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Enhancement in K-mean Clustering to Analyze Software Architecture using Normalization

Shilpa Sharma, Jyoti Godara
2015 International Journal of Computer Applications  
For increasing the software architecture analysis, the K-MEAN clustering will be used which is more efficient then the genetic clustering.  ...  In the past times the algorithm of genetic had been proposed to cluster the functions of similar properties. In the genetic algorithms, all the clustering values are depends on the chromosomes.  ...  The main function of the clustering technique is speedy and efficient recovery of software architecture by using fuzzy clustering technique.  ... 
doi:10.5120/21230-3973 fatcat:enoz6qdy4ngohdcojwbvdnwmmq

Software Architecture Module-View Recovery Using Cluster Ensembles

Choongki Cho, Ki-Seong Lee, Minsoo Lee, Chan-Gun Lee
2019 IEEE Access  
In this paper, we propose to take advantage of cluster ensembles for software architecture recovery. Our experiments on five open-source projects are reported and the results are analyzed.  ...  We argue that most previous studies have not considered cluster ensembles but relied on a single clustering algorithm.  ...  ACKNOWLEDGMENT A preliminary version of this paper appeared in Choongki Cho's Master thesis, ''Software Architecture Module-View Recovery via Cluster Ensembles,'' Department of Computer Science and Engineering  ... 
doi:10.1109/access.2019.2920427 fatcat:wkaz7taozjg6nijqagbglnk354

Software Architecture Recovery Techniques

2020 International Journal of Engineering and Advanced Technology  
We will use some software testing tools to compare these algorithms (software recovery techniques) with each project.  ...  It can be a library of a third-party organization. These dependencies effect the application but it is very hard to makeany software without using these external dependencies.  ...  This paper compares the efficiency of three different software recovery techniques namely, ACDC (Algorithm for Comprehensive Driven Clustering), LIMBO and WCA (Weighted Combined Algorithm).  ... 
doi:10.35940/ijeat.d8018.049420 fatcat:cnkjphq2qvapferxag2qm3stbi

Software Module Clustering Using Hybrid SocioEvolutionary Algorithms

Kawal Jeet, Renu Dhir
2016 International Journal of Information Engineering and Electronic Business  
This paper examines the use of novel evolutionary imperialist competitive algorithms, genetic algorithms and their combinations for software clustering.  ...  Software clustering is one of the powerful techniques which could be used to cluster large software systems into smaller manageable subsystems containing modules of similar features.  ...  ACKNOWLEDGMENT The authors are grateful to Spiros Mancoridis for providing both the Bunch tool and the MDGs used in this paper. We are also pleased to thank Mr.  ... 
doi:10.5815/ijieeb.2016.04.06 fatcat:7zovb6z5qfbnhkm6u36i3cqpoi


Dheepigaa V S .
2015 International Journal of Research in Engineering and Technology  
It poorly identifies the effective configuration space. So the cost required for testing get increased. In this work, techniques includes hierarchical clustering algorithm and ripper algorithm.  ...  Software systems are highly configurable. Although there are lots of advantages in improving the configuration, it is difficult to test unique errors hiding in configurations.  ...  INTRODUCTION A software system is a system of inter-communicating components based on software forming part of a computer system (a combination of hardware and software).  ... 
doi:10.15623/ijret.2015.0403095 fatcat:jk6rtt4gzff4zfq4wwkpzvhhvm

Clustering Techniques in Data Mining For Improving Software Architecture: A Review

Parneet Kaur, Kamaljit Kaur
2016 International Journal of Computer Applications  
This paper also gives comparative study of clustering techniques and addresses benefits and limitations of clustering techniques.  ...  There are many clustering techniques for the improvement of architecture which are discussed in this paper.  ...  Fuzzy clustering technique is used to achieve the main function of clustering technique which is used for efficient and speedy recovery of software architecture.  ... 
doi:10.5120/ijca2016909303 fatcat:j4dcqwltpndspj2rqanlr2ocxy

Using Machine Learning and Information Retrieval Techniques to Improve Software Maintainability [chapter]

Anna Corazza, Sergio Di Martino, Valerio Maggio, Alessandro Moschitti, Andrea Passerini, Giuseppe Scanniello, Fabrizio Silvestri
2013 Communications in Computer and Information Science  
The software architecture plays a fundamental role in the comprehension and maintenance of large and complex systems.  ...  Software architecture recovery (SAR) techniques aim at extracting architectural information from the source code by often involving clustering of program artifacts analyzed at different levels of abstraction  ...  [26] : (i) the level of granularity for the software entities to consider in the clustering; (ii) the information used to compare software entities, and (iii) the clustering algorithm to be exploited  ... 
doi:10.1007/978-3-642-45260-4_9 fatcat:ony773z7tzaw3obzch5ulcgxlm

Discovering Fails in Software Projects Planning Based on Linguistic Summaries [chapter]

Iliana Pérez Pupo, Pedro Y. Piñero Pérez, Roberto García Vacacela, Rafael Bello, Luis Alvarado Acuña
2020 Lecture Notes in Computer Science  
But the literature does no report investigations concerned with combination linguistic data summarization techniques and outliers' mining applied to planning of software project.  ...  Authors consider that the combination of outliers' mining and linguistic data summarization support project managers to decision-making process in the software project planning.  ...  The following is a hybrid algorithm that combines clustering techniques with distance-based methods to detect outliers and to build linguistic summaries from the outliers detected.  ... 
doi:10.1007/978-3-030-52705-1_27 fatcat:vevbmi75trahzfy4dmcppes5nq

