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Journal articles on the topic 'Software risk management'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 March 2023

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1

Fairley, R. E. "Software Risk Management." IEEE Software 22, no. 3 (May 2005): 101. http://dx.doi.org/10.1109/ms.2005.77.

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2

Boehm, B. W., and T. DeMarco. "Software risk management." IEEE Software 14, no. 3 (May 1997): 17–19. http://dx.doi.org/10.1109/ms.1997.589225.

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3

Murthi, S. "Preventive risk management software for software projects." IT Professional 4, no. 5 (September 2002): 9–15. http://dx.doi.org/10.1109/mitp.2002.1041172.

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4

Lyytinen, Kalle, Lars Mathiassen, and Janne Ropponen. "A Framework for Software Risk Management." Journal of Information Technology 11, no. 4 (December 1996): 275–85. http://dx.doi.org/10.1177/026839629601100402.

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We present a simple, but powerful framework for software risk management. The framework synthesizes, refines, and extends current approaches to managing software risks. We illustrate its usefulness through an empirical analysis of two software development episodes involving high risks. The framework can be used as an analytical device to evaluate and improve risk management approaches and as a practical tool to shape the attention and guide the actions of risk managers.
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5

Cui, Wei, Jia Ye, Yan Lin, Si Yu Qian, Yang Liu, Hai Feng Yang, and Ya Jun Li. "Japan Software Project Risk Management." Advanced Materials Research 267 (June 2011): 175–78. http://dx.doi.org/10.4028/www.scientific.net/amr.267.175.

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With the current domestic software outsourcing business with Japan's rise of a large number of outsourcing projects from Japan such as NEC, Hitachi, Toshiba and other large Japanese companies over billing, not only promoted the growth of the domestic economy, but also led to domestic software improve the overall business. In Dalian, the Dalian City party committee and government attach great importance to the development of the software industry, software industry has become the revitalization of old industrial bases to accelerate the economic development of Dalian's one of the important strategies. However, orders easier to do a single hard, if we really want Japan to do a good job outsourcing, is not so simple. How to make the project successful? In the process of the project will encounter those problems? What is the project's impact? These issues will be troubled by the development of each project managers. These are the risks of the project, how to effectively manage the risks, the success of the project is to explore the theme of this article.
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6

Fairley, R. "Risk management for software projects." IEEE Software 11, no. 3 (May 1994): 57–67. http://dx.doi.org/10.1109/52.281716.

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7

Dedolph, F. Michael. "The neglected management activity: Software risk management." Bell Labs Technical Journal 8, no. 3 (December 9, 2003): 91–95. http://dx.doi.org/10.1002/bltj.10077.

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8

Valério, Karollay Giuliani Oliveira, Carlos Eduardo Sanches da Silva, and Sandra Miranda Neves. "Risk Management in Software Development Projects." International Journal of Open Source Software and Processes 11, no. 1 (January 2020): 1–22. http://dx.doi.org/10.4018/ijossp.2020010101.

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Effective risk management contributes to the success of the software development project. The goal of this work was to identify risk management gaps, perspectives, the evolution of the theme and the study trends, in software development projects, using systematic literature review as a method. For the bibliometric analysis, articles referring to the topic were selected in the period from 2010 to 2018. As tools of analysis, Citespace and VOS Viewer software were used, allowing a comparative evaluation between the articles, as well as the analysis of clusters. Beyond content analysis of articles found. Gaps were identified for performance; team involvement; attention to failures; identification of tools for decision-making; and business strategy. In turn, perspectives were determined for research trends, such as the close relationship between business strategy, risk management and new management models. The research can propose new strategies and perspectives for risk management in software development and show their importance to the academic and practical spheres, demonstrating that the themes are complementary and important in the current technological and innovation sector.
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9

Soni, Dr Rachna. "Potential Factors for Software Risk Management." International Journal for Research in Applied Science and Engineering Technology 6, no. 4 (April 30, 2018): 3227–31. http://dx.doi.org/10.22214/ijraset.2018.4537.

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10

Lyytinen, Kalle, Lars Mathiassen, and Janne Ropponen. "A Framework for software risk management." Journal of Information Technology 11, no. 4 (December 1996): 275–85. http://dx.doi.org/10.1057/jit.1996.2.

