Relational-model based change management for non-functional requirements: Approach and experiment

2011 ◽  
Author(s):  
M. Kassab ◽  
O. Ormandjieva ◽  
M. Daneva
Keyword(s):  
Change Management ◽  
Relational Model ◽  
Functional Requirements ◽  
Model Based

scholarly journals Multidimensional Space Structure for Adaptable Data Model

2019 ◽  
Vol 8 (3) ◽  
pp. 7753-7758
Keyword(s):  
Data Model ◽  
Cartesian Product ◽  
Data Representation ◽  
Space Structure ◽  
Automated System ◽  
Relational Model ◽  
Multidimensional Data ◽  
Multidimensional Space ◽  
Model Based ◽  
Five Axes

The article presents an adaptable data model based on multidimensional space. The main difference between a multidimensional data representation and a table representation used in relational Database Management Systems (DBMSs) is that it is possible to add new elements to sets defining the axes of multidimensional space at any time. This changes the data model. The tabular representation of the relational model does not allow you to change the model itself during the operation of an automated system. Three levels of multidimensional data presentation space are considered. There are axis of multidimensional space, the Cartesian product of the sets of axis values and the values of space points. The five axes of multidimensional space defined in the article (entities, attributes, identifiers, time, modifiers) are basic for the design of an adaptable automated system. It is shown that it is possible to use additional axes for greater granularity of the stored data. The multidimensional space structure defined in the article for an adaptable data model is a flexible set for storing a relational domain model. Two types of operations in multidimensional information space are defined. Relations of the relational model are formed dynamically depending on the conditions imposed on the coordinates of the points. Thus, an adaptable data representation model based on multidimensional space can be used to create flexible dynamic automated information systems.

Build Evidence Chain Relational Model Based on Chinese Judgment Documents

2017 ◽  
pp. 94-107
Author(s):  
Siyuan Kong ◽  
Yemao Zhou ◽  
Jidong Ge ◽  
Zhongjin Li ◽  
Chuanyi Li ◽  
...  
Keyword(s):  
Relational Model ◽  
Model Based

Towards Test-Driven and Architecture Model-Based Security and Resilience Engineering

2013 ◽  
pp. 163-188
Author(s):  
Ayda Saidane ◽  
Nicolas Guelfi
Keyword(s):  
Software Systems ◽  
Critical Systems ◽  
Functional Requirements ◽  
Security Testing ◽  
Modeling Framework ◽  
Architecture Model ◽  
Model Based ◽  
Security Modeling

The quality of software systems depends strongly on their architecture. For this reason, taking into account non-functional requirements at architecture level is crucial for the success of the software development process. Early architecture model validation facilitates the detection and correction of design errors. In this research, the authors are interested in security critical systems, which require a reliable validation process. So far, they are missing security-testing approaches providing an appropriate compromise between software quality and development cost while satisfying certification and audit procedures requirements through automated and documented validation activities. In this chapter, the authors propose a novel test-driven and architecture model-based security engineering approach for resilient systems. It consists of a test-driven security modeling framework and a test based validation approach. The assessment of the security requirement satisfaction is based on the test traces analysis. Throughout this study, the authors illustrate the approach using a client server architecture case study.

Towards Test-Driven and Architecture Model-Based Security and Resilience Engineering

2014 ◽  
pp. 2072-2098
Author(s):  
Ayda Saidane ◽  
Nicolas Guelfi
Keyword(s):  
Software Systems ◽  
Critical Systems ◽  
Functional Requirements ◽  
Security Testing ◽  
Modeling Framework ◽  
Architecture Model ◽  
Model Based ◽  
Security Modeling

The quality of software systems depends strongly on their architecture. For this reason, taking into account non-functional requirements at architecture level is crucial for the success of the software development process. Early architecture model validation facilitates the detection and correction of design errors. In this research, the authors are interested in security critical systems, which require a reliable validation process. So far, they are missing security-testing approaches providing an appropriate compromise between software quality and development cost while satisfying certification and audit procedures requirements through automated and documented validation activities. In this chapter, the authors propose a novel test-driven and architecture model-based security engineering approach for resilient systems. It consists of a test-driven security modeling framework and a test based validation approach. The assessment of the security requirement satisfaction is based on the test traces analysis. Throughout this study, the authors illustrate the approach using a client server architecture case study.

