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Journal articles on the topic 'Software systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 June 2025

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1

Spinellis, Diomidis. "Systems Software." IEEE Software 30, no. 3 (2013): 18–19. http://dx.doi.org/10.1109/ms.2013.61.

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2

Silva, Dilma M. da, and Fabio Kon. "Adaptive software systems." Journal of the Brazilian Computer Society 10, no. 1 (2004): 3–4. http://dx.doi.org/10.1590/s0104-65002004000200001.

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3

Ebert, Christof, Divith Bajaj, and Michael Weyrich. "Testing Software Systems." IEEE Software 39, no. 4 (2022): 8–17. http://dx.doi.org/10.1109/ms.2022.3166755.

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4

Vogelsang, Andreas. "Explainable software systems." it - Information Technology 61, no. 4 (2019): 193–96. http://dx.doi.org/10.1515/itit-2019-0015.

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Abstract Software and software-controlled technical systems play an increasing role in our daily lives. In cyber-physical systems, which connect the physical and the digital world, software does not only influence how we perceive and interact with our environment but software also makes decisions that influence our behavior. Therefore, the ability of software systems to explain their behavior and decisions will become an important property that will be crucial for their acceptance in our society. We call software systems with this ability explainable software systems. In the past, we have worked on methods and tools to design explainable software systems. In this article, we highlight some of our work on how to design explainable software systems. More specifically, we describe an architectural framework for designing self-explainable software systems, which is based on the MAPE-loop for self-adaptive systems. Afterward, we show that explainability is also important for tools that are used by engineers during the development of software systems. We show examples from the area of requirements engineering where we use techniques from natural language processing and neural networks to help engineers comprehend the complex information structures embedded in system requirements.
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5

Suhler, P. A., N. Bagherzadeh, M. Malek, and N. Iscoe. "Software Authorization Systems." IEEE Software 3, no. 5 (1986): 34–41. http://dx.doi.org/10.1109/ms.1986.234396.

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6

Del Ra, William. "Software systems architecture." ACM SIGSOFT Software Engineering Notes 37, no. 2 (2012): 36. http://dx.doi.org/10.1145/2108144.2108171.

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7

Becker, Steffen, Wilhelm Hasselbring, Alexandra Paul, et al. "Trustworthy software systems." ACM SIGSOFT Software Engineering Notes 31, no. 6 (2006): 1–18. http://dx.doi.org/10.1145/1218776.1218781.

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8

Del Ra, William. "Software build systems." ACM SIGSOFT Software Engineering Notes 36, no. 4 (2011): 33–34. http://dx.doi.org/10.1145/1988997.1989005.

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9

Jones, Russell. "Supporting systems software." Data Processing 27, no. 5 (1985): 19–21. http://dx.doi.org/10.1016/0011-684x(85)90131-5.

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10

da Silva, Dilma M., and Fabio Kon. "Adaptive software systems." Journal of the Brazilian Computer Society 10, no. 1 (2004): 3–4. http://dx.doi.org/10.1007/bf03192349.

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11

Conn, Richard. "Software Systems Requirements." Journal on Educational Resources in Computing 2, no. 4 (2002): 1. http://dx.doi.org/10.1145/949257.949258.

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12

&NA;. "INFORMATION SYSTEMS SOFTWARE." Nursing Management (Springhouse) 31, no. 9 (2000): 44. http://dx.doi.org/10.1097/00006247-200009000-00028.

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13

Boasson, M. "Control systems software." IEEE Transactions on Automatic Control 38, no. 7 (1993): 1094–106. http://dx.doi.org/10.1109/9.231463.

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14

Bernstein, Larry. "Trustworthy software systems." ACM SIGSOFT Software Engineering Notes 30, no. 1 (2005): 4–5. http://dx.doi.org/10.1145/1039174.1039176.

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15

Leu, M. C. "Robotics software systems." Robotics and Computer-Integrated Manufacturing 2, no. 1 (1985): 1–12. http://dx.doi.org/10.1016/0736-5845(85)90002-x.

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16

Sherer, Susan A. "Purchasing software systems." Information & Management 24, no. 5 (1993): 257–66. http://dx.doi.org/10.1016/0378-7206(93)90003-c.

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17

N, Ausheva, and Shapovalova s. "TECHNOLOGIES OF INFERENCE IN SOFTWARE SYSTEMS." Modern problems of modeling 23 (May 24, 2022): 11–20. http://dx.doi.org/10.33842/2313-125x-2023-23-11-20.

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18

DZIURBAN, Eduard, and Oksana YASHYNA. "METHOD OF EVALUATION OF OBJECT-ORIENTED SOFTWARE SYSTEMS BASED ON THE ANALYSIS OF CHANGES IN THE SOFTWARE SYSTEM REQUIREMENTS." Herald of Khmelnytskyi National University. Technical sciences 315, no. 6(1) (2022): 77–81. http://dx.doi.org/10.31891/2307-5732-2022-315-6-77-81.

