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Journal articles on the topic 'Software generation'

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Published: 7 September 2024

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1

Misra, S. K., and P. J. Jalics. "Third-generation versus fourth-generation software development." IEEE Software 5, no. 4 (July 1988): 8–14. http://dx.doi.org/10.1109/52.17797.

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2

Lu, Ruqian, and Zhi Jin. "Automating application software generation." Expert Systems 20, no. 2 (May 2003): 72–78. http://dx.doi.org/10.1111/1468-0394.00227.

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3

Rudall, B. H. "Towards automatic software generation." Robotica 3, no. 1 (January 1985): 31–34. http://dx.doi.org/10.1017/s0263574700001454.

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SUMMARYCybernetic techniques already ensure that computing machines are produced efficiently. Consideration is now given to the case for automating the means of producing computer software. A formal notation to describe software production is outlined and some machine portable systems are introduced. New and powerful techniques for modelling machines and producing ‘program’ generators are described.
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4

Camuffo, M., M. Maiocchi, and M. Morselli. "Automatic software test generation." Information and Software Technology 32, no. 5 (June 1990): 337–46. http://dx.doi.org/10.1016/0950-5849(90)90003-a.

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5

Agarwal, Shubham, and Abhimanyu Bhatter. "Automated Software Test Data Generation Using Improved Search Procedure." Lecture Notes on Software Engineering 3, no. 2 (2015): 152–56. http://dx.doi.org/10.7763/lnse.2015.v3.181.

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6

Rajamanickam, Leelavathi, Nurul Azlia Binti Mat Saat, and Siti Norbaya Binti Daud. "Software Testing: The Generation Tools." International Journal of Advanced Trends in Computer Science and Engineering 8, no. 2 (April 15, 2019): 231–34. http://dx.doi.org/10.30534/ijatcse/2019/20822019.

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7

Yang, Fan, Z. H. Dong, and Jue Wang. "Method and Software Generation Platform." Applied Mechanics and Materials 743 (March 2015): 563–67. http://dx.doi.org/10.4028/www.scientific.net/amm.743.563.

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This paper proposed a method and software generation platform, which can automatically generate C++ codes of math equation, and package the software and method into a standard component. Also, the system integrates different types of methods in the unified information processing system with standard interface and format. Users can create new component and design experimental task with existing components. The system is quite convenient for developers to develop new component, easy for administrators to manage all existing component, and simple for users to design and operate experimental task.
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8

Keyvanpour, M. R., H. Homayouni, and Hasein Shirazee. "Automatic Software Test Case Generation." Journal of Software Engineering 5, no. 3 (June 15, 2011): 91–101. http://dx.doi.org/10.3923/jse.2011.91.101.

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9

LV, Ping, Qinrang LIU, Jiangxing WU, Hongchang CHEN, and Jianliang SHEN. "New generation software-defined architecture." SCIENTIA SINICA Informationis 48, no. 3 (March 1, 2018): 315–28. http://dx.doi.org/10.1360/n112017-00204.

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10

Luker, P. A. "Program Generators and Generation Software." Computer Journal 29, no. 4 (April 1, 1986): 315–21. http://dx.doi.org/10.1093/comjnl/29.4.315.

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11

Johnsonbaugh, Richard, and Martin Kalin. "A graph generation software package." ACM SIGCSE Bulletin 23, no. 1 (March 1991): 151–54. http://dx.doi.org/10.1145/107005.107032.

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12

Korel, B. "Automated software test data generation." IEEE Transactions on Software Engineering 16, no. 8 (1990): 870–79. http://dx.doi.org/10.1109/32.57624.

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13

Concas, Giulio, Giovanni Cantone, Ewan Tempero, and Hongyu Zhang. "New Generation of Software Metrics." Advances in Software Engineering 2010 (May 12, 2010): 1–2. http://dx.doi.org/10.1155/2010/913892.