Grey Correlation Model Based on Diatom Indices Evaluating Water Quality of Longjiang River

2013 ◽  
Vol 448-453 ◽  
pp. 43-47 ◽  
Author(s):  
Xin Tang ◽  
De Suo Cai ◽  
Wen Ting Yao
Keyword(s):  
Water Quality ◽  
Water Quality Assessment ◽  
Quality Standard ◽  
Relational Model ◽  
Water Quality Standard ◽  
Diatom Index ◽  
Model Based ◽  
Diatom Indices ◽  
Grey Relational

In order to evaluate the water quality of Longjiang river comprehensively, diatoms of 15 sampling sites are collected to establish the Grey Relational Model based on three diatom indexesIPS, IBD and IDG. From the Cluster analysis of sampling sites and the box plot of diatom index, IBD is the best, then the IPS, the diatom index weights on water quality assessment are 0.637 for IBD, 0.2583 for IPS, 0.1074 for IDG respectively. Finally, by comparing the water quality standard level based on Grey Relational Model, it can be known that the water quality of most sampling sites is fine except that site No.1 and No.3 belong to III water quality standard. The result shows that it is more comprehensive and reasonable to use the Grey Relational Model based on diatom index rather than individual diatom index to assess water quality.

A Model-Based Failure Identification and Propagation Framework for Conceptual Design of Complex Systems

2012 ◽  
Author(s):  
Hoda Mehrpouyan ◽  
David C. Jensen ◽  
Christopher Hoyle ◽  
Irem Y. Tumer ◽  
Tolga Kurtoglu
Keyword(s):  
System Architecture ◽  
Early Identification ◽  
Mitigation Strategies ◽  
Functional Requirements ◽  
Environmental Disturbances ◽  
Safety Issues ◽  
Model Based ◽  
Potential Safety ◽  
Failure Propagation ◽  
Failure Identification

In this paper, a model-based failure identification and propagation (MFIP) framework is introduced for early identification of potential safety issues caused by environmental disturbances and subsystem failures within a complex avionic system. The MFIP framework maps hazards and vulnerability modes to specific components in the system and analyzes failure propagation paths. Block definition diagrams (BDD) are used to represent system functional requirements in the form of demonstrating the relationships between various requirements, their associations, generalizations, as well as dependencies. These concept models help to identify hazardous factors and the relationships through which their detrimental effects are transferred through-out the proposed system architecture. As such, the approach provides the opportunity to reduce costs associated with redesign and provide important information on design viability. Using this technique, designers can examine the impacts of environmental and subsystem risks on the overall system during the early stages of design and develop hazard mitigation strategies.

Web Service QoS Matching Research Based on Ontology

2013 ◽  
Vol 385-386 ◽  
pp. 1679-1683
Author(s):  
Xin Bing Ma ◽  
Xiao Feng Zhou
Keyword(s):  
Web Service ◽  
Functional Requirements ◽  
Service Matching ◽  
Model Based ◽  
Ontology Model ◽  
Qos Parameters

In this article,take into account QoS characteristics comprehensively and build a reliable QoS ontology model. Based on the model,Web service QoS matching will be divided into three stages.Firstly,make a estimation of semantic comparability between QoS parameters of candidate services meeting the functional requirements and the QoS parameters of requirements in QoSIndependent ontology,find candidate services meeting users needs; Then,according to the critical QoS parameters between adjacent services constraints to further refine the matching between the candidate services;Finally choose the maximum service QoS value meeting the user requests in specific areas. So as to improve the efficiency and accuracy of service matching.

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