Applying a Knowledge Management Technique to Improve Risk Assessment and Effort Estimation of Healthcare Software Projects

2014 ◽  
pp. 40-56
Author(s):  
Emilia Mendes
Keyword(s):  
Risk Assessment ◽  
Knowledge Management ◽  
Management Technique ◽  
Effort Estimation ◽  
Software Projects

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

Fuzzy Rules for Risk Assessment and Contingency Estimation within COCOMO Software Project Planning Model

2014 ◽  
pp. 88-111 ◽  
Author(s):  
Ekananta Manalif ◽  
Luiz Fernando Capretz ◽  
Danny Ho
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Project Planning ◽  
Project Managers ◽  
Research Data ◽  
Software Project ◽  
Planning Model ◽  
Effort Estimation ◽  
New Approach ◽  
Project Risks

Software development can be considered to be the most uncertain project when compared to other projects due to uncertainty in the customer requirements, the complexity of the process, and the intangible nature of the product. In order to increase the chance of success in managing a software project, the project manager(s) must invest more time and effort in the project planning phase, which involves such primary and integrated activities as effort estimation and risk management, because the accuracy of the effort estimation is highly dependent on the size and number of project risks in a particular software project. However, as is common practice, these two activities are often disconnected from each other and project managers have come to consider such steps to be unreliable due to their lack of accuracy. This chapter introduces the Fuzzy-ExCOM Model, which is used for software project planning and is based on fuzzy technique. It has the capability to not only integrate the effort estimation and risk assessment activities but also to provide information about the estimated effort, the project risks, and the effort contingency allowance necessary to accommodate the identified risk. A validation of this model using the project’s research data shows that this new approach is capable of improving the existing COCOMO estimation performance.

Fuzzy Rules for Risk Assessment and Contingency Estimation Within COCOMO Software Project Planning Model

2018 ◽  
pp. 771-797
Author(s):  
Ekananta Manalif ◽  
Luiz Fernando Capretz ◽  
Danny Ho
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Project Planning ◽  
Project Managers ◽  
Research Data ◽  
Software Project ◽  
Planning Model ◽  
Effort Estimation ◽  
New Approach ◽  
Project Risks

Software development can be considered to be the most uncertain project when compared to other projects due to uncertainty in the customer requirements, the complexity of the process, and the intangible nature of the product. In order to increase the chance of success in managing a software project, the project manager(s) must invest more time and effort in the project planning phase, which involves such primary and integrated activities as effort estimation and risk management, because the accuracy of the effort estimation is highly dependent on the size and number of project risks in a particular software project. However, as is common practice, these two activities are often disconnected from each other and project managers have come to consider such steps to be unreliable due to their lack of accuracy. This chapter introduces the Fuzzy-ExCOM Model, which is used for software project planning and is based on fuzzy technique. It has the capability to not only integrate the effort estimation and risk assessment activities but also to provide information about the estimated effort, the project risks, and the effort contingency allowance necessary to accommodate the identified risk. A validation of this model using the project's research data shows that this new approach is capable of improving the existing COCOMO estimation performance.

The Application of Meta-Heuristic Algorithms to Improve the Performance of Software Development Effort Estimation Models

2015 ◽  
Vol 6 (4) ◽  
pp. 39-68 ◽  
Author(s):  
Maryam Hassani Saadi ◽  
Vahid Khatibi Bardsiri ◽  
Fahimeh Ziaaddini
Keyword(s):  
Software Development ◽  
Optimization Algorithms ◽  
Heuristic Optimization ◽  
Development Effort ◽  
Special Role ◽  
Effort Estimation ◽  
Software Projects ◽  
Software Development Effort ◽  
Estimation Models ◽  
Software Development Effort Estimation

One of the major activities in effective and efficient production of software projects is the precise estimation of software development effort. Estimation of the effort in primary steps of software development is one of the most important challenges in managing software projects. Some reasons for these challenges such as: discordant software projects, the complexity of the manufacturing process, special role of human and high level of obscure and unusual features of software projects can be noted. Predicting the necessary efforts to develop software using meta-heuristic optimization algorithms has made significant progressions in this field. These algorithms have the potent to be used in estimation of the effort of the software. The necessity to increase estimation precision urged the authors to survey the efficiency of some meta-heuristic optimization algorithms and their effects on the software projects. To do so, in this paper, they investigated the effect of combining various optimization algorithms such as genetic algorithm, particle swarm optimization algorithm and ant colony algorithm on different models such as COCOMO, estimation based on analogy, machine learning methods and standard estimation models. These models have employed various data sets to evaluate the results such as COCOMO, Desharnais, NASA, Kemerer, CF, DPS, ISBSG and Koten & Gary. The results of this survey can be used by researchers as a primary reference.

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.

Guest editor's introduction to the special issue “Knowledge Management Technique”

2004 ◽  
Vol 36 (4) ◽  
pp. 339
Author(s):  
Heeseok Lee ◽  
Jae Kyu Lee ◽  
Joon-Seuk Kim
Keyword(s):  
Knowledge Management ◽  
Management Technique ◽  
Special Issue ◽  
Issue Knowledge
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