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Thematische Bibliographien / General software engineering / Zeitschriftenartikel

Zeitschriftenartikel zum Thema „General software engineering“

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Autor: Grafiati

Veröffentlicht am 27. Juli 2024

Zuletzt aktualisiert am 29. Juli 2024

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1

Johnson, Pontus, Mathias Ekstedt, Michael Goedicke und Ivar Jacobson. „Towards general theories of software engineering“. Science of Computer Programming 101 (April 2015): 1–5. http://dx.doi.org/10.1016/j.scico.2014.11.005.

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2

Antonov, Anton. „APPLICATION OF AUTODESK SOFTWARE PRODUCT FOR TRAINING OF STUDENTS IN GENERAL ENGINEERING“. Journal Scientific and Applied Research 13, Nr. 1 (03.03.2018): 31–35. http://dx.doi.org/10.46687/jsar.v13i1.235.

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One of the most complex and dynamic enterprise systems are logistics. The system designing requires many people, whereas specialized software products can be used to help design different elements and stages. Certain purpose of the work is to be presented software products Autodesk Factory Design Suite and their application in the education of the students in general engineering, which leads to break the traditional way of absorption the material. This cause lasting interest in science, which is a prerequisite for highly qualified personnel, competition in the labor market.

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3

Hernández-López, Adrián, Ricardo Colomo-Palacios, Ángel García-Crespo und Fernando Cabezas-Isla. „Software Engineering Productivity“. International Journal of Information Technology Project Management 2, Nr. 1 (Januar 2011): 37–47. http://dx.doi.org/10.4018/jitpm.2011010103.

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Software engineering productivity has been widely studied, but there are many issues that remain unsolved. Interesting works related to new metrics and more replications of past productivity analysis have emerged, however, in order to fulfill these unsolved issues, a consensus about influencing factors and well recognized and useful sets of inputs and outputs for using in measurements must be reached. In this regard, a clear state of the art may shed light on further research in software engineering productivity, which remains a promising research area. In this paper, general concepts of software engineering productivity along with general issues and recent challenges that need further attention from the research community are presented.

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4

Antonov, Anton. „OVERVIEW OF A SOFTWARE PRODUCT “ANYLOGIC” USED IN TRAINING OF STUDENTS IN GENERAL ENGINEERING“. Journal Scientific and Applied Research 9, Nr. 1 (05.03.2016): 21–24. http://dx.doi.org/10.46687/jsar.v9i1.186.

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The design of a complex logistics system requires many people and resources to support the design of the various elements and stages, that can be used for specialized software products. One of the software that can be used for designing logistic systems such as warehouses, storage equipment, industrial buildings, transport schemes for road, rail, sea, air and combined transport is “AnyLogic” . Therefore the aim of this work is to present “AnyLogic” software product and its application in education of students in general engineering.

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5

Parnas, David Lorge. „Software engineering“. Communications of the ACM 40, Nr. 9 (September 1997): 128. http://dx.doi.org/10.1145/260750.260784.

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6

Leveson, Nancy G. „Software engineering“. Communications of the ACM 40, Nr. 2 (Februar 1997): 129–31. http://dx.doi.org/10.1145/253671.253754.

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7

CACM Staff. „Software engineering is engineering“. Communications of the ACM 55, Nr. 1 (Januar 2012): 6–7. http://dx.doi.org/10.1145/2063176.2063178.

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8

PALMER, KENT D. „SOFTWARE ENGINEERING DESIGN METHODOLOGIES AND GENERAL SYSTEMS THEORY“. International Journal of General Systems 24, Nr. 1-2 (Januar 1996): 43–94. http://dx.doi.org/10.1080/03081079608945107.

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9

Johnson, Pontus, und Mathias Ekstedt. „The Tarpit – A general theory of software engineering“. Information and Software Technology 70 (Februar 2016): 181–203. http://dx.doi.org/10.1016/j.infsof.2015.06.001.

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10

Bértolo, J. M., F. Obelleiro, J. M. Taboada und J. L. Rodríguez. „General purpose software package for electromagnetics engineering education“. Computer Applications in Engineering Education 10, Nr. 1 (2002): 33–44. http://dx.doi.org/10.1002/cae.10015.

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11

McDermid, John. „Editorial: Software engineering“. Software Engineering Journal 11, Nr. 6 (1996): 366. http://dx.doi.org/10.1049/sej.1996.0047.

