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Journal articles on the topic 'Software engineering – Mathematics'

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Published: 4 June 2021

Last updated: 2 February 2022

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1

Molina, J. A. López, and M. Trujillo. "Mathematica Software in Engineering Mathematics Classes." International Journal of Mechanical Engineering Education 33, no. 3 (July 2005): 244–50. http://dx.doi.org/10.7227/ijmee.33.3.6.

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In this paper we show the advantages of using Mathematica software in engineering mathematics classes through the study of an example problem concerning heat conduction in a slab. Firstly the problem is solved from the point of view of a parabolic model of heat conduction, and secondly from the viewpoint of a hyperbolic model.

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2

Hall, Anthony. "Software engineering mathematics." Science of Computer Programming 12, no. 2 (July 1989): 168–70. http://dx.doi.org/10.1016/0167-6423(89)90045-2.

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3

Hamlet, Dick. "Mathematics, Computer Science, Software Engineering." Electronic Notes in Theoretical Computer Science 40 (March 2001): 186. http://dx.doi.org/10.1016/s1571-0661(05)80044-1.

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4

Dougherty, John P. "MATH COUNTSWhere mathematics meets software engineering." ACM Inroads 8, no. 3 (July 28, 2017): 13–15. http://dx.doi.org/10.1145/3123734.

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5

Hamlet, D. "Science, Mathematics, Computer Science, Software Engineering." Computer Journal 55, no. 1 (September 12, 2011): 99–110. http://dx.doi.org/10.1093/comjnl/bxr090.

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6

Ramasamy, Subburaj. "Computational Mathematics for Software Reliability Engineering." Journal of Combinatorics, Information & System Sciences 44, no. 1-4 (December 30, 2020): 217–44. http://dx.doi.org/10.32381/jciss.2019.44.1-4.12.

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7

Li, Tun, Wanwei Liu, Juan Chen, Xiaoguang Mao, and Xinjun Mao. "Towards connecting discrete mathematics and software engineering." Tsinghua Science and Technology 25, no. 3 (June 2020): 325–35. http://dx.doi.org/10.26599/tst.2019.9010012.

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8

Gonthier, Georges. "Engineering mathematics." ACM SIGPLAN Notices 48, no. 1 (January 23, 2013): 1–2. http://dx.doi.org/10.1145/2480359.2429071.

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9

Boute, R. "Supertotal function definition in mathematics and software engineering." IEEE Transactions on Software Engineering 26, no. 7 (July 2000): 662–72. http://dx.doi.org/10.1109/32.859534.

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10

Tremblay, G. "Formal methods: mathematics, computer science or software engineering?" IEEE Transactions on Education 43, no. 4 (2000): 377–82. http://dx.doi.org/10.1109/13.883345.

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11

Notkin, David. "Software, Software Engineering and Software Engineering Research: Some Unconventional Thoughts." Journal of Computer Science and Technology 24, no. 2 (March 2009): 189–97. http://dx.doi.org/10.1007/s11390-009-9217-4.

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12

Li, Juan, and Bin Chen. "Military software safety engineering." Journal of Interdisciplinary Mathematics 21, no. 5 (July 4, 2018): 1133–37. http://dx.doi.org/10.1080/09720502.2018.1493042.

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13

Lohgheswary, N., Z. M. Nopiah, E. Zakaria, A. A. Aziz, and S. Salmaliza. "Review on the usage of Software in Engineering Mathematics." Journal of Engineering and Applied Sciences 14, no. 20 (October 31, 2019): 7485–89. http://dx.doi.org/10.36478/jeasci.2019.7485.7489.

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14

Dimitrov, Diyan M., and Stoyan D. Slavov. "Application of GeoGebra software into teaching mechanical engineering courses." MATEC Web of Conferences 178 (2018): 07008. http://dx.doi.org/10.1051/matecconf/201817807008.

