5,454 research outputs found

    Risk Prioritization using A FUZZY BASED Approach in Software Development Design Phase

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    The success of a software project's objective is directly proportional to the degree to which it satisfies all of the stakeholders' concerns regarding the project's requirements, including the budget, schedule, and overall performance. Risks can occur throughout the software development lifecycle (SDLC) phases and affect every phase. The design phase of the SDLC yields an overview of the software and can be defined as the software's blueprint. Different types of software have their own unique design phases and have different types of risks. With the high number of interacting components, complex systems have a greater propensity to be more volatile, which increases the risk. It is necessary to prioritize the risks in order of their severity levels. The issue at hand is the lack of effective methods to prioritize and mitigate the risk. Recent studies have suggested several methods for prioritizing risks, but it is clear that few of these have been implemented. These methods are overly complicated, time-consuming, prone to inconsistency, and challenging to put into practice. This paper proposes a novel Fuzzy-based approach to risk prioritization in the software design phase using MATLAB software. Fuzzy-based models have been shown to be more accurate than other techniques when using standard datasets to prioritize risks. Fuzzy-based methods that have been proposed take into account the characteristics of risks by modelling those characteristics as fuzz

    The Application of Fuzzy Logic for Test Case Prioritization

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    Diplomová práce je zaměřena na stanovení priority testovacích případů s využitím fuzzy logiky. Vhodným přístupem k získání výstupu na základě definovaného vstupu a stanovených pravidel byl zvolen fuzzy model přiřazující prioritu testovacím případům. K dosažení cíle práce byla nejprve stanovena kritéria, parametry a poté určena jejich váha pro jednotlivé testovací případy. Na závěr jsou vyhodnocena vstupní data s využitím řešení v programu MS Excel a MATLAB.The master’s thesis focuses on determination of Test case priority using Fuzzy logic. As principle of Fuzzy logic is a convenient way to turn given inputs to final output according to defined rules, a Fuzzy based model for assigning Test case priority has been chosen. In order to fulfil the aim of the thesis, firstly particular criteria along with parameters set to each Test case and its weights needs to be defined accordingly. So as to come to the conclusion and evaluate input data, the solution for computing in the program MS Excel and MATLAB is used herein.

