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Journal articles on the topic 'Software comparison'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Olyai, Alireza, and Reza Rezaei. "Analysis and Comparison of Software Product Line Frameworks." Journal of Software 10, no. 8 (August 2015): 991–1001. http://dx.doi.org/10.17706//jsw.10.8.991-1001.

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2

Sekhar, R. Poorna Chandra, and Dr G. Anjan Babu. "Comparison of Software Cost Estimation Techniques: An Overview." International Journal of Trend in Scientific Research and Development Volume-1, Issue-5 (August 31, 2017): 26–32. http://dx.doi.org/10.31142/ijtsrd2248.

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3

Gupta, Sanjali. "A Comparison between Various Software Cost Estimation Models." International journal of Emerging Trends in Science and Technology 03, no. 11 (November 22, 2016): 4771–76. http://dx.doi.org/10.18535/ijetst/v3i11.08.

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4

Kumar, Gottipalla Ashok. "Comparison Of Conventional Approach with Component Based Software Development." International Journal of Scientific Research 2, no. 2 (June 1, 2012): 141–42. http://dx.doi.org/10.15373/22778179/feb2013/47.

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5

Beck, Fabian, and Stephan Diehl. "Visual comparison of software architectures." Information Visualization 12, no. 2 (September 17, 2012): 178–99. http://dx.doi.org/10.1177/1473871612455983.

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Reverse engineering methods produce different descriptions of software architectures. In this article we address the task of exploring and comparing these descriptions. We present a novel visualization technique to compare architectures consisting of a decomposition of the software system and the dependencies among the code entities. This technique uses a visual representation of an adjacency matrix to provide a scalable analysis tool. Advanced layout features such as an automatic level of detail algorithm and sorting strategies improve the readability of the visualization. Using a case study, we show how this technique can be applied in practice.

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6

Mahalakshmi, R., and R. Saranya. "Comparison of Software Requirements Tools." Research Journal of Science and Technology 9, no. 2 (2017): 272. http://dx.doi.org/10.5958/2349-2988.2017.00049.3.

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7

Gonçales, Lucian José, Kleinner Farias, Toacy Cavalcante De Oliveira, and Murilo Scholl. "Comparison of Software Design Models." ACM Computing Surveys 52, no. 3 (July 27, 2019): 1–41. http://dx.doi.org/10.1145/3313801.

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8

Khan,et al., Ali Athar. "Comparison of Software Complexity Metrics." International Journal of Computing and Network Technology 4, no. 1 (January 1, 2016): 19–26. http://dx.doi.org/10.12785/ijcnt/040103.

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9

Eccarius, Petra. "Comparison of major software features." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (December 31, 2001): 299–300. http://dx.doi.org/10.1075/sll.4.1-2.21ecc.

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Eccarius, Petra. "Comparison of major software features." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (December 31, 2001): 299–300. http://dx.doi.org/10.1075/sll.4.12.21ecc.

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11

Zhang, Li, Xiao Dong Mu, Hai Jing Zhang, and Wei Song. "Comparison between Object-Oriented Software Testing and Traditional Software Testing." Applied Mechanics and Materials 411-414 (September 2013): 497–500. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.497.

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Object-oriented technology has been widely used in the area of computer software. However, traditional software testing techniques cannot perform effectively on object-oriented software. The differences between object-oriented software testing and traditional software testing are compared and elaborated from three aspects: testing model, testing software and testing cases.

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12

Levina, A. I., and A. V. Kubarskii. "Advantages of SaaS software in comparison with on-premises software." Scientific bulletin of the Southern Institute of Management, no. 4 (December 25, 2018): 89–94. http://dx.doi.org/10.31775/2305-3100-2018-4-89-94.

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Software-as-a-Service (SaaS) is becoming a popular outsourcing option for customers interested in paying for the right to access a standardized set of functions of the necessary software via the Internet. Due to the low cost of the service and the lack of high initial costs, the business becomes interested in using this technology. Software as a service allows you to significantly reduce the cost of IT services, to rethink the entire process of automating the business-processes of companies and creating software by eliminating high initial investments in infrastructure and its subsequent maintenance. Considering these advantages of SaaS over on-premises applications, business is increasingly talking about the possibility of a full transition to the use of SaaS services. In this paper, the concept of SaaS software, the architecture of this kind of applications, their distribution models and long-term use costs are analyzed, and this approach is compared with on-premises software in the above issues. Based on the analysis of actual data, recommendations were made on the topic of whether to abandon the usual set of technologies in favor of SaaS and which companies should take such actions.

