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Journal articles on the topic 'Research Software Engineering'

Author: Grafiati

Published: 3 June 2025

Last updated: 22 June 2025

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1

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

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2

Marcos, Esperanza. "Software engineering research versus software development." ACM SIGSOFT Software Engineering Notes 30, no. 4 (2005): 1–7. http://dx.doi.org/10.1145/1082983.1083005.

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3

Rainer, Austen, Dorota Jagielska, and Tracy Hall. "Software engineering practice versus evidence-based software engineering research." ACM SIGSOFT Software Engineering Notes 30, no. 4 (2005): 1–5. http://dx.doi.org/10.1145/1082983.1083177.

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4

Woodcock, Jim. "Software engineering research directions." ACM Computing Surveys 28, no. 4es (1996): 128. http://dx.doi.org/10.1145/242224.242387.

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5

Parnas, David Lorge. "Successful software engineering research." ACM SIGSOFT Software Engineering Notes 23, no. 3 (1998): 64–68. http://dx.doi.org/10.1145/279437.279464.

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6

Potts, C. "Software-engineering research revisited." IEEE Software 10, no. 5 (1993): 19–28. http://dx.doi.org/10.1109/52.232392.

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7

Alexander, Roger T., James M. Bieman, and Robert B. France. "A software engineering research repository." ACM SIGSOFT Software Engineering Notes 29, no. 5 (2004): 1–4. http://dx.doi.org/10.1145/1022494.1022532.

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8

Carver, Jeffrey C., and Ian A. Cosden. "Research Software Engineering Training—INTERSECT." Computing in Science & Engineering 26, no. 2 (2024): 61–64. http://dx.doi.org/10.1109/mcse.2024.3401340.

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9

Brilliant, Susan S., and John C. Knight. "Empirical research in software engineering." ACM SIGSOFT Software Engineering Notes 24, no. 3 (1999): 44–52. http://dx.doi.org/10.1145/311963.311998.

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10

Eldridge, RH. "Software engineering and IPSE research." Information and Software Technology 30, no. 8 (1988): 509–11. http://dx.doi.org/10.1016/0950-5849(88)90148-6.

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11

Dybå, Tore, Rafael Prikladnicki, Kari Rönkkö, Carolyn Seaman, and Jonathan Sillito. "Qualitative research in software engineering." Empirical Software Engineering 16, no. 4 (2011): 425–29. http://dx.doi.org/10.1007/s10664-011-9163-y.

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12

Nowostawski, Mariusz, Simon McCallum, and Deepti Mishra. "Gamifying research in software engineering." Computer Applications in Engineering Education 26, no. 5 (2018): 1641–52. http://dx.doi.org/10.1002/cae.21994.

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13

Sydorov, N. A. "Ecosystem research in software engineering." PROBLEMS IN PROGRAMMING, no. 4 (December 2024): 114–24. https://doi.org/10.15407/pp2024.04.114.

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The application of the concept of the ecosystem in the software engineering shows the existence of the same problems regarding the definition of the concept of the ecosystem and its use for research that still exists in ecology. Justification for applying the concept of the ecosystem in an area that differs significantly from the ecology area, as in our case, requires researchers to look for analogies. This primarily applies to landscape, energy and matter transfer chains (trophic chains) and nutritional cycles. Until such analogies will be found in software engineering, the ecosystem research is nothing more than system analysis, and the concept of the ecosystem is an attractive concept. The purpose of this position article is to draw the attention of the software engineering community to ecosystem research. Three concepts of ecosystems in ecology, software and software engineering are considered. The composition and essence of ecosystem research in the software engineering are given. The literature review of on the state of ecosystem research in the software was carried out.

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14

Serebrenik, Alexander, Miroslaw Staron, Jordi Cabot, Birgit Penzenstadler, Lorin Hochstein, and Jeffrey C. Carver. "AI Engineering Research in Software Engineering Venues." IEEE Software 39, no. 6 (2022): 105–8. http://dx.doi.org/10.1109/ms.2022.3196208.

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15

Felderer, Michael, Michael Goedicke, Lars Grunske, Wilhelm Hasselbring, Anna-Lena Lamprecht, and Bernhard Rumpe. "Investigating Research Software Engineering: Toward RSE Research." Communications of the ACM 68, no. 2 (2025): 20–23. https://doi.org/10.1145/3685265.