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14

Fraken, Berend, Joop S. Duisterhout, Frans S. C. Witte, and Jan H. van Bemmel. "AIDA's fourth-generation software functionality." Computer Methods and Programs in Biomedicine 25, no. 3 (November 1987): 245–58. http://dx.doi.org/10.1016/0169-2607(87)90082-4.

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15

Darema, Frederica. "The Next Generation Software Program." International Journal of Parallel Programming 33, no. 2-3 (June 2005): 73–79. http://dx.doi.org/10.1007/s10766-005-4785-6.

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16

Tyugu, Enn. "Three new-generation software environments." Communications of the ACM 34, no. 6 (June 1991): 46–59. http://dx.doi.org/10.1145/103701.103708.

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17

Giordano, Geoff. "Software for a New Generation." Plastics Engineering 71, no. 9 (October 2015): 24–27. http://dx.doi.org/10.1002/j.1941-9635.2015.tb01412.x.

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18

Akyildiz, Ian F., Pu Wang, and Shih-Chun Lin. "SoftWater: Software-defined networking for next-generation underwater communication systems." Ad Hoc Networks 46 (August 2016): 1–11. http://dx.doi.org/10.1016/j.adhoc.2016.02.016.

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19

Lind, M. R., and J. M. Sulek. "Undersizing software systems: third versus fourth generation software development." European Journal of Information Systems 7, no. 4 (December 1998): 261–68. http://dx.doi.org/10.1057/palgrave.ejis.3000308.

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20

Lind, M. R., and J. M. Sulek. "Undersizing software systems: third versus fourth generation software development." European Journal of Information Systems 7, no. 4 (1998): 261–68. http://dx.doi.org/10.1038/sj.ejis.3000308.

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21

Liqiang, Zhang, and Nataliia Miroshnichenko. "THE SOFTWARE SECURITY DECISION SUPPORT METHOD DEVELOPMENT." Advanced Information Systems 6, no. 1 (April 6, 2022): 97–103. http://dx.doi.org/10.20998/2522-9052.2022.1.16.

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The actuality of the power to improve the accuracy of the results was determined in order to make a decision about the process of testing the software security. An analysis of the methods of support for making a decision was carried out. The necessity and feasibility of improving the accuracy of the results was determined in case of further software security inconsistencies in the minds of the fuzziness of input and intermediate data. With this method, on the basis of the mathematical apparatus of fuzzy logic, the method of support for making a decision about the security of software security has been developed. The main feature of this method is the synthesis of an improved method of generating the initial vibration in the process of starting a piece of neural string. Within the framework of the model, the next stages of follow-up are reached. For the mathematical formalization of the process of accepting the decision and designation of the input data, the model of forming the vector in the input data was developed. Depending on this model for shaping the input data, an anonymous sign of potential inconsistencies and undeclared possibilities of the PP is valid until the data of PVS-Studio Analysis Results. To improve the accuracy of the classification of data collected, the method of creating a piece of neural array has been improved, which is modified by the method of generating a sample, which is being developed. This generation method includes three equal generations: generation of the initial vibration, generation of the initial butt and generation of a specific value of the safety characteristic. This made it possible to increase the accuracy of classification and acceptance of the solution by 1.6 times for positive elements in the selection by 1.2 times for negative elements in the selection. To confirm the effectiveness of the development of the method of support for the decision on how to ensure software security, a ROC-analysis was carried out over the course of the above procedures. The results of the experiment confirmed the hypothesis about the efficiency of the divided method of support to make a decision about the security of PZ up to 1.2 times equal to the methods, which are based on the position of discriminant and cluster analysis.
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22

Polovikova, O. N., V. V. Shiryaev, N. M. Oskorbin, and L. L. Smolyakova. "Features of Software Implementation of Logical Tasks in Prolog." Izvestiya of Altai State University, no. 1(117) (March 17, 2021): 116–20. http://dx.doi.org/10.14258/izvasu(2021)1-20.

