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Requirement Risk Identification: A Practitioner's Approach

Halima Sadia, Md. Rizwan Beg, Md. Faisal
2014 International Journal of Computer Applications  
In this paper, a method has been proposed to implement inspection technique for identifying the key requirement risk factors responsible in achieving successful outcome and use a Bayesian network approach  ...  It is a well known fact that it is more feasible to make changes to the software system under development in the early stages of the software development cycle.  ...  ., Applying Bayesian Belief Networks to Systems Dependability Assessment.  ... 
doi:10.5120/17890-8886 fatcat:r4cuntowznf2hjezkzfrxb6laa

Large engineering project risk management using a Bayesian belief network

Eunchang Lee, Yongtae Park, Jong Gye Shin
2009 Expert systems with applications  
Keywords: Risk management in large engineering projects Shipbuilding industry Bayesian belief network a b s t r a c t This paper presents a scheme for large engineering project risk management using a  ...  Bayesian belief network and applies it to the Korean shipbuilding industry.  ...  Fig. 1 . 1 Project risk management procedure using a Bayesian belief network.  ... 
doi:10.1016/j.eswa.2008.07.057 fatcat:we3vh3gh2zgebnvw3udxllfhzu

A BOW-TIE BASED RISK FRAMEWORK INTEGRATED WITH A BAYESIAN BELIEF NETWORK APPLIED TO THE PROBABILISTIC RISK ANALYSIS

Jose Cristiano Pereira, Gilson Brito Alves Lima, Annibal Parracho Santanna
2015 Brazilian Journal of Operations & Production Management  
To remedy this problem, the methodology presented in this paper covers the construction of a probabilistic risk analysis model, based on Bayesian Belief Network coupled to a bow-tie diagram.  ...  The use of probabilistic risk analysis in the jet engines manufacturing process is essential to prevent failure.  ...  Considering the context presented above, this paper aims to present a proposal for probabilistic risk analysis based on bow-tie methodology combined with Bayesian Belief Network to analyze critical activities  ... 
doi:10.14488/bjopm.2015.v12.n2.a14 fatcat:ou6k7ovrpnchfgvt6fp54bbiqy

MODELING OF THE PROSPECTS FOR SUSTAINABLE DEVELOPMENT OF AGRICULTURAL TERRITORIES BY THE BAYESIAN NETWORKS

Mykola Tymošenko, Kateryna Golovach
2018 Management Theory and Studies for Rural Business and Infrastructure Development  
The aim of the research is to provide a scientific basis for the need of using the modeling with the help of neural network technologies and to build a Bayesian belief network to make a decision on the  ...  The results of the implementation of the Bayesian network with the help of Netica software for deciding on the sustainable development of village councils in the future based on the questionnaire data  ...  Zare, Zare and Fallahnezhad (2016) implemented a system for evaluating software development projects based on optimal Bayesian networks.  ... 
doi:10.15544/mts.2018.25 fatcat:cg75udi2ejfqlchib3qk4kvr6e

A Survey of Bayesian Network Models for Decision Making System in Software Engineering

Nageswarao M., N. Geethanjali
2016 International Journal of Computer Applications  
Bayesian network model is used to predict the defect correction at various levels of the software development.  ...  Traditional Bayesian networks are system dependable and their models are invariant towards the accurate computation.  ...  Software uncertainties should be modeled using predicted probability values computed using Bayesian belief netwoks.  ... 
doi:10.5120/ijca2016906330 fatcat:cq45rwqsubaadfwszki26bap6q

Analyzing Time-to-Market and Reliability Trade-Offs with Bayesian Belief Networks [chapter]

Jianyun Zhou, Tor Stålhane
2005 Lecture Notes in Computer Science  
Bayesian Belief Networks (BBNs) is used to offer this opportunity.  ...  The use of BBN in software engineering concerns mostly software quality. Recently its application extends to other areas, such as process modeling and cost estimation.  ... 
doi:10.1007/11531371_85 fatcat:uizdb4kzfrhzferxiycniedzey

Probabilistic Assessment of Road Risks for Improving Logistics Processes

Abdelaziz Lakehal, Fouad Tachi, R. Ulewicz, B. Hadzima
2018 MATEC Web of Conferences  
To identify this last problem of road risk and to minimize its influence, a Bayesian network has been developed in this paper.  ...  Through experts' surveys and research in the literature, the various risks were identified. The structure of the Bayesian network is defined on the basis of this census.  ...  Bayesian belief networks tool Like all artificial intelligence techniques, Bayesian networks require inputs.  ... 
doi:10.1051/matecconf/201818301003 fatcat:5igd4diq25e5zkp5huz276tcom

Stroke Prediction Context-Aware Health Care System

Hamid Mcheick, Hoda Nasser, Mohamed Dbouk, Ahmad Nasser
2016 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)  
This paper proposes a prediction framework based on ontology and Bayesian Belief Networks BBN to support a medical teams in every daily.  ...  We propose a Stroke Prediction System (SPS), a new software component to handle the uncertainty of having a stroke disease by determining the risk score level.  ...  Since our system has certain range of uncertainty, we use its ontology to structure a Bayesian belief network.  ... 
doi:10.1109/chase.2016.49 dblp:conf/chase/McheickNDN16 fatcat:akfarbvxtbhjpoak3c7d5dntgy

