Usage for Agent Tasks [chapter]

DaeEun Kim
2008 Frontiers in Evolutionary Robotics  
An example of genetic programming result (a) evolved S-expression (n t =12, n f =4) (b) converted FSM In the first experiment, a varying number of terminal nodes were tested by using the number of terminal  ...  If the number of leaf nodes in a new tree exceeds the limit, the tree is mutated until the limit condition is satisfied.  ...  Since directly using EC to generate a program of complex behaviors is often very difficult, a number of extensions to basic EC are proposed in this book so as to solve these control problems of the robot  ... 
doi:10.5772/5458 fatcat:lju6msvfpva7tixpulht2kd33q

A Many Threaded CUDA Interpreter for Genetic Programming [chapter]

W. B. Langdon
2010 Lecture Notes in Computer Science  
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the whole GP population of 1 4 million reverse polish notation (RPN) expressions on graphics cards and nVidia  ...  Using sub-machine code tree GP a sustain peak performance of 665 billion GP operations per second (10,000 speed up) and an average of 22 peta GP ops per day is reported for a single GPU card on a Boolean  ...  Speed Performance depends both on the number of fitness cases run in parallel by the interpreter (nparallel) and the the number of copies of the interpreter run in parallel per multiprocessor (block size  ... 
doi:10.1007/978-3-642-12148-7_13 fatcat:sxjl62hkmfdizd6zq2blybrc4y

PhysicsGP: A Genetic Programming approach to event selection

Kyle Cranmer, R. Sean Bowman
2005 Computer Physics Communications  
We present a novel multivariate classification technique based on Genetic Programming.  ...  We calculate the Vapnik-Chervonenkis dimension of this class of learning machines and consider a practical example: the search for the Standard Model Higgs Boson at the LHC.  ...  Acknowledgments This work was supported by a graduate research fellowship from the National Science Foundation and US Department of Energy Grant DE-FG0295-ER40896.  ... 
doi:10.1016/j.cpc.2004.12.006 fatcat:34avwjziybd4hla4wyukkpal2m

Forecasting Models of the Coronavirus (COVID-19) Cumulative Confirmed Cases Using a Hybrid Genetic Programming Method

Konstantinos Salpasaranis, Vasilios Stylianakis
2020 European Journal of Engineering Research and Science  
This paper presents the implementation of a hybrid Genetic Programming (hGP) method in finding fitting models of the Coronavirus (COVID 19) for the cumulative confirmed cases in China for the first saturation  ...  The specific hGP method encapsulates the use of some well-known diffusion models for forecasting purposes, epidemiological models and produces time dependent models with high performance statistical indices  ...  TABLE 1 : 1 PROGRAM FITTING PARAMETERS OF MODIFIED GP Fitting Parameters of modified hGP Program Maximum Number of Generations Evaluation Function Precision coefficient for candidates value  ... 
doi:10.24018/ejers.2020.5.12.2129 fatcat:lq6fidjlprb4jkg4gc5qpg36u4

Evaluating the potential of polygenic risk score to improve colorectal cancer screening

Coral Arnau-Collell, Anna Díez-Villanueva, Beatriz Bellosillo, Josep M. Augé, Jenifer Muñoz, Elisabet Guinó, Leticia Moreira, Anna Serradesanferm, Àngels Pozo, Isabel Torà-Rocamora, Laia Bonjoch, Gemma Ibáñez-Sanz (+15 others)
2022 Cancer Epidemiology, Biomarkers and Prevention  
A 2-fold increase in CRC risk was observed for subjects in the highest decile of risk alleles ( {greater than or equal to} 65), compared to those in the first decile ( {less than or equal to} 54) (OR=2.22  ...  Conclusions: This is the first investigation analyzing PRS in a two-step CRC screening program. PRS could improve current CRC screening, most likely for higher at-risk subgroups.  ...  Word count: 4,177 Total number of figures and tables: 6 ACKNOWLEDGEMENTS We acknowledge the contribution of the CRIPREV consortium, which permitted to develop this study.  ... 
doi:10.1158/1055-9965.epi-22-0042 pmid:35511747 fatcat:h6c6xdj6afaernrnwi2agqdt5u

Memory analysis and significance test for agent behaviours

DaeEun Kim
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
We apply two types of memory-based control structures, Koza's genetic programming and finite state machines, to recognize the relevance of internal memory.  ...  Statistical significance test based on beta distribution differentiates the characteristics and performances of the two control structures.  ...  If the number of leaf nodes in a new tree exceeds the limit, the tree is mutated until the limit condition is satisfied.  ... 
doi:10.1145/1143997.1144025 dblp:conf/gecco/Kim06 fatcat:a4iwzv7yznebdgdfptiq6pl6dm

Using Genetic Algorithms in Integer Programming for Decision Support

Youcef Souar
2014 Academic Journal of Interdisciplinary Studies  
A local Mill shapes a suitable case to use Genetic Algorithms in Integer Programming as one of its application forms.  ...  At last we have concluded the efficiency of Genetic Algorithms in Integer Programming, and its superiority concerning characteristics, it also deserves to be used in more complicated problems and when  ...  specific number of generations, no change in the fitness or attaining a convergence value.  ... 
doi:10.5901/ajis.2014.v3n6p11 fatcat:juk3totidjhu5c5qtifxjadfmi

A Comparative Evaluation of Using Genetic Programming for Predicting Fault Count Data

Wasif Afzal, Richard Torkar
2008 2008 The Third International Conference on Software Engineering Advances  
This paper presents a comparative evaluation of traditional models and use of genetic programming (GP) for modeling software reliability growth based on weekly fault count data of three different industrial  ...  There have been a number of software reliability growth models (SRGMs) proposed in literature.  ...  The model's goodness of fit in our case was measured using Kolmogorov-Smirnov (K-S) test [12] .  ... 
doi:10.1109/icsea.2008.9 dblp:conf/icsea/AfzalT08 fatcat:ro52rpqclbdurirpqkid77lomq

Applications of genetic programming in cancer research

William P. Worzel, Jianjun Yu, Arpit A. Almal, Arul M. Chinnaiyan
2009 International Journal of Biochemistry and Cell Biology  
This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.  ...  In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and  ...  Programming Despite the advantages of GP, there are several limitations in its use.  ... 
doi:10.1016/j.biocel.2008.09.025 pmid:18929677 pmcid:PMC3298968 fatcat:hpsruvbpgjfznpxtle7g7so4m4
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