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One of the promising areas for using Prolog-systems is to solve logical tasks. This study outlines a solution approach based on the state generation procedure and the verification procedure. A solution to a logical task is presented, which demonstrates in practice the proposed approach and method of specifying a procedure for generating states. In the proposed example, a bit chain is generated that defines the code of a particular letter in the solution of the applied problem. Building a solution by means of code generation with verification allows not storing in the knowledge base a binary tree of all possible codes. The process of generating new states can be associated with the training of the program, with the dynamic formation of the knowledge base. The approach is based on the capabilities of software environments for adding facts and rules to existing ones, which were obtained as the results of the program or its stages. In this case, the entire program is the generating rule. An analysis of the constructed and tested procedures for the dynamic generation of states and the generation of facts allows us to talk about the applicability of such a solution for certain applied problems.
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23

Papa, Arled, Raphael Durner, Leonardo Goratti, Tinku Rasheed, and Wolfgang Kellerer. "Controlling Next-Generation Software-Defined RANs." IEEE Communications Magazine 58, no. 7 (July 2020): 58–64. http://dx.doi.org/10.1109/mcom.001.1900732.

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24

King, Myron, Nirav Dave, and Arvind. "Automatic generation of hardware/software interfaces." ACM SIGARCH Computer Architecture News 40, no. 1 (April 18, 2012): 325–36. http://dx.doi.org/10.1145/2189750.2151011.

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25

Sterritt, Roy, Christopher A. Rouff, Michael G. Hinchey, James L. Rash, and Walt Truszkowski. "Next generation system and software architectures." Science of Computer Programming 61, no. 1 (June 2006): 48–57. http://dx.doi.org/10.1016/j.scico.2005.11.005.

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26

Barnard, John M., and Geoff M. Downs. "Chemical Fragment Generation and Clustering Software§." Journal of Chemical Information and Computer Sciences 37, no. 1 (January 1997): 141–42. http://dx.doi.org/10.1021/ci960090k.

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27

Trimble, Sherry. "Is Second Generation Software Any Better?" NASSP Bulletin 70, no. 489 (April 1986): 32–35. http://dx.doi.org/10.1177/019263658607048909.

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28

King, Myron, Nirav Dave, and Arvind. "Automatic generation of hardware/software interfaces." ACM SIGPLAN Notices 47, no. 4 (June 2012): 325–36. http://dx.doi.org/10.1145/2248487.2151011.

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29

Cooper, Richard. "Crystallographic software for the next generation." Acta Crystallographica Section A Foundations and Advances 74, a2 (August 22, 2018): e167-e167. http://dx.doi.org/10.1107/s2053273318092756.

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30

Simonds, C. "Software for the next-generation automobile." IT Professional 5, no. 6 (November 2003): 7–11. http://dx.doi.org/10.1109/mitp.2003.1254962.

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31

Zhao, Ziyan, Li Zhang, Xiaoli Lian, Xiaoyun Gao, Heyang Lv, and Lin Shi. "ReqGen: Keywords-Driven Software Requirements Generation." Mathematics 11, no. 2 (January 9, 2023): 332. http://dx.doi.org/10.3390/math11020332.

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Software requirements specification is undoubtedly critical for the whole software life-cycle. Currently, writing software requirements specifications primarily depends on human work. Although massive studies have been proposed to speed up the process via proposing advanced elicitation and analysis techniques, it is still a time-consuming and error-prone task, which needs to take domain knowledge and business information into consideration. In this paper, we propose an approach, named ReqGen, which can provide further assistance by automatically generating natural language requirements specifications based on certain given keywords. Specifically, ReqGen consists of three critical steps. First, keywords-oriented knowledge is selected from the domain ontology and is injected into the basic Unified pre-trained Language Model (UniLM) for domain fine-tuning. Second, a copy mechanism is integrated to ensure the occurrence of keywords in the generated statements. Finally, a requirements-syntax-constrained decoding is designed to close the semantic and syntax distance between the candidate and reference specifications. Experiments on two public datasets from different groups and domains show that ReqGen outperforms six popular natural language generation approaches with respect to the hard constraint of keywords’ (phrases’) inclusion, BLEU, ROUGE, and syntax compliance. We believe that ReqGen can promote the efficiency and intelligence of specifying software requirements.
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32

Yıldırım, Nihan, and Yeliz Korkmaz. "Challenge of Millennials in Project Management." International Journal of Information Technology Project Management 8, no. 2 (April 2017): 87–108. http://dx.doi.org/10.4018/ijitpm.2017040106.