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Mechanics courses traditionally characterize with a rather low percentage of passing students. Dynamic mathematical packages like GeoGebra are widely used nowadays for teaching mathematics, but its interactive capabilities can be used for simulation of different physical phenomena. In this article few interactive applets for Static, Dynamic, Strength of Materials and Theory of Mechanisms and Machines courses, are presented. An experiment with comparison of the test results of two group of students after the exercise beam about internal forces, shows that group trained with GeoGebra applets have significantly higher mean result.

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15

Cody, W. J., and Webb Miller. "The Engineering of Numerical Software." Mathematics of Computation 47, no. 175 (July 1986): 379. http://dx.doi.org/10.2307/2008110.

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16

Karamyshev, Anton N., and Zhanna I. Zaytseva. "“MATHEMATICA” IN TEACHING STUDENTS MATHEMATICS." Práxis Educacional 15, no. 36 (December 4, 2019): 610. http://dx.doi.org/10.22481/praxisedu.v15i36.5937.

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The relevance of the topic of the article is due to the process of modernization of higher mathematical education in Russia, which has led to a significant change in curricula and the need to look for ways and forms of training that would allow students to learn the necessary material within the time granted for studying, while obtaining the maximum necessary amount of skills, knowledge, and competencies. The objective of the article is to justify the ways and principles of the development and implementation of new pedagogical and information technologies in the educational process, the organization of professional education of students in technical areas based on the integration of mathematics and computer science. The leading method of the study of this problem is the methodological analysis and subsequent synthesis, which, by analyzing the didactic content of the sections in mathematics and the possibilities of the computer mathematical environment called Mathematica, reveals the necessary methods and ways of developing and using modern computer technologies in the mathematical education of engineering students. It is proved that one of the main tools for implementing the methods for solving the indicated problem should be considered a computer, namely, the mathematical environment called Mathematica, and the basic principles of its systemic implementation in the educational process of the university have been identified. The materials of the article may be useful to teachers of mathematical disciplines of higher educational institutions, the computer programs and pedagogical software products created in Mathematica can serve as models for the development of similar pedagogical software products.

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17

Zalewski, Janusz. "Aerospace software engineering." Control Engineering Practice 3, no. 9 (September 1995): 1349–50. http://dx.doi.org/10.1016/0967-0661(95)90053-5.

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18

Su, Yang, Fan Li, Sheng-ming Hu, and Ping Chen. "Aspect-oriented software reverse engineering." Journal of Shanghai University (English Edition) 10, no. 5 (October 2006): 402–8. http://dx.doi.org/10.1007/s11741-006-0081-y.

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19

Dyke, P. P. G. "Hydrosoft '86: Hydraulic engineering software." Applied Mathematical Modelling 12, no. 3 (June 1988): 347–48. http://dx.doi.org/10.1016/0307-904x(88)90048-0.

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20

Cross, M., A. O. Moscardini, and B. A. Lewis. "Software engineering methodologies for scientific and engineering computation." Applied Mathematical Modelling 10, no. 5 (October 1986): 376–85. http://dx.doi.org/10.1016/0307-904x(86)90097-1.

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21

King, Trevor. "Introduction to Formal Methods for Software Engineering." Measurement and Control 26, no. 1 (February 1993): 19–21. http://dx.doi.org/10.1177/002029409302600105.

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This paper describes what is meant by formal methods for software engineering. It is intended for the non-mathematical reader, and a simple formal specification is presented. The process of formal specification, development and proof is described briefly. Finally the benefits and limitations of formal methods are summarized.

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22

French, Allen C. "Software engineering applied to programmable controller software design." ISA Transactions 29, no. 2 (January 1990): 23–32. http://dx.doi.org/10.1016/0019-0578(90)90060-x.

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23

Friske, Mel. "Teaching Proofs: A Lesson from Software Engineering." American Mathematical Monthly 92, no. 2 (February 1985): 142. http://dx.doi.org/10.2307/2322651.

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24

Friske, Mel. "Teaching Proofs: A Lesson from Software Engineering." American Mathematical Monthly 92, no. 2 (February 1985): 142–44. http://dx.doi.org/10.1080/00029890.1985.11971560.