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11

Mohtashami, Mojgan, Thomas Marlowe, Vassilka Kirova, and Fadi P. Deek. "Risk Management for Collaborative Software Development." EDPACS 35, no. 3 (March 26, 2007): 10–24. http://dx.doi.org/10.1080/07366980701307536.

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12

Boehm, B. W. "Software risk management: principles and practices." IEEE Software 8, no. 1 (January 1991): 32–41. http://dx.doi.org/10.1109/52.62930.

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13

Chittister, C. G., and Y. Y. Haimes. "Systems integration via software risk management." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 26, no. 5 (1996): 521–32. http://dx.doi.org/10.1109/3468.531900.

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14

Misra, Subhas C., Uma Kumar, Vinod Kumar, and Mahmud A. Shareef. "Risk management models in software engineering." International Journal of Process Management and Benchmarking 2, no. 1 (2007): 59. http://dx.doi.org/10.1504/ijpmb.2007.013318.

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15

Mohtashami, Mojgan, Thomas Marlowe, Vassilka Kirova, and Fadi P. Deek. "Risk Management for Collaborative Software Development." Information Systems Management 23, no. 4 (September 2006): 20–30. http://dx.doi.org/10.1201/1078.10580530/46352.23.4.20060901/95109.3.

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16

Fan, Chin-Feng, and Yuan-Chang Yu. "BBN-based software project risk management." Journal of Systems and Software 73, no. 2 (October 2004): 193–203. http://dx.doi.org/10.1016/j.jss.2003.12.032.

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17

Odzaly, Edzreena Edza, Des Greer, and Darryl Stewart. "Agile risk management using software agents." Journal of Ambient Intelligence and Humanized Computing 9, no. 3 (May 2, 2017): 823–41. http://dx.doi.org/10.1007/s12652-017-0488-2.

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18

Kumar, Nilesh, Deepak Shaharan, and Nishant Kumar. "Risk Management in Software Projects with Microcontroller." Journal of Advance Research in Mechanical & Civil Engineering (ISSN: 2208-2379) 1, no. 1 (January 31, 2014): 25–30. http://dx.doi.org/10.53555/nnmce.v1i1.380.

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The main motive to present this paper is to provide a secure management in software with the help of sense controlled device microcontroller This paper reviews the basic concepts, terminology, and techniques of Software Risk Management. It teaches readers how to identify and analyse software risks on their projects. Readers then learn techniques for planning indicting to mitigate risks so that the overall impact of those risks on their projects is minimized.
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19

Taimoor Hasan. "Analyzing and Resolving Issues in Software Project Risk Management." Lahore Garrison University Research Journal of Computer Science and Information Technology 1, no. 1 (March 31, 2017): 13–21. http://dx.doi.org/10.54692/lgurjcsit.2017.01012.

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In last decade the main reason for projects failure is poormanagement of software. But now a day’s most of the organizations arefocusing on software project management for making project successful.Software project management provides overall management of softwarefrom project planning phase to project execution. In software projectmanagement we also deal with risks that may occur during developmentof projects. In this paper we analyze risks during management ofsoftware and we resolve issues that come in software project riskmanagement. We introduce some approaches by which we can resolveall the issues regarding software risk management. Risk managementalso suggests us that how we can avoid risks and if risks occur then howwe can control those risks. By analyzing software risk management, wecome to know that what factors affect risk management and how we canremove them. Software risk management manages all risks efficientlyand makes our project successful.
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20

Bannerman, Paul L. "Risk and risk management in software projects: A reassessment." Journal of Systems and Software 81, no. 12 (December 2008): 2118–33. http://dx.doi.org/10.1016/j.jss.2008.03.059.

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21

Vogel, David A. "Software Safety for Every Phase of Software Development." Biomedical Instrumentation & Technology 40, no. 4 (July 1, 2006): 309–14. http://dx.doi.org/10.2345/i0899-8205-40-4-309.1.

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Abstract Where does risk management belong, at the beginning of a project or at the end? Many managers choose one or the other, or both. The correct answer is that risk management needs to be considered throughout the software development life cycle. When the risks include the safety of patients or the users of the software, the methods need to be more formal. This article will explain why, and then will provide the how and the how much.
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22

Zhang, Jiongjie. "Analysis on Risk Management of Software Outsourcing Project." BCP Business & Management 24 (August 10, 2022): 226–32. http://dx.doi.org/10.54691/bcpbm.v24i.1486.