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12

Leroy, Dorian, June Sallou, Johann Bourcier und Benoit Combemale. „When Scientific Software Meets Software Engineering“. Computer 54, Nr. 12 (Dezember 2021): 60–71. http://dx.doi.org/10.1109/mc.2021.3102299.

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13

Sydorov, N. O., und N. M. Sydorova. „Software engineering and big data software“. PROBLEMS IN PROGRAMMING, Nr. 3-4 (Dezember 2022): 69–72. http://dx.doi.org/10.15407/pp2022.03-04.069.

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Software engineering is a mature industry of human activity focused on the creation, deployment, marketing and maintenance of software. The fundamental concepts of engineering are life cycle model; three main components of life cycle phases - products, processes and resources; engineering and methodologies for creating, deployment and maintaining software. Software is the foun- dation of technological advances that lead to new high performance products. As the functionality of products grows, so does the need to efficiently and correctly create and maintain the complex software that enables this growth. Therefore, in addition to solving its own problems, software engineering serves the solution of the problems of creating and maintaining software in other domains, which are called application domains. Information technology is a well-known application domain. The basis of this domain is data. Information systems are being implemented in an organization to improve its effectiveness and efficiency. The functionality of information systems has grown dramatically when big data began to be used. This growth has led to the emergence of a wide variety of software-intensive big data information systems. At the same time, the role and importance of software engineering for solving the problems of this application domain has only intensified. Modern possibilities of software engineering are shown. The aspects of interaction between software engineering and big data systems are analyzed. The topics for the study of big data software ecosystems and big data system of systems are outlined.

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14

Mandrioli, Dino. „Software engineering concepts“. Advances in Engineering Software (1978) 8, Nr. 1 (Januar 1986): 63–64. http://dx.doi.org/10.1016/0141-1195(86)90028-8.

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15

Švéda, Miroslav. „Microcontroller software engineering“. Microprocessing and Microprogramming 34, Nr. 1-5 (Februar 1992): 11–13. http://dx.doi.org/10.1016/0165-6074(92)90091-k.

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16

Kacsuk, P. „Parallel software engineering“. Microprocessing and Microprogramming 38, Nr. 1-5 (September 1993): 187–88. http://dx.doi.org/10.1016/0165-6074(93)90142-8.

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17

CACM Staff. „Software engineering, like electrical engineering“. Communications of the ACM 58, Nr. 2 (28.01.2015): 8–9. http://dx.doi.org/10.1145/2702734.

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18

Lutz, Michael J., J. Fernando Naveda und James R. Vallino. „Undergraduate software engineering“. Communications of the ACM 57, Nr. 8 (August 2014): 52–58. http://dx.doi.org/10.1145/2632361.

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19

Gisselquist, Richard. „Engineering in software“. Communications of the ACM 41, Nr. 10 (Oktober 1998): 107–8. http://dx.doi.org/10.1145/286238.286254.

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20

Glesner, Sabine. „Rigorous software engineering“. Computer Science - Research and Development 28, Nr. 4 (21.09.2013): 263–64. http://dx.doi.org/10.1007/s00450-013-0252-6.

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21

Lu, RuQian, und Zhi Jin. „From knowledge based software engineering to knowware based software engineering“. Science in China Series F: Information Sciences 51, Nr. 6 (21.05.2008): 638–60. http://dx.doi.org/10.1007/s11432-008-0060-y.

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22

Hamming, R. W. „Foreword: Software engineering“. Journal of Systems Integration 6, Nr. 1-2 (März 1996): 5–7. http://dx.doi.org/10.1007/bf02262747.

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23

Sicilia, Miguel-Angel, Elena García-Barriocanal, Salvador Sánchez-Alonso und Daniel Rodríguez-García. „Ontologies of engineering knowledge: general structure and the case of Software Engineering“. Knowledge Engineering Review 24, Nr. 3 (September 2009): 309–26. http://dx.doi.org/10.1017/s0269888909990087.

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AbstractEngineering knowledge is a specific kind of knowledge that is oriented to the production of particular classes of artifacts, is typically related to disciplined design methods, and takes place in tool-intensive contexts. As a consequence, representing engineering knowledge requires the elaboration of complex models that combine functional and structural representations of the resulting artifacts with process and methodological knowledge. The different categories used in the engineering domain vary in their status and in the way they should be manipulated when building applications that support engineering processes. These categories include artifacts, activities, methods and models. This paper surveys existing models of engineering knowledge and discusses an upper ontology that abstracts the categories that crosscut different engineering domains. Such an upper model can be reused for particular engineering disciplines. The process of creating such elaborations is reported on the particular case study of Software Engineering as a concrete application example.