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25

Maureen, Hopcroft, and Goodland Michael. "ERP Implementation the Blindspot in Software Engineering." Journal of Algorithms & Computational Technology 4, no. 4 (December 2010): 481–94. http://dx.doi.org/10.1260/1748-3018.4.4.481.

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26

Gray, Michael A. "Sage: A New Mathematics Software System." Computing in Science & Engineering 10, no. 6 (November 2008): 72–75. http://dx.doi.org/10.1109/mcse.2008.154.

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27

Abate, Marcey. "Statistical Methods in Software Engineering." Technometrics 43, no. 1 (February 2001): 108. http://dx.doi.org/10.1198/tech.2001.s563.

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28

Mills, H. D. "The management of software engineering, Part I: Principles of software engineering." IBM Systems Journal 38, no. 2.3 (1999): 289–95. http://dx.doi.org/10.1147/sj.382.0289.

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29

Smith, A. M., and D. L. Dilaura. "Software Tools for Engineering Dark Skies." International Astronomical Union Colloquium 112 (1991): 71–76. http://dx.doi.org/10.1017/s0252921100003729.

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ABSTRACTAtmospheric scattering of outdoor nighttime electric illumination produces the principal component of background sky luminance that seriously affects ground-based optical astronomy. The sources for this scattering are Tight emitted skyward directly from luminaires, and light reflected off the ground and other illuminated objects. Careful illumination engineering can thus significantly reduce background sky luminance in two ways: 1) by providing outdoor electric lighting equipment that controls the directions in which light is emitted, and; 2) by proper design of outdoor lighting systems which make efficient use of the east amount of light. Recent developments in applied mathematics and computer software have produced computational tools that are being used to design lighting equipment and lighting systems. The software system for luminaire design significantly reduces the cost of this process by eliminating the need for extensive prototyping and provides for inexpensive experimentation with new designs. The system for outdoor lighting calculations permits the design of highly controlled lighting systems that eliminate glare and upward directed light while providing light appropriate for the visual task. These two software systems are described, along with examples of their use in areas that directly affect astronomical observations.

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30

Sollero, P. "Mathematica: A system for doing mathematics by computer, 2nd edition." Advances in Engineering Software 14, no. 4 (January 1992): 306. http://dx.doi.org/10.1016/0965-9978(92)90016-9.

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31

., Gunarto. "PELATIHAN MENGGUNAKAN SOFTWARE MATHCAD BAGI MAHASISWA PROGRAM STUDI TEKNIK MESIN UNIVERSITAS MUHAMMADIYAH PONTIANAK." Jurnal Buletin Al-Ribaath 15, no. 1 (October 1, 2018): 1. http://dx.doi.org/10.29406/br.v15i1.1120.

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The purpose of this community service was to train students of Mechanical Engineering Program University of Muhammadiyah Pontianak in using MATHCAD software. This training aims to support the courses of Basic Calculus, Advanced Calculus, Basic Engineering Mathematics, Advanced Engineering Mathematics and to improve the ability of Mechanical Engineering students about software MATHCAD. The program included preparation, training, and reporting. As the program ended, understanding of training participants in using this software is able to apply independently by direct practice with MATHCAD software properly. Keywords: engineering, MATHCAD, mathematics, software, training

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32

Chen, Feng Xin. "Research of Scientific Computing in the Engineering Linear Algebra Teaching." Applied Mechanics and Materials 333-335 (July 2013): 2218–21. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.2218.

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In this paper, we use some examples to discuss the necessity of using computer software to convert mathematical theory into numerical computations, which can combine classical theory with modern computing and make the abstract concept visualized, then give the future engineer a good foundation for further studies in mathematics as well as other subjects.

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33

Rasheed, Aqsa, Bushra Zafar, Tehmina Shehryar, Naila Aiman Aslam, Muhammad Sajid, Nouman Ali, Saadat Hanif Dar, and Samina Khalid. "Requirement Engineering Challenges in Agile Software Development." Mathematical Problems in Engineering 2021 (May 8, 2021): 1–18. http://dx.doi.org/10.1155/2021/6696695.