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It is a well-known fact that software maintenance plays an important role and becomes important in the software life cycle. Since object-oriented programming has long become the standard, it is very important to understand the problems of maintaining object-oriented software systems, and how to avoid them by identifying potential gaps in the software system as early as the design analysis. This article is aimed at evaluating object-oriented systems using the analysis of changes in the requirements for the software system. The main problems raised in the article are the change of the algorithm for analyzing the impact of changing non-functional requirements on functional ones and their inheritance. The demand for efficient software is increasing day by day, and the adoption of object-oriented design of software systems is able to satisfy this demand, as it is perhaps the most powerful mechanism for developing efficient software systems. This can not only help in reducing the cost but also helps in developing high quality system software. Software developers need appropriate metrics to develop an effective software system. This practice is aimed at researching methods for evaluating an object-oriented software system using software impact analysis based on tracking requirements to changes in functional requirements using non- functional requirements. Although there are many advantages to the object-oriented approach, and the fact that this approach is the most widespread now and will be in the future, it will be truly recognized, proven and practical only when the management aspects of the software development process using of this methodology will be carefully considered. This is where software metrics play an important role, enabling better planning, evaluating improvements, reducing unpredictability, early detection of potential problems, and evaluating performance. This paper proposes a set of metrics best suited to evaluate the use of core concepts of the object-oriented paradigm, such as inheritance, encapsulation, polymorphism, and a strong emphasis on code reuse, which are uniquely responsible for increasing software quality and development productivity.
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19

Korablin, Y. P., and A. A. Shipov. "Questions of verification in distributed software systems." Contemporary problems of social work 1, no. 2 (2015): 102–6. http://dx.doi.org/10.17922/2412-5466-2015-1-2-102-106.

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20

ARAI, Tamio. "Software systems for assembly." Journal of the Japan Society for Precision Engineering 57, no. 2 (1991): 221–23. http://dx.doi.org/10.2493/jjspe.57.221.

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21

USHIDA, Hirohide, and Hiroshi NAKAJIMA. "Software Systems with Emotion." Journal of Japan Society for Fuzzy Theory and Systems 12, no. 6 (2000): 762–69. http://dx.doi.org/10.3156/jfuzzy.12.6_44.

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22

Lenin, R. B., S. Ramaswamy, Liguo Yu, and R. B. Govindan. "Open Source Software Systems." International Journal of Open Source Software and Processes 2, no. 4 (2010): 28–47. http://dx.doi.org/10.4018/ijossp.2010100103.

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Complex software systems and the huge amounts of data they produce are becoming an integral part of our organizations. We are also becoming increasingly dependent on high quality software products in our everyday lives. These systems ‘evolve’ as we identify and correct existing defects, provide new functionalities, or increase their nonfunctional qualities - such as security, maintainability, performance, etc. Simultaneously, more software development projects are distributed over multiple locations (often globally) and are often several millions of dollars in development costs. Consequently, as the Internet continually eliminates geographic boundaries, the concept of doing business within a single country has given way to companies focusing on competing in an international marketplace. The digitalization of work and the reorganization of work processes across many organizations have resulted in routine and/or commodity components being outsourced.
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23

Mössinger, Jürgen. "Software in Automotive Systems." IEEE Software 27, no. 2 (2010): 92–94. http://dx.doi.org/10.1109/ms.2010.55.

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24

Collings, Patti B. "Fathom: Dynamic Systems Software." American Statistician 55, no. 3 (2001): 258–59. http://dx.doi.org/10.1198/tas.2001.s123.

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25

Wing, Jeannette M., and Mandana Vaziri-Farahani. "Model checking software systems." ACM SIGSOFT Software Engineering Notes 20, no. 4 (1995): 128–39. http://dx.doi.org/10.1145/222132.222148.

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26

Gardner, Philippa. "Verified trustworthy software systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2104 (2017): 20150408. http://dx.doi.org/10.1098/rsta.2015.0408.

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27

Rice, J. R. "Future scientific software systems." IEEE Computational Science and Engineering 4, no. 2 (1997): 44–48. http://dx.doi.org/10.1109/99.609831.

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28

Lane, Chris. "Systems software integrity assurance." ACM SIGAda Ada Letters 30, no. 3 (2010): 11–12. http://dx.doi.org/10.1145/1879097.1879071.

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29

Hamlet, Dick. "Continuity in software systems." ACM SIGSOFT Software Engineering Notes 27, no. 4 (2002): 196–200. http://dx.doi.org/10.1145/566171.566203.

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30

Pruett, G., A. Abbondanzio, J. Bielski, et al. "BladeCenter systems management software." IBM Journal of Research and Development 49, no. 6 (2005): 963–75. http://dx.doi.org/10.1147/rd.496.0963.

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31

Crnkovic, Ivica, and Judith Stafford. "Embedded Systems Software Architecture." Journal of Systems Architecture 59, no. 10 (2013): 1013–14. http://dx.doi.org/10.1016/j.sysarc.2013.11.005.

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32

Müllerburg, M. "Software intensive embedded systems." Information and Software Technology 41, no. 14 (1999): 979–84. http://dx.doi.org/10.1016/s0950-5849(99)00072-5.

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33

Limebeer, David J. N. "Control systems software reviews." Automatica 30, no. 4 (1994): 563. http://dx.doi.org/10.1016/0005-1098(94)90140-6.