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24

Stoica, Anca-Juliana, Kristiaan Pelckmans und William Rowe. „System components of a general theory of software engineering“. Science of Computer Programming 101 (April 2015): 42–65. http://dx.doi.org/10.1016/j.scico.2014.11.008.

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25

Ralph, Paul, Iaakov Exman, Pan-Wei Ng, Pontus Johnson, Michael Goedicke, Alper Tolga Kocata und Kate Liu Yan. „How to Develop a General Theory of Software Engineering“. ACM SIGSOFT Software Engineering Notes 39, Nr. 6 (09.12.2014): 23–25. http://dx.doi.org/10.1145/2674632.2674647.

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26

Exman, Iaakov, Dewayne E. Perry, Balbir Barn und Paul Ralph. „Separability Principles for a General Theory of Software Engineering“. ACM SIGSOFT Software Engineering Notes 41, Nr. 1 (22.02.2016): 25–27. http://dx.doi.org/10.1145/2853073.2853093.

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27

Murthy MR, Narasimha. „Future Scope of Artificial Intelligence in Software Engineering“. International Journal of Science and Research (IJSR) 12, Nr. 12 (05.12.2023): 1401–2. http://dx.doi.org/10.21275/sr231113100032.

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28

Davis, Michael. „Will software engineering ever be engineering?“ Communications of the ACM 54, Nr. 11 (November 2011): 32–34. http://dx.doi.org/10.1145/2018396.2018407.

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29

Bosco, Michael F. „Teaching Software Engineering by Reverse Engineering“. Computer Science Education 2, Nr. 2 (Januar 1991): 117–30. http://dx.doi.org/10.1080/0899340910020202.

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30

Wooldridge, M. „Agent-based software engineering“. IEE Proceedings - Software Engineering 144, Nr. 1 (1997): 26. http://dx.doi.org/10.1049/ip-sen:19971026.

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31

Bott, Frank. „Editorial: Software engineering education“. Software Engineering Journal 4, Nr. 4 (1989): 174. http://dx.doi.org/10.1049/sej.1989.0021.

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32

Pyle, I. C. „Real-world software engineering“. Software Engineering Journal 6, Nr. 3 (1991): 68. http://dx.doi.org/10.1049/sej.1991.0010.

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33

Kelly, Diane, Spencer Smith und Nicholas Meng. „Software Engineering for Scientists“. Computing in Science & Engineering 13, Nr. 5 (September 2011): 7–11. http://dx.doi.org/10.1109/mcse.2011.86.

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34

Carver, Jeffrey C. „Software Engineering for Science“. Computing in Science & Engineering 18, Nr. 2 (März 2016): 4–5. http://dx.doi.org/10.1109/mcse.2016.31.

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35

Hall, P. A. V., und G. H. Galal. „Computer-aided software engineering“. Computer-Aided Engineering Journal 6, Nr. 4 (1989): 113. http://dx.doi.org/10.1049/cae.1989.0028.

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36

Mølgaard, John. „Software engineering: System aspects“. Microprocessing and Microprogramming 24, Nr. 1-5 (August 1988): 49. http://dx.doi.org/10.1016/0165-6074(88)90027-0.

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37

Bucchiarone, Antonio, Kendra M. L. Cooper, Dayi Lin, Edward F. Melcer und Kelvin Sung. „Games and Software Engineering“. ACM SIGSOFT Software Engineering Notes 48, Nr. 1 (10.01.2023): 85–89. http://dx.doi.org/10.1145/3573074.3573096.

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Games are a popular form of entertainment and, due to their nature (i.e., interactive, immersive, etc.), strongly lend themselves for use beyond this original intent. Serious games, or games with a purpose, have been introduced to integrate the entertainment value games with domain specific objectives on important topics within education, health, and the environment to mention a few. In addition, gamification has been used to enhance nonentertainment applications with game elements; it aspires to foster behavioral changes, engagement, motivation, and participation in activities. In this context, the actions performed have meaning/value in the game experience in order to improve workplace performance or learn something in real life. The growing adoption of gameful experiences in all of the previous contexts make their design and development increasingly complex due to, for example, the number and variety of users, and their potential mission criticality. This complexity is nurtured, among the other factors, by a lack of theoretical grounding and adequate frameworks to engineer the intended solutions. In this paper, we report the outcomes of the 6th International Workshop on Games and Software Engineering: Engineering fun, inspiration, and motivation (GAS 2023 ) 1, which was held as part of the 44th International Conference on Software Engineering (ICSE 2022) in Pittsburgh, PA, USA on May 20, 2022. The workshop program includes two exciting keynotes discussing topics related to training and learning, and fulfilling the promise and potential of gamification. The two paper sessions examined gamification from the perspectives of software project, testing, and, design. The conclusion of the workshop is anchored by a panel of four highly qualified researchers and practitioners discussing lessons learned and the future of gamification.