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Agile software development has large success rate due to its benefits and promising nature but natively where the size of the project is small. Requirement engineering (RE) is crucial as in each software development life cycle, “Requirements” play a vital role. Though agile provides values to customer’s business needs, changing requirement, and interaction, we also have to face impediments in agile, many of which are related to requirement challenges. This article aims to find out the challenges being faced during requirement engineering of agile projects. Many research studies have been conducted on requirement challenges which are somehow biased, no suggestions are given to improve the agile development process, and the research does not highlight large-scale agile development challenges. Hence, this article covers all the challenges discussed above and presents a comprehensive overview of agile models from requirement engineering perspective. The findings and results can be very helpful for software industry to improve development process as well as for researchers who want to work further in this direction.

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34

Karady, G. G., and K. Nigim. "Improve Learning Efficiency by Using General-Purpose Mathematics Software in Power Engineering." IEEE Power Engineering Review 22, no. 11 (2002): 54–55. http://dx.doi.org/10.1109/mper.2002.4311809.

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35

Karady, G. G., and K. A. Nigim. "Improve learning efficiency by using general purpose mathematics software in power engineering." IEEE Transactions on Power Systems 18, no. 3 (August 2003): 979–85. http://dx.doi.org/10.1109/tpwrs.2003.814847.

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36

Santos, María Jesús, Alejandro Medina, José Miguel Mateos Roco, and Araceli Queiruga-Dios. "Compartmental Learning versus Joint Learning in Engineering Education." Mathematics 9, no. 6 (March 20, 2021): 662. http://dx.doi.org/10.3390/math9060662.

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Sophomore students from the Chemical Engineering undergraduate Degree at the University of Salamanca are involved in a Mathematics course during the third semester and in an Engineering Thermodynamics course during the fourth one. When they participate in the latter they are already familiar with mathematical software and mathematical concepts about numerical methods, including non-linear equations, interpolation or differential equations. We have focused this study on the way engineering students learn Mathematics and Engineering Thermodynamics. As students use to learn each matter separately and do not associate Mathematics and Physics, they separate each matter into different and independent compartments. We have proposed an experience to increase the interrelationship between different subjects, to promote transversal skills, and to make the subjects closer to real work. The satisfactory results of the experience are exposed in this work. Moreover, we have analyzed the results obtained in both courses during the academic year 2018–2019. We found that there is a relation between both courses and student’s final marks do not depend on the course.

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37

Wongthongtham, P., E. Chang, T. Dillon, and I. Sommerville. "Development of a Software Engineering Ontology for Multisite Software Development." IEEE Transactions on Knowledge and Data Engineering 21, no. 8 (August 2009): 1205–17. http://dx.doi.org/10.1109/tkde.2008.209.

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38

POYET, PATRICE, ANNE-MARIE DUBOIS, and BERTRAND DELCAMBRE. "Artificial Intelligence Software Engineering in Building Engineering." Computer-Aided Civil and Infrastructure Engineering 5, no. 3 (September 1990): 167–205. http://dx.doi.org/10.1111/j.1467-8667.1990.tb00376.x.

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39

Pizlo, Zygmunt, Azriel Rosenfeld, and Isaac Weiss. "Visual Space: Mathematics, Engineering, and Science." Computer Vision and Image Understanding 65, no. 3 (March 1997): 450–54. http://dx.doi.org/10.1006/cviu.1996.0498.

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40

Jackson, Michael. "Problem frames and software engineering." Expert Systems 25, no. 1 (February 2008): 7–8. http://dx.doi.org/10.1111/j.1468-0394.2008.00456.x.

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41

Tong, T. O., M. C. Kekana, M. Y. Shatalov, and S. P. Moshokoa. "Numerical Investigation of Brusselator Chemical Model by Residual Function Using Mathematica Software." Journal of Computational and Theoretical Nanoscience 17, no. 7 (July 1, 2020): 2947–54. http://dx.doi.org/10.1166/jctn.2020.9324.