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13

Alameer, Mohammed, and Thamer Alhussain. "Students' Engagement in Educational Software: A Comparison between Narrative and Traditional Styles." International Journal of Information and Education Technology 6, no. 4 (2016): 322–26. http://dx.doi.org/10.7763/ijiet.2016.v6.707.

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14

Petrarca, Alicia M., Aaron J. Lengel, and Mary F. Powers. "Comparison of patient assistance program software." American Journal of Health-System Pharmacy 68, no. 14 (July 15, 2011): 1331–38. http://dx.doi.org/10.2146/ajhp100512.

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15

Abdul Sattar, Saniu, Nimbal Pandita, and Prateek Upadhyay. "A Comparison on Software Quality Models." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 12 (January 3, 2018): 22. http://dx.doi.org/10.23956/ijarcsse.v7i12.479.

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Abstract. Quality that is identified independent of any measurable characteristics is defined as the capability to meet customer expectations, whether the requirements are explicit or not. A recent innovation in the systems area is the development of a set of mechanisms and models for evaluating quality. This article compares the design of a Quality Model with its factors and criteria Different quality models were studied: McCall, Boehm, FURPS, Dromey, and GEQUAMO in an attempt to identify the aspects present in these models that are deemed important in Software Quality. GEQUAMO software quality model is the best among the models compared, since it can be customizable as per requirement in a dynamic and a flexible way.

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16

Andro, Mathieu, Emmanuelle Asselin, and Marc Maisonneuve. "Digital libraries: Comparison of 10 software." Library Collections, Acquisitions, and Technical Services 36, no. 3-4 (January 2012): 79–83. http://dx.doi.org/10.1016/j.lcats.2012.05.002.

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17

Chandra, Vishal. "Comparison between Various Software Development Methodologies." International Journal of Computer Applications 131, no. 9 (December 17, 2015): 7–10. http://dx.doi.org/10.5120/ijca2015907294.

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18

Tiberti, Matteo, Elena Papaleo, Tone Bengtsen, Wouter Boomsma, and Kresten Lindorff-Larsen. "ENCORE: Software for Quantitative Ensemble Comparison." PLOS Computational Biology 11, no. 10 (October 27, 2015): e1004415. http://dx.doi.org/10.1371/journal.pcbi.1004415.

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19

Ferens, Daniel V., and Bryan A. Daly. "A Comparison of Software Scheduling Models." Journal of Parametrics 13, no. 1 (May 1993): 3–34. http://dx.doi.org/10.1080/10157891.1993.10462515.

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20

Erickson, Collin B., Bruce E. Ankenman, and Susan M. Sanchez. "Comparison of Gaussian process modeling software." European Journal of Operational Research 266, no. 1 (April 2018): 179–92. http://dx.doi.org/10.1016/j.ejor.2017.10.002.

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21

Viuff, Thomas, Xu Xiang, Bernt Johan Leira, and Ole Øiseth. "Software-to-Software Comparison of End-Anchored Floating Bridge Global Analysis." Journal of Bridge Engineering 25, no. 5 (May 2020): 04020022. http://dx.doi.org/10.1061/(asce)be.1943-5592.0001545.

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22

Singh, Vandana. "Comparison of technical support for open source software versus proprietary software." Proceedings of the American Society for Information Science and Technology 47, no. 1 (November 2010): 1–2. http://dx.doi.org/10.1002/meet.14504701437.

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23

Iyawa, Gloria E., Marlien E. Herselman, and Alfred Coleman. "Customer Interaction in Software Development: A Comparison of Software Methodologies Deployed in Namibian Software Firms." Electronic Journal of Information Systems in Developing Countries 77, no. 1 (November 2016): 1–13. http://dx.doi.org/10.1002/j.1681-4835.2016.tb00560.x.

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24

Field, Dawn, Edward J. Feil, and Gareth A. Wilson. "Databases and software for the comparison of prokaryotic genomes." Microbiology 151, no. 7 (July 1, 2005): 2125–32. http://dx.doi.org/10.1099/mic.0.28006-0.