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16

Al Sghaier, Hiba. "RESEARCH TRENDS IN SOFTWARE ENGINEERING FIELD: A LITERATURE REVIEW." International Journal of Engineering Technologies and Management Research 7, no. 6 (2020): 58–65. http://dx.doi.org/10.29121/ijetmr.v2020.i7.6.694.

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Software engineering is one of computer science branches, it comprises of building and developing software systems and applications. Software engineering is a discipline that has a constant growth in research in aim to identify new technologies and adopt it in different areas; there is a considerable investment on software engineering trends at the current time due to the availability of mobile technologies. With millions of billions of smart devices that are connected to the internet, all industries around the world are rapidly becoming a technology driven industries. Software engineers are aware of programming languages that are employed to develop software systems, by applying engineering principles to development process; they can design customized software systems for individual or organizational customers. The new trends in software engineering are numerous, Cloud Computing, machine learning, deep learning, big Data, mobile Computing. Nevertheless, there are many more other research trends in software engineering's field that have been intensively explored and implemented in many different industries. In this paper, authors try to summarize the most fields that are integrated with software engineering recently.

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17

Al Sghaier, Hiba. "RESEARCH TRENDS IN SOFTWARE ENGINEERING FIELD: A LITERATURE REVIEW." International Journal of Engineering Technologies and Management Research 7, no. 6 (2020): 58–65. http://dx.doi.org/10.29121/ijetmr.v7.i6.2020.694.

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Software engineering is one of computer science branches, it comprises of building and developing software systems and applications. Software engineering is a discipline that has a constant growth in research in aim to identify new technologies and adopt it in different areas; there is a considerable investment on software engineering trends at the current time due to the availability of mobile technologies. With millions of billions of smart devices that are connected to the internet, all industries around the world are rapidly becoming a technology driven industries. Software engineers are aware of programming languages that are employed to develop software systems, by applying engineering principles to development process; they can design customized software systems for individual or organizational customers. The new trends in software engineering are numerous, Cloud Computing, machine learning, deep learning, big Data, mobile Computing. Nevertheless, there are many more other research trends in software engineering's field that have been intensively explored and implemented in many different industries. In this paper, authors try to summarize the most fields that are integrated with software engineering recently.

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18

Theisen, Christopher, Marcel Dunaiski, Laurie Williams, and Willem Visser. "Software Engineering Research at the International Conference on Software Engineering in 2016." ACM SIGSOFT Software Engineering Notes 42, no. 4 (2018): 1–7. http://dx.doi.org/10.1145/3149485.3149496.

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19

Chao, Tian, and Tuyatsetseg Badarch. "Research on Civil Engineering Software for Engineering Computation." American Journal of Computer Science and Technology 5, no. 2 (2022): 63. http://dx.doi.org/10.11648/j.ajcst.20220502.16.

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20

Xoliqov, Qurbonboy To‘Ychiyevich, Matluba Mamatmurod Qizi Norqulova, and Akbar Axmadovich Ochilov. "ON METHODS OF USING ENGINEERING SOFTWARE IN RESEARCH ACTIVITY OF STUDENTS." CURRENT RESEARCH JOURNAL OF PEDAGOGICS 04, no. 05 (2023): 109–14. http://dx.doi.org/10.37547/pedagogics-crjp-04-05-16.

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The article describes the ways and advantages of using engineering programs in the development of research activities of physics students, as well as the ways of using the Multisim program in conducting research.

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21

Russo, Daniel, and Klaas-Jan Stol. "PLS-SEM for Software Engineering Research." ACM Computing Surveys 54, no. 4 (2021): 1–38. http://dx.doi.org/10.1145/3447580.

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Software Engineering (SE) researchers are increasingly paying attention to organizational and human factors. Rather than focusing only on variables that can be directly measured, such as lines of code, SE research studies now also consider unobservable variables, such as organizational culture and trust. To measure such latent variables, SE scholars have adopted Partial Least Squares Structural Equation Modeling (PLS-SEM), which is one member of the larger SEM family of statistical analysis techniques. As the SE field is facing the introduction of new methods such as PLS-SEM, a key issue is that not much is known about how to evaluate such studies. To help SE researchers learn about PLS-SEM, we draw on the latest methodological literature on PLS-SEM to synthesize an introduction. Further, we conducted a survey of PLS-SEM studies in the SE literature and evaluated those based on recommended guidelines.