    Risk-based maintenance of critical and complex systems

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    Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2016-2017.De nos jours, la plupart des systèmes dans divers secteurs critiques tels que l'aviation, le pétrole et les soins de santé sont devenus très complexes et dynamiques, et par conséquent peuvent à tout moment s'arrêter de fonctionner. Pour éviter que cela ne se reproduise et ne devienne incontrôlable ce qui engagera des pertes énormes en matière de coûts et d'indisponibilité; l'adoption de stratégies de contrôle et de maintenance s'avèrent plus que nécessaire et même vitale. Dans le génie des procédés, les stratégies optimales de maintenance pour ces systèmes pourraient avoir un impact significatif sur la réduction des coûts et sur les temps d'arrêt, sur la maximisation de la fiabilité et de la productivité, sur l'amélioration de la qualité et enfin pour atteindre les objectifs souhaités des compagnies. En outre, les risques et les incertitudes associés à ces systèmes sont souvent composés de plusieurs relations de cause à effet de façon extrêmement complexe. Cela pourrait mener à une augmentation du nombre de défaillances de ces systèmes. Par conséquent, un outil d'analyse de défaillance avancée est nécessaire pour considérer les interactions complexes de défaillance des composants dans les différentes phases du cycle de vie du produit pour assurer les niveaux élevés de sécurité et de fiabilité. Dans cette thèse, on aborde dans un premier temps les lacunes des méthodes d'analyse des risques/échec et celles qui permettent la sélection d'une classe de stratégie de maintenance à adopter. Nous développons ensuite des approches globales pour la maintenance et l'analyse du processus de défaillance fondée sur les risques des systèmes et machines complexes connus pour être utilisées dans toutes les industries. Les recherches menées pour la concrétisation de cette thèse ont donné lieu à douze contributions importantes qui se résument comme suit: Dans la première contribution, on aborde les insuffisances des méthodes en cours de sélection de la stratégie de maintenance et on développe un cadre fondé sur les risques en utilisant des méthodes dites du processus de hiérarchie analytique (Analytical Hierarchy Process (AHP), de cartes cognitives floues (Fuzzy Cognitive Maps (FCM)), et la théorie des ensembles flous (Fuzzy Soft Sets (FSS)) pour sélectionner la meilleure politique de maintenance tout en considérant les incertitudes. La deuxième contribution aborde les insuffisances de la méthode de l'analyse des modes de défaillance, de leurs effets et de leur criticité (AMDEC) et son amélioration en utilisant un modèle AMDEC basée sur les FCM. Les contributions 3 et 4, proposent deux outils de modélisation dynamique des risques et d'évaluation à l'aide de la FCM pour faire face aux risques de l'externalisation de la maintenance et des réseaux de collaboration. Ensuite, on étend les outils développés et nous proposons un outil d'aide à la décision avancée pour prédire l'impact de chaque risque sur les autres risques ou sur la performance du système en utilisant la FCM (contribution 5).Dans la sixième contribution, on aborde les risques associés à la maintenance dans le cadre des ERP (Enterprise Resource Planning (ERP)) et on propose une autre approche intégrée basée sur la méthode AMDEC floue pour la priorisation des risques. Dans les contributions 7, 8, 9 et 10, on effectue une revue de la littérature concernant la maintenance basée sur les risques des dispositifs médicaux, puisque ces appareils sont devenus très complexes et sophistiqués et l'application de modèles de maintenance et d'optimisation pour eux est assez nouvelle. Ensuite, on développe trois cadres intégrés pour la planification de la maintenance et le remplacement de dispositifs médicaux axée sur les risques. Outre les contributions ci-dessus, et comme étude de cas, nous avons réalisé un projet intitulé “Mise à jour de guide de pratique clinique (GPC) qui est un cadre axé sur les priorités pour la mise à jour des guides de pratique cliniques existantes” au centre interdisciplinaire de recherche en réadaptation et intégration sociale du Québec (CIRRIS). Nos travaux au sein du CIRRIS ont amené à deux importantes contributions. Dans ces deux contributions (11e et 12e) nous avons effectué un examen systématique de la littérature pour identifier les critères potentiels de mise à jour des GPCs. Nous avons validé et pondéré les critères identifiés par un sondage international. Puis, sur la base des résultats de la onzième contribution, nous avons développé un cadre global axé sur les priorités pour les GPCs. Ceci est la première fois qu'une telle méthode quantitative a été proposée dans la littérature des guides de pratiques cliniques. L'évaluation et la priorisation des GPCs existants sur la base des critères validés peuvent favoriser l'acheminement des ressources limitées dans la mise à jour de GPCs qui sont les plus sensibles au changement, améliorant ainsi la qualité et la fiabilité des décisions de santé.Today, most systems in various critical sectors such as aviation, oil and health care have become very complex and dynamic, and consequently can at any time stop working. To prevent this from reoccurring and getting out of control which incur huge losses in terms of costs and downtime; the adoption of control and maintenance strategies are more than necessary and even vital. In process engineering, optimal maintenance strategies for these systems could have a significant impact on reducing costs and downtime, maximizing reliability and productivity, improving the quality and finally achieving the desired objectives of the companies. In addition, the risks and uncertainties associated with these systems are often composed of several extremely complex cause and effect relationships. This could lead to an increase in the number of failures of such systems. Therefore, an advanced failure analysis tool is needed to consider the complex interactions of components’ failures in the different phases of the product life cycle to ensure high levels of safety and reliability. In this thesis, we address the shortcomings of current failure/risk analysis and maintenance policy selection methods in the literature. Then, we develop comprehensive approaches to maintenance and failure analysis process based on the risks of complex systems and equipment which are applicable in all industries. The research conducted for the realization of this thesis has resulted in twelve important contributions, as follows: In the first contribution, we address the shortcomings of the current methods in selecting the optimum maintenance strategy and develop an integrated risk-based framework using Analytical Hierarchy Process (AHP), fuzzy Cognitive Maps (FCM), and fuzzy Soft set (FSS) tools to select the best maintenance policy by considering the uncertainties.The second contribution aims to address the shortcomings of traditional failure mode and effect analysis (FMEA) method and enhance it using a FCM-based FMEA model. Contributions 3 and 4, present two dynamic risk modeling and assessment tools using FCM for dealing with risks of outsourcing maintenance and collaborative networks. Then, we extend the developed tools and propose an advanced decision support tool for predicting the impact of each risk on the other risks or on the performance of system using FCM (contribution 5). In the sixth contribution, we address the associated risks in Enterprise Resource Planning (ERP) maintenance and we propose another integrated approach using fuzzy FMEA method for prioritizing the risks. In the contributions 7, 8, 9, and 10, we perform a literature review regarding the risk-based maintenance of medical devices, since these devices have become very complex and sophisticated and the application of maintenance and optimization models to them is fairly new. Then, we develop three integrated frameworks for risk-based maintenance and replacement planning of medical devices. In addition to above contributions, as a case study, we performed a project titled “Updating Clinical Practice Guidelines; a priority-based framework for updating existing guidelines” in CIRRIS which led to the two important contributions. In these two contributions (11th and 12th) we first performed a systematic literature review to identify potential criteria in updating CPGs. We validated and weighted the identified criteria through an international survey. Then, based on the results of the eleventh contribution, we developed a comprehensive priority-based framework for updating CPGs based on the approaches that we had already developed and applied success fully in other industries. This is the first time that such a quantitative method has been proposed in the literature of guidelines. Evaluation and prioritization of existing CPGs based on the validated criteria can promote channelling limited resources into updating CPGs that are most sensitive to change, thus improving the quality and reliability of healthcare decisions made based on current CPGs. Keywords: Risk-based maintenance, Maintenance strategy selection, FMEA, FCM, Medical devices, Clinical practice guidelines