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Nowadays many companies outsource the whole or part of software projects to other companies to reduce the cost of software projects and focus on the development of core competitive businesses. Due to the rapid update and iteration speed of information technology, the complexity of software projects is also increasing, and the risk factors in software outsourcing projects are also increasing. The existence of these risks can prolong the project cycle, or directly lead to project failure. At present, many software outsourcing companies do not pay much attention to project risk management, and cannot effectively identify, supervise and deal with risks, resulting in out of control or even failure of software outsourcing projects. This paper will summarize the list of risk factors by studying the characteristics and status quo of today's outsourcing projects, and analyzing the possible analysis of each stage of software outsourcing projects. Use brainstorming, expert assessment, and qualitative analysis to evaluate and identify risk factors. Finally, from a practical point of view, this paper will put forward some suggestions for the future software outsourcing project risk management. I hope to achieve two purposes through the research of this paper. One is to contribute some research experience to the risk management of software outsourcing projects and guide the actual work of enterprises. Second, we should advocate innovative thinking and encourage more and better ideas to emerge.
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23

DeMarco, T., and T. Lister. "Risk management during requirements." IEEE Software 20, no. 5 (September 2003): 99–101. http://dx.doi.org/10.1109/ms.2003.1231163.

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24

Chittister, C., and Y. Y. Haimes. "Assessment and management of software technical risk." IEEE Transactions on Systems, Man, and Cybernetics 24, no. 2 (1994): 187–202. http://dx.doi.org/10.1109/21.281419.

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25

Conrow, E. H., and P. S. Shishido. "Implementing risk management on software intensive projects." IEEE Software 14, no. 3 (1997): 83–89. http://dx.doi.org/10.1109/52.589242.

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26

Hilali, Raqiya Ahmed Al, and Smiju Sudevan. "Software Project Risk Management Practice in Oman." International Journal of Electrical, Electronics and Computers 5, no. 6 (2020): 32–47. http://dx.doi.org/10.22161/eec.563.

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27

Afshari, Ali, Vladimir Brtka, and Melita Ćoćkalo-Hronjec. "Project risk management in Iranian software projects." Journal of Engineering Management and Competitiveness 8, no. 2 (2018): 81–88. http://dx.doi.org/10.5937/jemc1802081a.

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28

Tavares, Breno Gontijo, Carlos Eduardo Sanches da Silva, and Adler Diniz de Souza. "Risk management analysis in Scrum software projects." International Transactions in Operational Research 26, no. 5 (March 8, 2017): 1884–905. http://dx.doi.org/10.1111/itor.12401.

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29

Teklemariam, Mihret Abeselom, and Ernest Mnkandla. "Software Project Risk Management Practice in Ethiopia." Electronic Journal of Information Systems in Developing Countries 79, no. 1 (March 2017): 1–14. http://dx.doi.org/10.1002/j.1681-4835.2017.tb00583.x.

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30

SCHNEIDEWIND, NORMAN. "SOFTWARE RISK ANALYSIS." International Journal of Reliability, Quality and Safety Engineering 16, no. 02 (April 2009): 117–36. http://dx.doi.org/10.1142/s0218539309003320.

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There has been a lack of attention to the subject of risk management in the design and operation of software. This is strange because the risk to reliability is a critical problem in attempts to achieve a safe operation of the software. To address this problem, we evaluate existing models and introduce a new model for software risk prediction. The new model — cumulative failures gradient function — is based on the principles of neural networks. This metric identifiers the minimum test time required to achieve maximum improvement in software quality. We used three NASA Space Shuttle software systems in the evaluation of both existing and new models. The results showed that it was not possible to consistently rank these systems because the validity of the risk predictions varied depending on the risk model that was used. Therefore, the results suggest that it is advisable to use a variety of models to comprehensively evaluate the software risk.
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31

Castro, Laura M., Víctor M. Gulías, Carlos Abalde, and J. Santiago Jorge. "Managing the Risks of Risk Management." Journal of Decision Systems 17, no. 4 (January 2008): 501–21. http://dx.doi.org/10.3166/jds.17.501-521.