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The explosion in the number of complete genomes over the past decade has spawned a new and exciting discipline, that of comparative genomics. To exploit the full potential of this approach requires the development of novel algorithms, databases and software which are sophisticated enough to draw meaningful comparisons between complete genome sequences and are widely accessible to the scientific community at large. This article reviews progress towards the development of computational tools and databases for organizing and extracting biological meaning from the comparison of large collections of genomes.

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25

Abdullah, Johari Yap, Abdul Manaf Abdullah, Helmi Hadi, Adam Husein, and Zainul Ahmad Rajion. "Comparison of STL skull models produced using open-source software versus commercial software." Rapid Prototyping Journal 25, no. 10 (November 11, 2019): 1585–91. http://dx.doi.org/10.1108/rpj-08-2018-0206.

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Purpose This paper aims to compare the automatic segmentation of medical data and conversion to stereolithography (STL) skull models using open-source software versus commercial software. Design/methodology/approach Both open-source and commercial software used automatic segmentation and post-processing of the data without user intervention, thus avoiding human error. Detailed steps were provided for comparisons and easier to be repeated by other researchers. The results of segmentation, which were converted to STL format were compared using geometric analysis. Findings STL skull models produced using open-source software are comparable with the one produced using commercial software. A comparison of STL skull model produced using InVesalius with STL skull model produced using MIMICS resulted in an average dice similarity coefficient (DSC) of 97.6 ± 0.04 per cent and Hausdorff distance (HD) of 0.01 ± 0.005 mm. Inter-rater study for repeatability on MIMICS software yielded an average DSC of 100 per cent and HD of 0. Social implications The application of open-source software will benefit the small research institutions or hospitals to produce and virtualise three-dimensional model of the skulls for teaching or clinical purposes without having to purchase expensive commercial software. It is also easily reproduceable by other researchers. Originality/value This study is one of the first comparative evaluations of an open-source software with propriety commercial software in producing accurate STL skull models. Inaccurate STL models can lead to inaccurate pre-operative planning or unfit implant.

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26

Jameel, Furqan, and Ibrahim Khan. "Comparison of Controllers in Software-Defined Networking." i-manager's Journal on Cloud Computing 2, no. 3 (July 15, 2015): 1–7. http://dx.doi.org/10.26634/jcc.2.3.4790.

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27

Kazim, Mohammad Mahtab. "Comparison of various software cost estimation models." Global Sci-Tech 10, no. 3 (2018): 132. http://dx.doi.org/10.5958/2455-7110.2018.00021.6.

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28

Dobránsky, Jozef, Rastislav Mikuš, and Juraj Ružbarský. "Comparison of Cooling Variants by Simulation Software." Advanced Materials Research 801 (September 2013): 75–80. http://dx.doi.org/10.4028/www.scientific.net/amr.801.75.

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This paper deals with the verification of thermoplastic flowing when manufacturing plastic products by injection moulding used in the consumer industry. An analysis was performed by Plastic Insight, which is used for the determination of flow properties of thermoplastic materials. A good knowledge of flow properties of these materials enables a very good starting position for the design of thermoplastic products made by the injection moulding technology [1,2]. The task of this simulation was the comparison of injection parameters of a mould, with and without cooling of channels. Simulated thermoplastic material is used for the manufacture of ribs in washing machine drums. The tested material was polypropylene.

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29

Vlachos, M., L. Berger, R. Mathelier, P. Agrafiotis, and D. Skarlatos. "SOFTWARE COMPARISON FOR UNDERWATER ARCHAEOLOGICAL PHOTOGRAMMETRIC APPLICATIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W15 (August 26, 2019): 1195–201. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w15-1195-2019.