    Exploring Software Development Change Analysis with an Emphasis on Requirements

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    Most software requirements are not definitive of the development process. Rapid changes in user expectations, market conditions, and company practises all need regular updates to software. Requirement change management is a crucial and difficult component of every software development project. Project failure or cancellation often occurs because of requirements changes. Requirements Change refers to requirements that are added, removed, or amended during the system development life cycle. Requirements Change requires additional work in the design phase, which boosts the cost of developing the system, lengthens the time required, and reduces system quality. The paper investigates research efforts in the topic of requirement change and helps in determining the study's purpose. Various Requirement Change Management concepts and approaches are provided, and numerous activities are conducted to mitigate the effects of requirement changes. The study emphasizes on causes, attributes, prioritization of changed requirement, framework for RCM and Change Impact Analysis. This study briefly describes all the possible fact and figure about requirement change.  The study includes various phases of requirement change management such as Requirement Elicitation, Requirement Change Identification in Requirement Document using Two Phase Requirement Document Comparison Algorithm, Prioritization of Changed Requirement using Fuzzy approach, Interdependency analysis and change impact analysis on various software project parameters such as time, cost and human resources

    A Framework for Prioritizing Opportunities of Improvement in the Context of Business Excellence Model in Healthcare Organization

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    In today\u27s world, the healthcare sector is facing challenges to improve the efficiency and effectiveness of its operations. More and more improvement projects are being adopted to enhance healthcare services, making it more patient-centric, and enabling better cost control. Healthcare organizations strive to identify and carry out such improvement initiatives to sustain their businesses and gain competitive advantage. Seeking to reach a higher operational level of excellence, healthcare organizations utilize business excellence criteria to conduct assessment and identify organizational strengths and weaknesses. However, while such assessments routinely identify numerous areas for potential improvement, it is not feasible to conduct all improvement projects simultaneously due to limitations in time, capital, and personnel, as well as conflict with other organization\u27s projects or strategic objectives. An effective prioritization and selection approach is valuable in that it can assist the organization to optimize its available resources and outcomes. This study attempts to enable such an approach by developing a framework to prioritize improvement opportunities in healthcare in the context of the business excellence model through the integration of the Fuzzy Delphi Method and Fuzzy Interface System. To carry out the evaluation process, the framework consists of two phases. The first phase utilizes Fuzzy Delphi Method to identify the most significant factors that should be considered in healthcare for electing the improvement projects. The FDM is employed to handle the subjectivity of human assessment. The research identifies potential factors for evaluating projects, then utilizes FDM to capture expertise knowledge. The first round in FDM is intended to validate the identified list of factors from experts; which includes collecting additional factors from experts that the literature might have overlooked. When an acceptable level of consensus has been reached, a second round is conducted to obtain experts\u27 and other related stakeholders\u27 opinions on the appropriate weight of each factor\u27s importance. Finally, FDM analyses eliminate or retain the criteria to produce a final list of critical factors to select improvement projects. The second phase in the framework attempts to prioritize improvement initiatives using the Hierarchical Fuzzy Interface System. The Fuzzy Interface System combines the experts\u27 ratings for each improvement opportunity with respect to the factors deemed critical to compute the priority index. In the process of calculating the priority index, the framework allows the estimation of other intermediate indices including: social, financial impact, strategical, operational feasibility, and managerial indices. These indices bring an insight into the improvement opportunities with respect to each framework\u27s dimensions. The framework allows for a reduction of the bias in the assessment by developing a knowledge based on the perspectives of multiple experts