Bayesian Belief Network Model Quantification Using Distribution-Based Node Probability and Experienced Data Updates for Software Reliability Assessment

Seung Jun Lee, Sang Hun Lee, Tsong-Lun Chu, Athi Varuttamaseni, Meng Yue, Ming Li, Jaehyun Cho, Hyun Gook Kang
2018 IEEE Access  
INDEX TERMS Bayesian belief network, nuclear power plant, probabilistic risk assessment, software reliability. 64556 2169-3536  ...  Based on a Bayesian belief network (BBN) model developed to estimate the number of software faults considering the software development lifecycle, we performed a pilot study of software reliability quantification  ...  In order to estimate the failure probability of the NPP safety graded software and incorporate it into an NPP PRA model, a Bayesian belief network (BBN) model was developed in Kang et al.  ... 
doi:10.1109/access.2018.2878376 fatcat:vbzyticqeraddnfzpm3wuroriu

Quality Prediction and Assessment for Product Lines [chapter]

Hongyu Zhang, Stan Jarzabek, Bo Yang
2003 Lecture Notes in Computer Science  
In this paper, we propose a Bayesian Belief Network (BBN) based approach to quality prediction and assessment for a software product line.  ...  It helps us capture the impact of variants on quality attributes, and helps us predict and assess the quality of a product line member by performing quantitative analysis over it.  ...  Bayesian Belief Network -The Graphical Model Bayesian Belief Network (BBN) is a knowledge representation. It provides a graphical model that resembles human reasoning.  ... 
doi:10.1007/3-540-45017-3_45 fatcat:ww63iuxl2jhndmzawq4aaad3eq

Estimating software robustness in relation to input validation vulnerabilities using Bayesian networks

Ekincan Ufuktepe, Tugkan Tuglular
2017 Software quality journal  
We propose a method for estimating the robustness of software in relation to input validation vulnerabilities using Bayesian networks.  ...  Using our method, software development teams can track changes made to software to deal with invalid inputs. Software Qual J (2018) 26:455-489 457  ...  Kondakci (2010) proposed a network security risk assessment model using Bayesian belief networks (BBNs).  ... 
doi:10.1007/s11219-017-9359-5 fatcat:spuuzv6zunainjyp73wij3cree

INFORMATION SECURITY RISK ASSESSMENT UNDER UNCERTAINTY USING DYNAMIC BAYESIAN NETWORKS

R. Sarala .
2014 International Journal of Research in Engineering and Technology  
The Dynamic Bayesian Network models help to detect the uncertain relationship associated with the risk event.  ...  In this paper, a novel approach is presented; where Dynamic Bayesian Network models are constructed to identify multi stage attacks.  ...  Representing Uncertainty using Bayesian Network Bayesian Belief Networks also known as Probability networks or Causal network are models for representing un-certainty in knowledge.  ... 
doi:10.15623/ijret.2014.0319055 fatcat:2ofmvrw53jectoeyng3u7oypya

Decreased Business Uncertainty by Using Bayesian Networks for the Paradigm Shift in Business Simulator

Alberto Ochoa, Miguel Ruiz-Jaimes, Sandra Leon, Yadira Toledo, Iván Ramírez
2016 Research in Computing Science  
Strategies as the use of Bayesian networks are associated with the behaviors are linked with the variables and scenarios that can be a presenter during the life of the business.  ...  or clothes in Latin America fail in his first two years this due to lack of follow-appropriate decisions to bring out various problems, which is why the business simulators help lessen the burden of analyzing  ...  In software engineering Bayesian networks, have been used in different areas such as: Estimation of effort and quality.  ... 
doi:10.13053/rcs-122-1-7 fatcat:ht37smifbbeatm426fb32znopm

Supply Chain Risk Management: Systematic literature review and a conceptual framework for capturing interdependencies between risks

Abroon Qazi, John Quigley, Alex Dickson
2015 2015 International Conference on Industrial Engineering and Operations Management (IEOM)  
'Systematic Literature Review' method is used to examine quality articles published over a time period of almost 15 years (2000 -June, 2014).  ...  The findings of the study are validated through text mining software. Systematic literature review has identified the progress of research based on various descriptive and thematic typologies.  ...  Based on the efficacy of Bayesian belief networks in handling interdependencies between risks, we propose modeling of an entire network as a Bayesian belief network.  ... 
doi:10.1109/ieom.2015.7093701 fatcat:ym575b6m3bbe7hidi6qu3y4qgi

An analysis on operational risk in international banking: A Bayesian approach (2007–2011)

José Francisco Martínez-Sánchez, María Teresa V. Martínez-Palacios, Francisco Venegas-Martínez
2016 Estudios Gerenciales  
To do this, a Bayesian network (BN) model is designed with prior and subsequent distributions to estimate the frequency and severity.  ...  This study aims to develop a Bayesian methodology to identify, quantify and measure operational risk in several business lines of commercial banking.  ...  In order to quantify the OR at each node of the network, we fit prior distributions by using the @Risk software.  ... 
doi:10.1016/j.estger.2016.06.004 fatcat:4p3xo5gzzbgepgwuhf6yo4bvp4
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