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<p><strong>Abstract.</strong> This paper presents an investigation as to whether and how the selection of the SfM-MVS software affects the 3D reconstruction of submerged archaeological sites. Specifically, Agisoft Photoscan, VisualSFM, SURE, 3D Zephyr and Reality Capture software were used and evaluated according to their performance in 3D reconstruction using specific metrics over the reconstructed underwater scenes. It must be clarified that the scope of this study is not to evaluate specific algorithms or steps that the various software use, but to evaluate the final results and specifically the generated 3D point clouds. To address the above research issues, a dataset from the ancient shipwreck, laying at 45 meters below sea level, is used. The dataset is composed of 19 images having very small camera to object distance (1 meter), and 42 images with higher camera to object distance (3 meters) images. Using a common bundle adjustment for all 61 images, a reference point cloud resulted from the lower dataset is used to compare it with the point clouds of the higher dataset generated using the different photogrammetric packages. Following that, a comparison regarding the number of total points, cloud to cloud distances, surface roughness, surface density and a combined 3D metric was done to evaluate and see which one performed the best.</p>

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30

Oakes, T. R., T. Johnstone, K. S. Ores Walsh, L. L. Greischar, A. L. Alexander, A. S. Fox, and R. J. Davidson. "Comparison of fMRI motion correction software tools." NeuroImage 28, no. 3 (November 2005): 529–43. http://dx.doi.org/10.1016/j.neuroimage.2005.05.058.

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31

Cristescu, Marian Pompiliu, Eduard Alexandru Stoica, and Laurenţiu Vasile Ciovică. "The Comparison of Software Reliability Assessment Models." Procedia Economics and Finance 27 (2015): 669–75. http://dx.doi.org/10.1016/s2212-5671(15)01047-3.

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32

Abdullah, A., Z. Sun, N. Pongnapang, and K. H. Ng. "Comparison of computed tomography dose reporting software." Radiation Protection Dosimetry 151, no. 1 (December 7, 2011): 153–57. http://dx.doi.org/10.1093/rpd/ncr451.

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33

Van Milgen, J., R. Boston, R. Kohn, and J. Ferguson. "Comparison of available software for dynamic modeling." CrossRef Listing Of Deleted DOIs 45, Suppl. 1 (1996): 257–73. http://dx.doi.org/10.1051/rnd:19960642.

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34

Frederick, Linda J., and Michael J. Brantmayer. "A Comparison of NIOSH Lifting Equation Software." Ergonomics in Design: The Quarterly of Human Factors Applications 6, no. 3 (July 1998): 26–31. http://dx.doi.org/10.1177/106480469800600306.

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35

Tortelli, M., D. Rossi, G. Boggia, and L. A. Grieco. "ICN software tools: Survey and cross-comparison." Simulation Modelling Practice and Theory 63 (April 2016): 23–46. http://dx.doi.org/10.1016/j.simpat.2016.01.015.

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36

Biehlmaier, Oliver, Joachim Hehl, and Gabor Csucs. "Acquisition speed comparison of microscope software programs." Microscopy Research and Technique 74, no. 6 (November 17, 2010): 539–45. http://dx.doi.org/10.1002/jemt.20944.

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37

Van Milgen, J., R. Boston, R. Kohn, and J. Ferguson. "Comparison of available software for dynamic modeling." Annales de Zootechnie 45, Suppl. 1 (1996): 257–73. http://dx.doi.org/10.1051/animres:19960642.

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38

Stringfellow, C., C. D. Amory, D. Potnuri, A. Andrews, and M. Georg. "Comparison of software architecture reverse engineering methods." Information and Software Technology 48, no. 7 (July 2006): 484–97. http://dx.doi.org/10.1016/j.infsof.2005.05.007.

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39

Rice, Gareth, Roland Clift, and Richard Burns. "Comparison of currently available european LCA software." International Journal of Life Cycle Assessment 2, no. 1 (March 1997): 53–59. http://dx.doi.org/10.1007/bf02978725.

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40

Szyperski, Clemens. "Emerging component software technologies — a strategic comparison." Software - Concepts & Tools 19, no. 1 (March 1998): 2–10. http://dx.doi.org/10.1007/s003780050002.

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41

Ghanim, Wisam S., Omer K. Ahmed, and Obed M. Ali. "Gasoline Engine Simulation Software: A Comparison Review." IOP Conference Series: Materials Science and Engineering 1076, no. 1 (February 1, 2021): 012070. http://dx.doi.org/10.1088/1757-899x/1076/1/012070.

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42

Goodarzi Pour, D., H. Razmi, S. Jabedar Maralani, and S. Zeighami. "New software: comparison between three software programs for root canal length measurement." Dentomaxillofacial Radiology 37, no. 4 (May 2008): 228–31. http://dx.doi.org/10.1259/dmfr/16010494.

