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ردیف | عنوان | نوع |
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1 |
Using Orthogonal Defect Classification to characterize NoSQL database defects
استفاده از طبقه بندی نقص متعامد برای توصیف نقص پایگاه داده NoSQL-2020 NoSQL databases are increasingly used for storing and managing data in business-critical Big Data sys- tems. The presence of software defects (i.e., bugs) in these databases can bring in severe consequences to the NoSQL services being offered, such as data loss or service unavailability. Thus, it is essential to understand the types of defects that frequently affect these databases, allowing developers take action in an informed manner (e.g., redirect testing efforts). In this paper, we use Orthogonal Defect Classification (ODC) to classify a total of 4096 software defects from three of the most popular NoSQL databases: Mon- goDB, Cassandra, and HBase. The results show great similarity for the defects across the three different NoSQL systems and, at the same time, show the differences and heterogeneity regarding research carried out in other domains and types of applications, emphasizing the need for possessing such information. Our results expose the defect distributions in NoSQL databases, provide a foundation for selecting repre- sentative defects for NoSQL systems, and, overall, can be useful for developers for verifying and building more reliable NoSQL database systems. Keywords: Defect analysis | NoSQL | Orthogonal Defect Classification | Software defect | Software fault |
مقاله انگلیسی |
2 |
Uniform data access platform for SQL and NoSQL database systems
پلت فرم دسترسی یکسان داده برای سیستم های پایگاه داده SQL و NoSQL-2017 Integration of data stored in heterogeneous database systems is a very challenging task and it may hide
several difficulties. As NoSQL databases are growing in popularity, integration of different NoSQL systems
and interoperability of NoSQL systems with SQL databases become an increasingly important issue. In
this paper, we propose a novel data integration methodology to query data individually from different
relational and NoSQL database systems. The suggested solution does not support joins and aggregates
across data sources; it only collects data from different separated database management systems accord
ing to the filtering options and migrates them. The proposed method is based on a metamodel approach
and it covers the structural, semantic and syntactic heterogeneities of source systems. To introduce the
applicability of the proposed methodology, we developed a web-based application, which convincingly
confirms the usefulness of the novel method.
Keywords: Uniform data access | Relational database management systems | NoSQL database management systems | MongoDB | Data integration | JSON |
مقاله انگلیسی |
3 |
Big Data Analytics Architecture for Agro Advisory System
معماری تحلیل داده های بزرگ برای سیستم مشاوره کشاورزی-2016 Modern trends in the agriculture domain have
made people realize the importance of big data. The key
challenge of big data in agriculture is to identify the
effectiveness of big data analytics. Moreover, how big data
analytics can be used to improve the productivity in
agricultural practices. The purpose of the proposed research
is to reduce the technological gap between rural communities
and information through recommendations and decision
support system. The main contribution of this paper is to
propose an open source, cost-effective and scalable big data
analytics architecture for an Agro advisory system. As a part
of implementation, an analytic framework for big data
application development is built and implemented. Also, a
prototype application for crop yield prediction is implemented
for cotton crop in Ahmedabad district, Gujarat, India.
Keywords: Big Data | Big Data Analytics | NoSQL Database | Multiple Linear Regression. |
مقاله انگلیسی |