    A Risk- and Fuzzy Set-Based Methodology for Advanced Concept Technology Demonstration Military Utility Assessment Design

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    The U.S. Department of Defense Advanced Concept Technology Demonstration (ACTD) and derivative, rapid acquisition programs offer timely solutions to critical military needs by assessing the utility of technologies mature enough to be fielded without application of traditional, defense system development processes. Military utility assessments (MUA) are ACTDs\u27 most critical features, but the lack of a standard for identifying assessment criteria tailored to specific demonstrations risks poorly informed acquisition decisions and the military operations those decisions are intended to support. The purpose of this research was to develop and deploy a methodology for identifying measures of effectiveness integral to advanced concept technology demonstration military utility assessment design. Within a context determined by attributes of complex systems, the research observed twin premises that ACTD assessment designs should accommodate: all risks possible when incorporating demonstration prototypes within superior and complex, joint military operations metasystems; and the ambiguities and other of what have been termed “fuzzy” manifestations of the cognition and language with which end-user, military operators craft and express perspectives required to identify measures of effectiveness fundamental to MUA designs. The effort pursued three research questions: (1) How might joint military operations metasystem models guide the identification of ACTD measures of effectiveness? (2) How might be developed and employed joint military metasystem models with which can be identified ACTD measures of effectiveness? (3) How useful might ACTD managers and analysts find the MUA design methodology developed and deployed with this research? The deployed methodology stimulated answers to these research questions by uniquely combining tailored versions of established risk assessment methods with a fuzzy method for resolving small group preferences. The risk assessment methods honored one research premise while enabling the identification and employment of a joint military operations metasystem model suited to MUA design needs of a simulated ACTD. The fuzzy preference method honored the second research premise as it, too, promoted metasystem model employment. The complete methodology was shown to hold favor with a large segment of a community expert in managing and assessing the utility of ACTDs emphasizing critical, joint military service needs

    A review paper: optimal test cases for regression testing using artificial intelligent techniques

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    The goal of the testing process is to find errors and defects in the software being developed so that they can be fixed and corrected before they are delivered to the customer. Regression testing is an essential quality testing technique during the maintenance phase of the program as it is performed to ensure the integrity of the program after modifications have been made. With the development of the software, the test suite becomes too large to be fully implemented within the given test cost in terms of budget and time. Therefore, the cost of regression testing using different techniques should be reduced, here we dealt many methods such as retest all technique, regression test selection technique (RTS) and test case prioritization technique (TCP). The efficiency of these techniques is evaluated through the use of many metrics such as average percentage of fault detected (APFD), average percentage block coverage (APBC) and average percentage decision coverage (APDC). In this paper we dealt with these different techniques used in test case selection and test case prioritization and the metrics used to evaluate their efficiency by using different techniques of artificial intelligent and describe the best of all

    Control priorization model for improving information security risk assessment

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    Evaluating particular assets for information security risk assessment should take into consideration the availability of adequate resources and return on investments (ROI). Despite the need for a good risk assessment framework, many of the existing frameworks lack of granularity guidelines and mostly depend on qualitative methods. Hence, they require additional time and cost to test all the information security controls. Further, the reliance on human inputs and feedback will increase subjective judgment in organizations. The main goal of this research is to design an efficient Information Security Control Prioritization (ISCP) model in improving the risk assessment process. Case studies based on penetration tests and vulnerability assessments were performed to gather data. Then, Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) was used to prioritize them. A combination of sensitivity analysis and expert interviews were used to test and validate the model. Subsequently, the performance of the model was evaluated by the risk assessment experts. The results demonstrate that ISCP model improved the quality of information security control assessment in the organization. The model plays a significant role in prioritizing the critical security technical controls during the risk assessment process. Furthermore, the model’s output supports ROI by identifying the appropriate controls to mitigate risks to an acceptable level in the organizations. The major contribution of this research is the development of a model which minimizes the uncertainty, cost and time of the information security control assessment. Thus, the clear practical guidelines will help organizations to prioritize important controls reliably and more efficiently. All these contributions will minimize resource utilization and maximize the organization’s information security
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