Towards Predicting Software Defects with Clustering Techniques

Waheeda Almayyan
2021 International Journal of Artificial Intelligence & Applications  
Our aim was to evaluate the performance of clustering techniques with feature selection schemes to address the problem of software defect prediction problem.  ...  We analysed the National Aeronautics and Space Administration (NASA) dataset benchmarks using three clustering algorithms: (1) Farthest First, (2) X-Means, and (3) selforganizing map (SOM).  ...  Farthest First Clustering Technique Farthest First is a unique clustering algorithm that combines both hierarchical and distance-based clustering.  ... 
doi:10.5121/ijaia.2021.12103 fatcat:cnozclryubfd7lcaqwm6g2nxc4

Using Computing Intelligence Techniques to Estimate Software Effort

Jin-Cherng Lin, Yueh-Ting Lin, Han-Yuan Tzeng, Yan-Chin Wang
2013 International Journal of Software Engineering & Applications  
This research uses some computing intelligence techniques, such as Pearson product-moment correlation coefficient method and one-way ANOVA method to select key factors, and K-Means clustering algorithm  ...  In the IT industry, precisely estimate the effort of each software project the development cost and schedule are count for much to the software company.  ...  Performance indicators in Ward clustering and Differential Evolution Algorithm of Model 2 In model 2, we use Ward clustering method and Differential Evolution Algorithm to estimate the software project  ... 
doi:10.5121/ijsea.2013.4104 fatcat:xecg7zlalzcpllgavvxp4ioyvq

E-SC4R: Explaining Software Clustering for Remodularisation [article]

Alvin Jian Jia Tan, Chun Yong Chong, Aldeida Aleti
2021 arXiv   pre-print
Software clustering is often used as a remodularisation and architecture recovery technique to help recover a semantic representation of the software design.  ...  clustering algorithms using software features extracted from the code.  ...  Acknowledgement This work was carried out within the framework of the research project FRGS/1/2018/ICT01/MUSM/03/1 under the Fundamental Research Grant Scheme provided by the Ministry of Education, Malaysia  ... 
arXiv:2107.01766v2 fatcat:rzpblqytg5h5hfimwf7rs3jhzu

A Subtractive Clustering Based Approach For Early Prediction Of Fault Proneness In Software Modules

Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur
2010 Zenodo  
Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach.  ...  In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems.  ...  and requirement metric data and obtain the combined data. • Analyze, refine metrics and normalize the metric values. • Find the suitable algorithm for clustering of the software components into faulty/  ... 
doi:10.5281/zenodo.1331264 fatcat:v3vesdkhajetpi65vvnv6sh33a

August 2016 VOLUME 5, ISSUE 8, AUGUST 2016 5th Generation Wi-Fi Shatha Ghazal, Raina S Alkhlailah Abstract | PDF with Text | DOI: 10.17148/IJARCCE.2016.5801 ECG Arrhythmia Detection Using Choi-Williams Time-Frequency Distribution and Artificial Neural Network Sanjit K. Dash, G. Sasibhushana Rao Abstract | PDF with Text | DOI: 10.17148/IJARCCE.2016.5802 Data Security using RSA Algorithm in Cloud Computing Santosh Kumar Singh, Dr. P.K. Manjhi, Dr. R.K. Tiwari Abstract | PDF with Text | DOI: 10.17148/IJARCCE.2 ...

Abdullah K K A, Robert A B C, Adeyemo A B
2016 IJARCCE  
This paper discussed query terms with semantic search for retrieval of web content using different semantic indexing techniques.  ...  This would derive search related terms in the retrieved result taking into consideration the advantages, limitations on each of the techniques.  ...  But [19] presented a concept-driven algorithm for clustering search results, the Lingo algorithm, which uses LSI techniques to separate search results into meaningful group but do not consider building  ... 
doi:10.17148/ijarcce.2016.5869 fatcat:ihbu5ekllnhqjbuw6yeetnin3q

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

Ms. Kale Sanjivani
2018 International Journal for Research in Applied Science and Engineering Technology  
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 this research, the K-means clustering algorithm will be used to separate the relevant test cases from irrelevant test cases. Relevant test cases denote the prioritized test cases.  ...  This set of prioritization algorithms has improved the efficiency of regression testing and guarantee testing adequacy, because only the modified and affected parts of software were tested.  ... 
doi:10.22214/ijraset.2018.5216 fatcat:fmw5j3crxna65k67misc5e5tj4

CLUBAS: An Algorithm and Java Based Tool for Software Bug Classification Using Bug Attributes Similarities

Naresh Kumar Nagwani, Shrish Verma
2012 Journal of Software Engineering and Applications  
The algorithm CLUBAS is an example of classification using clustering technique.  ...  CLUBAS is a hybrid algorithm, and is designed by using text clustering, frequent term calculations and taxonomic terms mapping techniques.  ...  The algorithm CLUBAS is designed using the technique of classification by clustering, in which first clustering is done using textual similarity of bug attributes and then proper labels are generated and  ... 
doi:10.4236/jsea.2012.56050 fatcat:6cjpwjntzbhf3alkg4bfp6ncw4
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