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38

Jaccheri, Letizia. „Women and Software Engineering“. ACM SIGSOFT Software Engineering Notes 49, Nr. 2 (03.04.2024): 16–18. http://dx.doi.org/10.1145/3650142.3650147.

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My goal with this text is to provide some concepts and questions that can help the reader to reflect on and elevate the discussion about Women and Software Engineering by providing historical data and some reflection points for the future. Feminism constitutes both a theoretical perspective and a social movement aiming to diminish and ultimately eliminate gender-based inequality and oppression. Data feminism merges data science with feminist principles to examine and address biases and power dynamics in data and technology. Studies at the intersection between gender and software engineering cover gender representation, barriers, and experiences. The main questions I propose for future reflections in the community are: What are the benefits that women bring to software engineering? How does the career and the life of female software engineers unfold? How should software engineering research change so that feminist principles are incorporated? How can feminist knowledge and processes help to examine power structure in software engineering?

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39

Lehman, M. M. „Software engineering, the software process and their support“. Software Engineering Journal 6, Nr. 5 (1991): 243. http://dx.doi.org/10.1049/sej.1991.0028.

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40

Burnett, Margaret, Curtis Cook und Gregg Rothermel. „End-user software engineering“. Communications of the ACM 47, Nr. 9 (September 2004): 53–58. http://dx.doi.org/10.1145/1015864.1015889.

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41

Jacobson, Ivar, und Ed Seidewitz. „A new software engineering“. Communications of the ACM 57, Nr. 12 (26.11.2014): 49–54. http://dx.doi.org/10.1145/2677034.

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42

Jacobson, Ivar, und Ed Seidewitz. „A New Software Engineering“. Queue 12, Nr. 10 (Oktober 2014): 30–38. http://dx.doi.org/10.1145/2685690.2693160.

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43

Seidman, Stephen. „Software Engineering Certification Schemes“. Computer 41, Nr. 5 (Mai 2008): 87–89. http://dx.doi.org/10.1109/mc.2008.164.

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44

Hall, J. G., und L. Rapanotti. „Beauty in software engineering“. Computer 46, Nr. 2 (Februar 2013): 85–87. http://dx.doi.org/10.1109/mc.2013.42.

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45

Kryvyi, S., und E. Grinenko. „Ecosystems of Software Engineering“. Cybernetics and Systems Analysis 56, Nr. 4 (Juli 2020): 628–40. http://dx.doi.org/10.1007/s10559-020-00280-3.

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46

de Champeaux, Dennis. „Software engineering considered harmful“. Communications of the ACM 45, Nr. 11 (November 2002): 102–4. http://dx.doi.org/10.1145/581571.581608.

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47

Killalea, Tom. „Velocity in Software Engineering“. Queue 17, Nr. 3 (Juni 2019): 54–64. http://dx.doi.org/10.1145/3344777.3352692.

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48

Killalea, Tom. „Velocity in software engineering“. Communications of the ACM 62, Nr. 9 (21.08.2019): 44–47. http://dx.doi.org/10.1145/3345626.

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49

V David, V. David. „Software Engineering: A Roadmap“. Journal of Science and Technology 7, Nr. 10 (21.12.2022): 86–92. http://dx.doi.org/10.46243/jst.2022.v7.i10.pp86-92.

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50

Kamthan, Pankaj. „A Perspective on Software Engineering Education with Open Source Software“. International Journal of Open Source Software and Processes 4, Nr. 3 (Juli 2012): 13–25. http://dx.doi.org/10.4018/ijossp.2012070102.

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As the development and use of open source software (OSS) becomes prominent, the issue of its outreach in an educational context arises. The practices fundamental to software engineering, including those related to management, process, and workflow deliverables, are examined in light of OSS. Based on a pragmatic framework, the prospects of integrating OSS in a traditional software engineering curriculum are outlined, and concerns in realizing them are given. In doing so, the cases of the adoption of an OSS process model, the use of OSS as a computer-aided software engineering (CASE) tool, OSS as a standalone subsystem, and open source code reuse are considered. The role of openly accessible content in general is discussed briefly.

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