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22

Vijiyan, Gayatri. "Current Trends in Software Engineering Research." Review of Computer Engineering Research 2, no. 3 (2015): 65–70. http://dx.doi.org/10.18488/journal.76/2015.2.3/76.3.65.70.

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23

Suthar, Devendra. "LATEST TRENDS IN SOFTWARE ENGINEERING RESEARCH." International Journal of Technical Research & Science Special, June (2021): 30–33. http://dx.doi.org/10.30780/specialissue-scrdsi-2021/008.

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24

McDermid, J. A., and K. H. Bennett. "Software engineering research: A critical appraisal." IEE Proceedings - Software 146, no. 4 (1999): 179. http://dx.doi.org/10.1049/ip-sen:19990618.

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25

Fuggetta, Alfonso. "Some reflections on software engineering research." ACM SIGSOFT Software Engineering Notes 24, no. 1 (1999): 74–77. http://dx.doi.org/10.1145/308769.308791.

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26

Stol, Klaas-Jan, and Brian Fitzgerald. "The ABC of Software Engineering Research." ACM Transactions on Software Engineering and Methodology 27, no. 3 (2018): 1–51. http://dx.doi.org/10.1145/3241743.

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27

Xu, Haiping. "Future Research Directions of Software Engineering and Knowledge Engineering." International Journal of Software Engineering and Knowledge Engineering 25, no. 02 (2015): 415–21. http://dx.doi.org/10.1142/s0218194015500035.

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Software Engineering (SE) and Knowledge Engineering (KE) are closely related disciplines with goals of turning the development process of software systems and knowledge-based systems, respectively, into engineering disciplines. In particular, they together can provide systematic approaches for engineering intelligent software systems more efficiently and cost-effectively. As there is a large overlap between the two disciplines, the interplay is vital for both to be successful. In this paper, we divide the intersection of SE and KE into three subareas, namely Knowledge-Supported Software Engineering (KSSE), Engineering Knowledge as a Software (EKaaS), and Intelligent Software System Engineering (ISSE). For each subarea, we describe the challenges along with the current trends, and predict the future research directions that may have the most potential for success.

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28

Koschke, Rainer. "Software visualization in software maintenance, reverse engineering, and re-engineering: a research survey." Journal of Software Maintenance and Evolution: Research and Practice 15, no. 2 (2003): 87–109. http://dx.doi.org/10.1002/smr.270.

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29

Song, Xi Jun, and Zhi Lian Zeng. "Research on Application of Software Engineering Theory in Software Development." Applied Mechanics and Materials 687-691 (November 2014): 1921–24. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1921.

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With the development of information society, the size and number of computer software increases sharply. This demands the quality of software higher and higher. Thus does software engineering management come into being, and is enriched, developed and perfected in engineering practice continually. In this paper, the author analyses the new theory's research background, meaning, and the applicant region. This paper sums up the experience of software engineering implementation in project developing, and points out the problems of software in software explore. From the character and existing problem in software, the author compares the usability of a lot of soft engineer process models in developing organization, points out the importance of the implantation in these organizations. In the end, this paper also gives its suggestions on implant principle, organization development, system building, staff training, and environment construction.

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30

Hernández-López, Adrián, Ricardo Colomo-Palacios, Ángel García-Crespo, and Fernando Cabezas-Isla. "Software Engineering Productivity." International Journal of Information Technology Project Management 2, no. 1 (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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31

DeFranco, Joanna F., and Phillip Laplante. "A software engineering team research mapping study." Team Performance Management: An International Journal 24, no. 3/4 (2018): 203–48. http://dx.doi.org/10.1108/tpm-08-2017-0040.