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The need for understanding Generation Y employees' attitudes and expectations that considerably differed from previous generations had been a focus of researchers in the last decades. IT industry and specifically software industry had been among the most popular employment areas of Generation Y professionals and hence Generation Y Software Developers constitutes the majority of the work force in the software industry. As known, software development is a project-based business where the project management methodologies and principles are utilized. Similar to other project based works, the effectiveness of human resources management and team development is the determinant of project success in software development. Therefore, to effectively manage and to adapt appropriate approaches for leading the project teams which include Generation Y software professionals, managers and leaders prior in need to understand their perspective. In this context, research aims to understand the expectations and attitudes of Generation Y Software Developer professionals in projects. The research is structured in two parts reflecting these dual aims. The first part of the research addresses the expectations of Y generation employees from project management and project environment in software development projects. The second part of the research explores the attitudes of Y generation Employees in software development project teams. Survey is conducted with the participation of 113 Generation Y Software Professionals who are employed in major software companies in Turkey. Basic concepts that are explored in the study are expectations from working environment, expectations from project type and content, leadership, motivation factors, challenges faced, perceptions on generation conflicts and the attitudes of Generation Y professionals towards project-based work and work environments. Software industry is dominated by project based management methods, perceptions and attitudes of Generation Y in projects are expected to provide practical guidelines to policy makers and HR professionals in developing solutions and tools for improving motivations and effectiveness of Generation Y employees.
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33

Alenezi, Mamdouh, Mohammed Akour, and Hamid Abdul Basit. "Exploring Software Security Test Generation Techniques: Challenges and Opportunities." International Journal of Education and Information Technologies 15 (June 3, 2021): 107–21. http://dx.doi.org/10.46300/9109.2021.15.11.

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Ensuring the security of the software has raised concerns from the research community which triggered numerous approaches that tend to eliminate it. The process of ensuring the security of software includes the introduction of processes in the Software Development Life Cycle where one of them is testing after the software is developed. Manually testing software for security is a labor-intensive task. Therefore, it is required to automate the process of testing by generating test cases by automated techniques. In this paper, we review various software security test case generation approaches and techniques. We try to explore and classify the most eminent techniques for test case generation. The techniques are summarized and presented briefly to covers all researches work that has been done in the targeted classification. Moreover, this paper aims to depict the sound of security in the current state of the art of test case generation. The findings are summarized and discussed where the opportunities and challenges are revealed narratively. Although the paper intends to provide a comprehensive view of the research in test case generation, there was a noticeable lack in the test case generation from the security perspectives
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34

Zia, Z., A. Rashid, and K. uz Zaman. "Software cost estimation for component-based fourth-generation-language software applications." IET Software 5, no. 1 (2011): 103. http://dx.doi.org/10.1049/iet-sen.2010.0027.

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35

Langston, William. "The generation effect: Software demonstrating the phenomenon." Behavior Research Methods, Instruments, & Computers 31, no. 1 (March 1999): 81–85. http://dx.doi.org/10.3758/bf03207696.

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36

Rassenfoss, Stephen. "E&P Software: The Next Generation." Journal of Petroleum Technology 65, no. 09 (September 1, 2013): 78–82. http://dx.doi.org/10.2118/0913-0078-jpt.

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37

Nejati, Shiva. "Next-Generation Software Verification: An AI Perspective." IEEE Software 38, no. 3 (May 2021): 126–30. http://dx.doi.org/10.1109/ms.2021.3049322.