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32

Kwan, Tak Wah, and Hareton K. N. Leung. "A Risk Management Methodology for Project Risk Dependencies." IEEE Transactions on Software Engineering 37, no. 5 (September 2011): 635–48. http://dx.doi.org/10.1109/tse.2010.108.

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33

Jiang, James J., Gary Klein, and T. Selwyn Ellis. "A Measure of Software Development Risk." Project Management Journal 33, no. 3 (September 2002): 30–41. http://dx.doi.org/10.1177/875697280203300305.

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Risks to software development are present throughout the creation of information systems (IS). The ability of researchers and practitioners to consider risk within their models and project management methods has been hampered by the lack of a rigorously tested instrument to measure risk properties. An instrument to measure software development risk based on properties described in the literature is proposed. A survey of 152 IS project participants was collected to examine the reliability and validity of the instrument, both which appear strong. The instrument then was used to empirically demonstrate a strong anticipated relationship between risk and project success.
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34

Poth, Alexander, and Ali Sunyaev. "Effective Quality Management: Value- and Risk-Based Software Quality Management." IEEE Software 31, no. 6 (November 2014): 79–85. http://dx.doi.org/10.1109/ms.2013.138.

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35

PENG, YI, GANG KOU, GUOXUN WANG, HONGGANG WANG, and FRANZ I. S. KO. "EMPIRICAL EVALUATION OF CLASSIFIERS FOR SOFTWARE RISK MANAGEMENT." International Journal of Information Technology & Decision Making 08, no. 04 (December 2009): 749–67. http://dx.doi.org/10.1142/s0219622009003715.

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Software development involves plenty of risks, and errors exist in software modules represent a major kind of risk. Software defect prediction techniques and tools that identify software errors play a crucial role in software risk management. Among software defect prediction techniques, classification is a commonly used approach. Various types of classifiers have been applied to software defect prediction in recent years. How to select an adequate classifier (or set of classifiers) to identify error prone software modules is an important task for software development organizations. There are many different measures for classifiers and each measure is intended for assessing different aspect of a classifier. This paper developed a performance metric that combines various measures to evaluate the quality of classifiers for software defect prediction. The performance metric is analyzed experimentally using 13 classifiers on 11 public domain software defect datasets. The results of the experiment indicate that support vector machines (SVM), C4.5 algorithm, and K-nearest-neighbor algorithm ranked the top three classifiers.
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36

M.Elhady, Abdelghafar, Ahmed Abou Elfetouh S., Hazem M. El-bakry, and A. E. Hassan. "Generic Software Risk Management Framework for SCADA System." International Journal of Computer Applications 70, no. 3 (May 17, 2013): 45–52. http://dx.doi.org/10.5120/11946-7762.

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37

Hall, J. W., I. C. Cruickshank, and P. S. Godfrey. "Software-supported risk management for the construction industry." Proceedings of the Institution of Civil Engineers - Civil Engineering 144, no. 1 (February 2001): 42–48. http://dx.doi.org/10.1680/cien.2001.144.1.42.

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38

Hashmi, Sobia, Majid Kaleem, and Ali Ahmed. "Risk Management for the Development Of Software Project." International Conference on Electrical Engineering 9, no. 9th (May 1, 2014): 1–4. http://dx.doi.org/10.21608/iceeng.2014.30387.

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39

Roy, Mandira, Novarun Deb, Agostino Cortesi, Rituparna Chaki, and Nabendu Chaki. "Requirement-oriented risk management for incremental software development." Innovations in Systems and Software Engineering 17, no. 3 (June 19, 2021): 187–204. http://dx.doi.org/10.1007/s11334-021-00406-6.

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40

Saveliev, D. V. "Risk Management and Assessment in Software Development Projects." Èlektronnoe modelirovanie 43, no. 4 (August 2, 2021): 113–24. http://dx.doi.org/10.15407/emodel.43.04.113.

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The article defines the concept of threat model. Described a list of current security guidelines for the development and administration of web systems. Formed the list of cybersecurity threats, the consequences of their implementation are determined. Described the process of forming a model of cybersecurity threats of web systems. Defined the list of threats based on the recommendations and experience of authoritative organizations in the world and Ukraine. Defined the concepts of risk, risk index and risk status for the security of web systems. Defined the main principles of risk management in software development projects.
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41

KOUTBI, Salma EL, and Ali IDRI. "Software Effort Estimation Risk Management over Projects Portfolio." Computer and Information Science 11, no. 4 (October 31, 2018): 45. http://dx.doi.org/10.5539/cis.v11n4p45.