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Purpose The purpose of this mapping study has been performed to identify, critically analyze and synthesize research performed in the area of software engineering teams. Teams, in a general sense, have been studied extensively. But the distinctive processes that need to be executed effectively and efficiently in software engineering require a better understanding of current software engineering team research. Design/methodology/approach In this work, software engineering team publications were analyzed and the key findings of each paper that met our search inclusion criteria were synthesized. In addition, a keyword content analysis was performed to create a taxonomy to categorize each paper and evaluate the state of software engineering team research. Findings In software engineering team research, the resulting areas that are the most active are teamwork/collaboration, process/design and coordination. Clear themes of analysis have been determined to help understand how team members collaborate, factors affecting their success and interactions among all project stakeholders. In addition, themes related to tools to support team collaboration, improve the effectiveness of software engineering processes and support team coordination have been found. However, the research gaps determined from the content analysis point toward a need for more research in the area of communication and tools. Originality/value The goal of this work is to define the span of previous research in this area, create a taxonomy to categorize such research and identify open research areas to provide a clear road map for future research in the area of software engineering teams. These results, along with the key finding themes presented, will help guide future research in an area that touches all parts of the software engineering and development processes.

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32

Marijan, Dusica, Thomas Zimmermann, MyungJoo Ham, and Bran Selic. "Bridging Software Engineering Research and Industrial Practice." ACM SIGSOFT Software Engineering Notes 46, no. 1 (2021): 30–32. http://dx.doi.org/10.1145/3437479.3437488.

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There is a long-standing challenge to narrow the gap between software engineering research and industrial practice. This gap is reinforced by a number of challenges, including differing timelines, metrics, expectations, and perceptions of these two communities. We believe that these and other related challenges need be analyzed and discussed, to discover synergies and strengthen collaborations between researchers and practitioners in software engineering. In this report, we present insights from the 7th International Workshop on Software Engineering Research and Industrial Practice held virtually at the International Conference on Software Engineering 2020.

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33

Sydorov, M. O. "Towards ecosystem research in the software engineering." PROBLEMS IN PROGRAMMING, no. 2-3 (September 2024): 124–31. https://doi.org/10.15407/pp2024.02-03.124.

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The application of the concept of the ecosystem in the software engineering shows the existence of the same problems regarding the definition of the concept of the ecosystem and its use for research that still exists in ecology. Justification for applying the ecosystem concept in the area that differs significantly from the ecology, as in our case, requires researchers to look for analogies. This primarily applies to landscape, energy and matter transfer chains (trophic chains) and nutritional cycles. Until such analogies are found in software engineering, ecosystem research will be nothing more than system analysis, and the concept of the ecosystem is an attractive concept. The purpose of this article is to draw the attention of the software engineering community to ecosystem research. Three concepts of ecosystems in ecology, software and software engineering are considered. The composition and essence of ecosystem research in the software engineering are given. The literature review of the state of the ecosystem research for software ecosystems has been carried out.

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34

Korthals, Rodney L. "Utilizing software engineering to improve software process capabilities within the Biological Engineering Research Unit." Computers and Electronics in Agriculture 19, no. 3 (1998): 265–75. http://dx.doi.org/10.1016/s0168-1699(98)00002-7.

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35

Wang, Jin. "Doing Doctorate Student Research Under Software Engineering." Data Research 3, no. 2 (2019): 20. http://dx.doi.org/10.31058/j.data.2019.33003.

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36

Kajan, E. "Software engineering a forty years research retrospective." Scientific Publications of the State University of Novi Pazar Series A: Applied Mathematics, Informatics and mechanics 12, no. 2 (2020): 83–98. http://dx.doi.org/10.5937/spsunp2002083k.

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This paper presents author experience with software development during last forty years. It is divided into three eras: closed and open -systems and Internet of Everything, each covered by challenges, issues and solutions. The main stream is given from the interoperability perspective and flavored by security issues. Variety of applications domains, that author faced during his carrier, each with own challenges, is presented. Example include computer graphics systems, special-purpose solutions, business-to-business, business process management, e-government, and smart cities.

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37

Venkatraman, Sitalakshmi. "Software Engineering Research Gaps in the Cloud." Journal of Information Technology Research 6, no. 1 (2013): 1–19. http://dx.doi.org/10.4018/jitr.2013010101.