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In recent years, mathematical models have been developed to illustrate some physical phenomena in science and engineering. One of those systems of nonlinear differential equations is Brusselator chemical model. A mathematical template of checking accuracy of from black-boxes has been developed and investigated. Brusselator model is used as case study as its analytical solution is non-existence. The algorithms investigated from Mathematica software includes Adams method, Backward differential formula (BDF) and Implicit Runge-Kutta method which works well on stiff systems. The graphical results are on interval of 0 ≤ t ≤ 30.

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42

Ruder, Joseph A. "Software engineering for distributed control systems." ISA Transactions 30, no. 2 (January 1991): 33–40. http://dx.doi.org/10.1016/0019-0578(91)90037-6.

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43

A. Ben Zayed, Hissah, and Mashael S. Maashi. "Optimizing the Software Testing Problem Using Search-Based Software Engineering Techniques." Intelligent Automation & Soft Computing 29, no. 1 (2021): 307–18. http://dx.doi.org/10.32604/iasc.2021.017239.

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44

Goldberg, R. "Software engineering: An emerging discipline." IBM Systems Journal 25, no. 3.4 (1986): 334–53. http://dx.doi.org/10.1147/sj.253.0334.

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45

Vyatkin, Valeriy, and Alois Zoitl. "Advanced software engineering in industrial automation." Control Engineering Practice 21, no. 11 (November 2013): 1606–7. http://dx.doi.org/10.1016/j.conengprac.2012.11.003.

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46

Et. al., Pooja Sharma,. "Requirement Analysis For Business Process Re-Engineering With Computational Intelligence." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (April 11, 2021): 1663–66. http://dx.doi.org/10.17762/turcomat.v12i5.2143.

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There are enormous software applications which are developed for the usage of the software users. The software user may be categorized as public users who use online services through internet, and the private users who use the specific software inside a specific organization only. The private users can be the business organizations, Educational institutions, Health care centers and other government organizations. Each organization has a specific requirement on the base of which the software and the customer relationship management frame work has to be designed. Organization specific software are developed, tested and delivered to the service users by the software development companies and where under maintenance by the development team in the timely manner. At times, when these registered users are in need of alterations and modifications in the software which are used, then the business process reengineering is required to be done. Thus business process reengineering plays a vital role in the maintainability and the sustainability of the software product based on the user requirement. To create an effective Business process Re-engineering Framework, the user (or) the stakeholder requirements are considered as the prerequisite. Based on the requirement the software product would be re-engineering, the stakeholders requirements has to be initially preprocessed and the stake holders has to be grouped and prioritized with the ranking of the requirement modules that has to be implemented. Finally the risk assessment has to be done to estimate the critical conditions or the changes that would be faced while re- engineering and the requirements will be clustered for effective execution.

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47

Sun, Hong, Qian Wei Tu, Xiao Wan Wang, Jian Hong Zhang, Qian Zhong Wu, and Shou Wen Qin. "The Pricing and Charging of Cloud Computing SaaS." Advanced Materials Research 798-799 (September 2013): 703–7. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.703.

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In this paper, different mathematics models are applied to research the reasonable pricing of the cloud computing software products on the SaaS platform and explore the sales price of the cloud computing software products with the maximum total profits. These information can be the reference for decision-makers to determine the pricing strategy. The aim of this paper is for the cloud computing company to provide the majority of users with the inexpensive and excellent softwares and services, which can make the company dominate the cloud computing market quickly, gain the huge profits in the sustainable development manner and consider the interests of the company, users and the society.Keywords: clouding computing, SaaS, pricing and charging, mathematical analysis

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48

McManus, John, and Trevor Wood‐Harper. "Software engineering: a quality management perspective." TQM Magazine 19, no. 4 (June 19, 2007): 315–27. http://dx.doi.org/10.1108/09544780710756223.

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49

BHATTI, M. ASGHAR. "Developing Engineering Design Software Using Hypercard." Computer-Aided Civil and Infrastructure Engineering 3, no. 2 (November 6, 2008): 111–26. http://dx.doi.org/10.1111/j.1467-8667.1988.tb00161.x.

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50

Britcher, R. N. "Re-engineering software: A case study." IBM Systems Journal 29, no. 4 (1990): 551–67. http://dx.doi.org/10.1147/sj.294.0551.

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