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34

Dudkin, M. V., A. I. Kaz'min, A. A. Menn, and V. N. Popolitov. "FMS Software Development Systems." IFAC Proceedings Volumes 19, no. 2 (1986): 131–35. http://dx.doi.org/10.1016/s1474-6670(17)64110-7.

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35

OHTAKE, HISAO, TOSHIO TSUJI, and HIROYUKI KURATA. "Software of Living Systems." KAGAKU KOGAKU RONBUNSHU 25, no. 2 (1999): 169–76. http://dx.doi.org/10.1252/kakoronbunshu.25.169.

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36

Chen, I. R. "High Assurance Software Systems." Computer Journal 49, no. 5 (2006): 507–8. http://dx.doi.org/10.1093/comjnl/bxl040.

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37

Hasselbring, W., and R. Reussner. "Toward Trustworthy Software Systems." Computer 39, no. 4 (2006): 91–92. http://dx.doi.org/10.1109/mc.2006.142.

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38

Rechtin, Eberhardt. "Software systems architecting (abstract)." ACM SIGSOFT Software Engineering Notes 21, no. 6 (1996): 1. http://dx.doi.org/10.1145/250707.239102.

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39

Ritter, Norbert. "Engineering adaptive software systems." it – Information Technology 56, no. 1 (2014): 1–3. http://dx.doi.org/10.1515/itit-2014-9001.

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40

Murphy, E. E., and J. Voelcker. "Technology '90: systems software." IEEE Spectrum 27, no. 1 (1990): 38–40. http://dx.doi.org/10.1109/6.45053.

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41

Jackson, Daniel, Martyn Thomas, Lynette I. Millett, and Trace Baker. "Software For Dependable Systems." INSIGHT 11, no. 2 (2008): 62–63. http://dx.doi.org/10.1002/inst.200811262.

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42

Buffet, Pierre. "Telecommunication systems and software." World Patent Information 14, no. 1 (1992): 13–16. http://dx.doi.org/10.1016/0172-2190(92)90144-8.

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43

Atamtürk, Alper, and Martin W. P. Savelsbergh. "Integer-Programming Software Systems." Annals of Operations Research 140, no. 1 (2005): 67–124. http://dx.doi.org/10.1007/s10479-005-3968-2.

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44

Cooney, Timothy M. "Software: Decision Support Systems." Journal of Forestry 84, no. 1 (1986): 13–14. http://dx.doi.org/10.1093/jof/84.1.13.

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45

Суханова, Наталия, Nataliya Sukhanova, Юрий Соломенцев, et al. "Automation software reliability assessment software for control systems." Bulletin of Bryansk state technical university 2015, no. 3 (2015): 157–60. http://dx.doi.org/10.12737/23018.

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Software is complex and expensive product. As to the automation systems are applied the high wants, included reliability of software. To realize projects in the field of automation of technolo-gy processes it is necessary to construct the new software and to improve, adapt and transfer existing software. The field of investigations and trial of software reliability was not automated yet, the instrumental tools are absent, witch can allow to estimate reliability indexes at all stages of software life cycle. In the article it is developed the structure of automation system for soft-ware reliability monitoring.
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46

Petkov, Doncho, Denis Edgar-Nevill, Raymond Madachy, and Rory O’Connor. "Information Systems, Software Engineering, and Systems Thinking." International Journal of Information Technologies and Systems Approach 1, no. 1 (2008): 62–78. http://dx.doi.org/10.4018/jitsa.2008010105.

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47

Carithers, W. R. "Systems software: An introduction to systems programming." Proceedings of the IEEE 75, no. 3 (1987): 431. http://dx.doi.org/10.1109/proc.1987.13750.

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48

Rine, David. "A note on software engineering, software systems engineering and software design." ACM SIGSOFT Software Engineering Notes 18, no. 4 (1993): 16–18. http://dx.doi.org/10.1145/163626.163629.

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49

Sydorov, N. O., and N. M. Sydorova. "Software engineering and big data software." PROBLEMS IN PROGRAMMING, no. 3-4 (December 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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50

Steinbrückner, Frank, and Claus Lewerentz. "Understanding software evolution with software cities." Information Visualization 12, no. 2 (2012): 200–216. http://dx.doi.org/10.1177/1473871612438785.

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Software cities are visualizations of software systems in the form of virtual cities. They are used as platforms to integrate a large variety of product- and process-related analysis data. Their usability, however, for real-world software development often suffers from their inability to appropriately deal with software changes. Even small structural changes can disrupt the overall structure of the city, which in turn corrupts the mental maps of its users. In this article we describe a systematic approach to utilize the city metaphor for the visualization of evolving software systems as growing software cities. The main contribution is a new layout approach which explicitly takes the development history of software systems into account. The approach has two important effects: first, it creates a stable gestalt of software cities even when the underlying software systems evolve; thus, by preserving its users’ mental maps these cities are especially suitable for use during ongoing system development. Second, it makes history directly visible in the city layouts, which allows for supporting novel analysis scenarios. We illustrate such scenarios by presenting several thematic cities’ maps, each capturing specific development history aspects.
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