Development Risk Assessment in Software Projects Using Dependability Models

2013 ◽  
Author(s):  
A. Melo ◽  
E. Tavares ◽  
M. Marinho ◽  
E. Sousa ◽  
B. Nogueira ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Software Projects ◽  
Development Risk

Towards an efficient risk assessment in software projects–Fuzzy reinforcement paradigm

2018 ◽  
Vol 71 ◽  
pp. 833-846 ◽  
Author(s):  
Arun Kumar Sangaiah ◽  
Oluwarotimi Williams Samuel ◽  
Xiong Li ◽  
Mohamed Abdel-Basset ◽  
Haoxiang Wang
Keyword(s):  
Risk Assessment ◽  
Software Projects

An Early Multi-Criteria Risk Assessment Model

2019 ◽  
Vol 21 (2) ◽  
pp. 51-64
Author(s):  
Priyanka Chandani ◽  
Chetna Gupta
Keyword(s):  
Risk Assessment ◽  
Software Development ◽  
Cumulative Risk ◽  
Requirement Engineering ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Software Projects ◽  
Development Life Cycle ◽  
Weighted Score ◽  
Development Phases

Accurate time and budget is an essential estimate for planning software projects correctly. Quite often, the software projects fall into unrealistic estimates and the core reason generally owes to problems with the requirement analysis. For investigating such problems, risk has to identified and assessed at the requirement engineering phase only so that defects do not seep down to other software development phases. This article proposes a multi-criteria risk assessment model to compute risk at a requirement level by computing cumulative risk score based on a weighted score assigned to each criterion. The result of comparison with other approaches and experimentation shows that using this model it is possible to predict the risk at the early phase of software development life cycle with high accuracy.

A Risk Assessment Framework for Airport Development Projects

2018 ◽  
Vol 2672 (29) ◽  
pp. 35-47
Author(s):  
Anna Hopper
Keyword(s):  
Risk Assessment ◽  
Financial Risk ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Development Projects ◽  
Assessment Framework ◽  
Risk Mitigation Strategies ◽  
Risk Forecast ◽  
Risk Determinants ◽  
Development Risk

This paper develops a risk assessment framework for airport development projects. It discusses the major types of inherent development risk, including political risk, environmental risk, financial risk, airline risk, forecast risk, and regulatory or operational risk, and it offers suggestions for risk mitigation strategies. Furthermore, it identifies and analyzes relative risk determinants, which affect the magnitude and type of risk that development projects will likely face. These include the presence of a dominant airline, the airport’s rate structure, the airport’s ownership and operating structure, local demand, and geopolitical events. These factors and their interconnected relationships are illustrated through case studies of relevant airport development projects.

scholarly journals A Risk Assessment Framework to Reduce Risk Level and Optimize Software Quality

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Sanjeev Puri
Keyword(s):  
Risk Assessment ◽  
Risk Analysis ◽  
Security Policy ◽  
Management Control ◽  
Risk Level ◽  
Assessment Framework ◽  
Security Risk ◽  
Software Projects ◽  
Risk Levels ◽  
Reduce Risk

Risk management for software projects is intended to minimize the chances of unexpected events, or more specifically to keep all possible outcomes under tight management control with making judgments about how risk events are to be treated, valued, compared and combined. It is necessary to have some well-founded infrastructure for the identification of software security risks as well as the application of appropriate controls to manage risks. To be truly beneficial, the risk analysis framework must be granular and practical enough to produce a customizable roadmap of which problems exist, and to rank them in order of severity. The paper a risk assessment framework for a precise, unambiguous and efficient risk analysis with qualitative risk analysis methodologies and tree based techniques by exploiting the synthesis of risk analysis methods with object-oriented modeling, semi-formal methods and tools, in order to improve the security risk analysis of software and security policy implementation of security-cri tical systems to reduce risk levels and optimizequality instructions.

scholarly journals Research of Risk Evaluation Model for CBM Development Based on Multi-Information Fusion

2015 ◽  
Vol 8 (1) ◽  
pp. 337-340 ◽  
Author(s):  
Yongchang Zhang ◽  
Yongguo Yang
Keyword(s):  
Risk Assessment ◽  
Information Fusion ◽  
Evaluation Model ◽  
Assessment Model ◽  
High Yield ◽  
Risk Assessment Model ◽  
Energy Projects ◽  
High Investment ◽  
Development Risk ◽  
Risk Evaluation Model

CBM development is a major concern in national energy projects. With high investment, high risks and high yield, CBM enables many investors generate the project plans while expressing concerns at the same time regarding the risks. Focusing on the development of risk assessment model in CBM development and applications, this paper proposes the CBM development risk assessment model of multi-information fusion, describing in detail the composite structure and application methods of the model, and eventually proves the model feasibility and significance by practical instances.

scholarly journals Development of Rule-Based Software Risk Assessment and Management Method with Fuzzy Inference System

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Mustafa Batar ◽  
Kökten Ulaş Birant ◽  
Ali Hakan Işık
Keyword(s):  
Risk Assessment ◽  
Software Development ◽  
Fuzzy Inference ◽  
Development Projects ◽  
Software Projects ◽  
Inference System ◽  
Rule Based ◽  
Management Method ◽  
Software Risk ◽  
Risk Assessment And Management

There is an enormous budget and financial plan in software development projects, and it is required that they take a huge investment to carry on. When looked at, the costs depend on the global substantial information about software development: in 1985, $150 billion; in 2010, $2 trillion; in 2015, $5 trillion; and in 2020, over $7 trillion. Additionally, on the first new days of 2021, a day-by-day Apple Store’s quantity has been approximately $500 million. In spite of the expenditures and the margins that are dramatically expanding and increasing each year, the phase of software development accomplishment is not high enough. In light of the “CHAOS” report arranged in 2015, just 17% of the software projects were finished in an opportune way, in the allotted financial plan, and as per the necessities. However, 53% of the software projects were finished in the long run or potentially over a spending plan as well as without satisfying the prerequisites precisely. In addition, software development projects were not completed and were dropped out as well in the ratio of 30%. Also, the “CHAOS” report published in 2020 has figured out that only 33% of the software projects were completed successfully all over the world. In order to cope with these unsuccessful and failure results, an effective method for software risk assessment and management has to be specified, designated, and applied. In this way, before causing trouble that has the power of preventing successful accomplishment of software development projects, software risks are able to be noticed and distinguished on time. In this study, a new and original rule set, which could be used and carried out effectively in software risk assessment and management, has been designed and developed based on the implementation of fuzzy approached technique integrated with machine learning algorithm—Adaptive Neuro-Fuzzy Inference System (ANFIS). By this approach and technique, machines (computers) are able to create several software risk rules not to be seen, not to be recognized, and not to be told by human beings. In addition, this fuzzy inference approach aims to decrease risks in the software development process in order to increase the success rate of the software projects. Also, the experimental results of this approach show that rule-based software risk assessment and management method has a valid and accurate model with a high accuracy rate and low average testing error.

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