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43

Choudhary, Vidyanand. "Comparison of Software Quality Under Perpetual Licensing and Software as a Service." Journal of Management Information Systems 24, no. 2 (October 2007): 141–65. http://dx.doi.org/10.2753/mis0742-1222240206.

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44

Zuo, Jieyu, Yuan Gao, Nadia Bou-Chacra, and Raimar Löbenberg. "Evaluation of the DDSolver Software Applications." BioMed Research International 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/204925.

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When a new oral dosage form is developed, its dissolution behavior must be quantitatively analyzed. Dissolution analysis involves a comparison of the dissolution profiles and the application of mathematical models to describe the drug release pattern. This report aims to assess the application of the DDSolver, an Excel add-in software package, which is designed to analyze data obtained from dissolution experiments. The data used in this report were chosen from two dissolution studies. The results of the DDSolver analysis were compared with those obtained using an Excel worksheet. The comparisons among three different products obtained similarity factors(f2)of 23.21, 46.66, and 17.91 using both DDSolver and the Excel worksheet. The results differed when DDSolver and Excel were used to calculate the release exponent “n” in the Korsmeyer-Peppas model. Performing routine quantitative analysis proved to be much easier using the DDSolver program than an Excel spreadsheet. The use of the DDSolver program reduced the calculation time and has the potential to omit calculation errors, thus making this software package a convenient tool for dissolution comparison.

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45

Rawat, Shubham, Nupur Goyal, and Mangey Ram. "Software reliability growth modeling for agile software development." International Journal of Applied Mathematics and Computer Science 27, no. 4 (December 20, 2017): 777–83. http://dx.doi.org/10.1515/amcs-2017-0054.

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AbstractThe frequent incremental release of software in agile development impacts the overall reliability of the product. In this paper, we propose a generic software reliability model for the agile process, taking permanent and transient faults into consideration. The proposed model is implemented using the NHPP (non-homogenous Poisson process) and the Musa model. The comparison of the two implementations yields an effective, empirical and reliable model for agile software development.

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46

Ochieng, Peter, Waweru Mwangi, and Solomon Mwanjele Mwgha. "Software Size Estimation in Incremental Software Development based on Improved Pairwise Comparison Matrices." International Journal of Computer Applications 93, no. 5 (May 16, 2014): 29–39. http://dx.doi.org/10.5120/16213-5519.

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47

Harris, P. M., I. M. Smith, C. Wang, C. Giusca, and R. K. Leach. "Software measurement standards for areal surface texture parameters: part 2—comparison of software." Measurement Science and Technology 23, no. 10 (September 11, 2012): 105009. http://dx.doi.org/10.1088/0957-0233/23/10/105009.

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48

Muravyov, Sergey V., Irina A. Marinushkina, and Diana D. Garif. "Numerical experimental investigation of comparison data evaluation method using preference aggregation." ACTA IMEKO 6, no. 1 (April 25, 2017): 20. http://dx.doi.org/10.21014/acta_imeko.v6i1.408.

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<p class="Abstract">An integrated software for experimental testing preference aggregation method for interlaboratory comparison data processing is presented. The data can be obtained by a Monte-Carlo simulation and/or taken from real comparisons. Numerical experimental investigations with the software have shown that, as against traditional techniques of interlaboratory comparison data processing, the preference aggregation method provides a robust comparison reference value to be closer to a nominal value.</p>

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49

Olyai, Alireza, and Reza Rezaei. "Analysis and Comparison of Software Product Line Frameworks." Journal of Software 10, no. 8 (2015): 991–1001. http://dx.doi.org/10.17706/jsw.10.8.991-1001.

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50

Wang, Ruo Hong. "Professional Software Analysis and Comparison for Graphic Design." Applied Mechanics and Materials 644-650 (September 2014): 3170–73. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3170.

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Contacting with the development of the society, the world is increasingly close, the Internet has become an inseparable part of modern society, and the new century must rely on the powerful computer information technology to better development. The continuous renewal of network, the rapid development of computer technology, computer graphic design industries widely used. Application in the field of generalized naturally shows the importance of computer graphic design, further shows the importance of studying graphic design knowledge. Present and future society requires high-quality high-cultural level of computer graphic design talent, so graphic designers must be skilled to master the operation and application of computer design software and technical skills.

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