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38

Petrenko, Denis A. "The new generation of IndorSoft software products." SAPR i GIS avtomobilnykh dorog, no. 1(1) (2013): 10–17. http://dx.doi.org/10.17273/cadgis.2013.1.2.

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39

Shakurov, M., D. Korobkin, S. Fomenkov, and A. Golovanchikov. "Software for generation of video files metadata." Journal of Physics: Conference Series 2060, no. 1 (October 1, 2021): 012029. http://dx.doi.org/10.1088/1742-6596/2060/1/012029.

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Abstract In today’s world, information is one of the most important resources. Its large turnover in the media makes companies look for ways to automate processes related to labeling and storage of data. But often these processes are left on the shoulders of archive workers who have to review the footage in real-time and create metadata based on what they see, which will be transferred into the archive. This process is often very time-consuming. As a result of the analysis of approaches to video data processing, comparative analysis of the efficiency and availability of computer vision services, a software for searching faces, and forming metadata in the video archive of the VGTRK company was designed and implemented.
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40

Ouadjaout, Salim, and Dominique Houzet. "Generation of Embedded Hardware/Software from SystemC." EURASIP Journal on Embedded Systems 2006, no. 1 (2006): 018526. http://dx.doi.org/10.1186/1687-3963-2006-018526.

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41

Devanbu, P. T., D. E. Perry, and J. S. Poulin. "Guest editors introduction: next generation software reuse." IEEE Transactions on Software Engineering 26, no. 5 (May 2000): 423–24. http://dx.doi.org/10.1109/tse.2000.846299.

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42

Uzuncaova, Engin, Sarfraz Khurshid, and Don Batory. "Incremental Test Generation for Software Product Lines." IEEE Transactions on Software Engineering 36, no. 3 (May 2010): 309–22. http://dx.doi.org/10.1109/tse.2010.30.

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43

Gray, Paul. "Software Quality, Robots, and the Next Generation." Information Systems Management 29, no. 3 (June 2012): 246–50. http://dx.doi.org/10.1080/10580530.2012.687318.

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44

Paradkar, A., K. C. Tai, and M. A. Vouk. "Automatic test-generation for predicates [software testing]." IEEE Transactions on Reliability 45, no. 4 (1996): 515–30. http://dx.doi.org/10.1109/24.556575.

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45

Voas, J. "A new generation of software quality conferences." IEEE Software 17, no. 1 (2000): 22–23. http://dx.doi.org/10.1109/52.819963.

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46

Kuliamin, V. V. "Combinatorial generation of operation system software configurations." Proceedings of the Institute for System Programming of RAS 23 (2012): 359–70. http://dx.doi.org/10.15514/ispras-2012-23-20.

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47

Protsko, L. B., P. G. Sorenson, J. P. Tremblay, and D. A. Schaefer. "Towards the automatic generation of software diagrams." IEEE Transactions on Software Engineering 17, no. 1 (1991): 10–21. http://dx.doi.org/10.1109/32.67575.

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48

Tripathi, G., and Prashant Kumar. "Stroke Symbol Generation Software for Fighter Aircraft." Defence Science Journal 63, no. 2 (March 23, 2013): 153–56. http://dx.doi.org/10.14429/dsj.63.4257.

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49

V.I.E., Anireh, and John Tarilanyo Afa. "(Lantool) Power Generation Cost Minimization Software Application." American Journal of Electrical and Electronic Engineering 2, no. 1 (January 7, 2014): 21–26. http://dx.doi.org/10.12691/ajeee-2-1-5.

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50

Doran, Jonathon, and Ian Parberry. "Controlled Procedural Terrain Generation Using Software Agents." IEEE Transactions on Computational Intelligence and AI in Games 2, no. 2 (June 2010): 111–19. http://dx.doi.org/10.1109/tciaig.2010.2049020.

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