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Over the last decades, software development effort estimation has integrated new approaches dealing with uncertainty. However, effort estimates are still plagued with errors limiting their reliability. Thus, estimates error management at an organization level provides a promising alternative to the classical approaches dealing with single projects as a portfolio can afford more flexibility and opportunities in terms of risk management. The most widely used approaches in risk management were mainly based on the Gaussian approximation that shows its limits facing “ruin” risk associated to unusual events. The aim of this paper is to propose a Multi-Projects Error Modeling framework to characterize error at a portfolio level using bootstrapping, mixture of Gaussians and power law to emphasize the tail behavior respectively.
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42

Muntés-Mulero, Victor, Oscar Ripolles, Smrati Gupta, Jacek Dominiak, Eric Willeke, Peter Matthews, and Balázs Somosköi. "Agile risk management for multi‐cloud software development." IET Software 13, no. 3 (June 2019): 172–81. http://dx.doi.org/10.1049/iet-sen.2018.5295.

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43

Betts, Kellyn. "Risk-management software tool makes long-overdue debut." Environmental Science & Technology 33, no. 11 (June 1999): 230A—231A. http://dx.doi.org/10.1021/es9928273.

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44

Fairley, R. E. "Risk Management: The Key to Successful Software Projects *." IFAC Proceedings Volumes 23, no. 5 (October 1990): 45–50. http://dx.doi.org/10.1016/s1474-6670(17)52208-9.

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45

Safavi, A. "Computer-based Risk Management in Software Planning/Scheduling." IFAC Proceedings Volumes 23, no. 5 (October 1990): 69–74. http://dx.doi.org/10.1016/s1474-6670(17)52212-0.

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46

Wang, Can, Hong Feng Hou, and Chun Ming Xu. "Research on Risk Management Based on Software Project." Applied Mechanics and Materials 380-384 (August 2013): 2363–66. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.2363.

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This paper focuses on risk management in each phase of life circle of software development and intrduces advisable measures for each risk. Secondly, it presents a formula to calculate risk. In the end, we analyze the sensitivity of risk by illustration, through sensitivity analysis can we find the most dependent index which can provide great assisstance.
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47

Slabospickaya, O. A., and G. Koval. "An integrated technology for intelligent software risk management." Cybernetics and Systems Analysis 45, no. 6 (November 2009): 971–76. http://dx.doi.org/10.1007/s10559-009-9166-5.

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48

Bubevski, Vojo. "A novel approach to software quality risk management." Software Testing, Verification and Reliability 24, no. 2 (January 10, 2013): 124–54. http://dx.doi.org/10.1002/stvr.1488.

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49

Li, Jianping, Minglu Li, Dengsheng Wu, Qianzhi Dai, and Hao Song. "A Bayesian Networks-Based Risk Identification Approach for Software Process Risk: The Context of Chinese Trustworthy Software." International Journal of Information Technology & Decision Making 15, no. 06 (November 2016): 1391–412. http://dx.doi.org/10.1142/s0219622016500401.

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For all of the many advantages and enormous benefits that information technology has brought to us, it has subjected to increasing risks that need enough attention. Bayesian network (BN) is an important probabilistic inference approach to support reasoning under uncertainty. This paper describes how BN is applied to quantify the occurrence probability of software process risk factors and the influence strength among the process risk factors in the context of Chinese trustworthy software. The information of 52 factors was obtained through a questionnaire survey of 93 project managers in five high Capability Maturity Model Integration (CMMI) level software companies. The focus of this paper is to present the key risk checklist and good timing for process risk control to improve software process risk management. Special effort has been put on the description of the experimental study, which provides the top 20 key risk factors in software process and critical software sub-processes for process risk management. The findings can provide the key risk checklist to software risk manager for risk identification and decision-making in process risk management. This is a general approach and, as such, it can be applied to a certain software project or some software enterprises with updated data.
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50

Ali, Hashim, Nousheen Akhtar, and Muhammad Younus Javed. "An Optimized Risk Management Model Based on Software Risk Factors Analysis." Advanced Science Letters 24, no. 4 (April 1, 2018): 2306–11. http://dx.doi.org/10.1166/asl.2018.10941.

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