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This paper takes a systematic review methodology to unearth the reason for a slow adoption of cloud computing by businesses, despite the user interests and cloud advancements gained recently. The key finding is that the IT industry has taken different modelling approaches to engineer and deliver the cloud services based on the goals of different key cloud players, thereby raising various adoption challenges and concerns. In this context, there is a need for rethinking Software Engineering concepts. This motivates us to question whether the existing Software Engineering theories and modelling principles are sufficient for the new cloud computing paradigm. Due to the paucity of a comprehensive review in literature, the main aim of this review article is to identify such research gaps and insufficiencies in Software Engineering, and to provide recommendations for bridging these gaps. In this work, the systemic review of the state of the art of cloud computing has resulted in identifying four major cloud modelling gaps that require prime attention. The paper discusses these gaps and identifies the key Software Engineering challenges prevalent in addressing each of these gaps. Finally, the author proposes five topmost research recommendations specifically designed for overcoming these gaps/challenges in order to facilitate a sustainable cloud adoption. Overall, the author’s findings have established the need to rethink Software Engineering theories for arriving at a multilateral or distributed cloud modelling approach. With such rethinking, the proposed cloud design automatically incorporates cloud user-roles, interoperability, intelligent automation and trusted cloud infrastructure strategies for achieving a sustainable cloud framework of the future.

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38

Starke, Gernot. "Urgent research issues in software process engineering." ACM SIGSOFT Software Engineering Notes 18, no. 4 (1993): 13–15. http://dx.doi.org/10.1145/163626.163628.

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39

Xia, Franck. "What's wrong with software engineering research methodology." ACM SIGSOFT Software Engineering Notes 23, no. 1 (1998): 62–65. http://dx.doi.org/10.1145/272263.272279.

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40

Abrahão, Silvia, Miroslaw Staron, Maria Teresa Baldassarre, et al. "Research Highlights in Evidence-Based Software Engineering." IEEE Software 41, no. 1 (2024): 133–36. http://dx.doi.org/10.1109/ms.2023.3321418.

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41

Hills, Mark, Paul Klint, and Jurgen J. Vinju. "Enabling PHP software engineering research in Rascal." Science of Computer Programming 134 (February 2017): 37–46. http://dx.doi.org/10.1016/j.scico.2016.05.003.

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42

Kuang, Li-Qun, and Xie Han. "The Research of Software Engineering Curriculum Reform." Physics Procedia 33 (2012): 1762–67. http://dx.doi.org/10.1016/j.phpro.2012.05.282.

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43

Parnas, David Lorge. "Who taught me about software engineering research?" ACM SIGSOFT Software Engineering Notes 23, no. 4 (1998): 26–28. http://dx.doi.org/10.1145/286366.286372.

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44

Fuggetta, Alfonso. "Rethinking the modes of software engineering research." Journal of Systems and Software 47, no. 2-3 (1999): 133–38. http://dx.doi.org/10.1016/s0164-1212(99)00033-3.

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45

Moukahal, Lama J., Marwa A. Elsayed, and Mohammad Zulkernine. "Vehicle Software Engineering (VSE): Research and Practice." IEEE Internet of Things Journal 7, no. 10 (2020): 10137–49. http://dx.doi.org/10.1109/jiot.2020.3001026.

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46

Cohen, Jeremy, Daniel S. Katz, Michelle Barker, Neil Chue Hong, Robert Haines, and Caroline Jay. "The Four Pillars of Research Software Engineering." IEEE Software 38, no. 1 (2021): 97–105. http://dx.doi.org/10.1109/ms.2020.2973362.

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47

Boehm, Barry. "Industrial priorities for software engineering research (panel)." ACM SIGSOFT Software Engineering Notes 21, no. 6 (1996): 2. http://dx.doi.org/10.1145/250707.239103.

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48

Mei, Hong, Dong-Gang Cao, and Fu-Qing Yang. "Development of Software Engineering: A Research Perspective." Journal of Computer Science and Technology 21, no. 5 (2006): 682–96. http://dx.doi.org/10.1007/s11390-006-0682-8.

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49

Rombach, Prof Dr Dieter. "New Institute for Applied Software Engineering Research." Software Process: Improvement and Practice 2, no. 2 (1996): 152–55. http://dx.doi.org/10.1002/(sici)1099-1670(199606)2:2<152::aid-spip37>3.0.co;2-7.

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50

V Kalyani, V. Kalyani. "What Makes Good Research in Software Engineering." Journal of Science and Technology 7, no. 8 (2022): 24–35. http://dx.doi.org/10.46243/jst.2022.v7.i08.pp24-35.

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