Testing Web Applications Using Poor Quality Data

Laranjeiro, Nuno; Soydemir, Seyma Nur; Bernardino, Jorge

doi:10.1109/ladc.2016.30

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…The goal of the work, besides providing a broad vision of the state of the art in this domain, was to support the definition of an approach that could use such knowledge to define effective tests for assessing data-centric applications in presence of poor quality data. We presented, in our previous work [16], an initial proposal for assessing the behavior of relational database applications in presence of poor quality data. The approach is based on the bytecode instrumentation of a JDBC driver, which allows us to intercept calls to the database.…”

Section: Background and Related Workmentioning

confidence: 99%

“…In a previous work, we presented a prototype for testing relational database applications in presence of poor quality data [16], which is essentially a tool for injecting poor quality data on relational database interfaces (namely on JDBC interfaces). In this work, we further generalize the approach and extend it to document NoSQL databases (e.g., MongoDB, Apache CouchDB), which are nowadays attracting a lot of attention from the industry and are increasingly being used in real system deployments.…”

Section: Introductionmentioning

confidence: 99%

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Testing data-centric services using poor quality data: from relational to NoSQL document databases

et al. 2017

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Businesses are nowadays deploying their services online, reaching out to clients all around the world. Many times deployed as web applications or web services, these business-critical systems typically perform large amounts of database operations; thus, they are dependent on the quality of the data to provide correct service to clients. Research and practice have shown that the quality of the data in an enterprise system gradually decreases overtime, bringing in diverse reliability issues to the applications that are using the data to provide services. These issues range from simple incorrect operations to aborted operations or severe system failures. In this paper, we present an approach to test data-centric services in presence of poor quality data. The approach has been designed to consider relational and NoSQL database nodes used by the system under test and is based on the injection of poor quality data on the database-application interface. The results indicate the effectiveness of the approach in discovering issues, not only at the application-level, but also in the middleware being used, contributing to the development of more reliable services.

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Section: Background and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Testing data-centric services using poor quality data: from relational to NoSQL document databases

et al. 2017

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“…Content generated by users is said to contain unverified, misleading, or erroneous information that diminishes the credibility and lowers the quality of data [16][17][18]. Because of this, low data quality is one of the significant concerns in UGC [19] that can lead to poor decisions [20,21], or in rare cases, generate errors that eventually crash the underlying platforms [22].…”

Section: Introductionmentioning

confidence: 99%

Quality Characteristics for User-Generated Content

Musto

Dahanayake

2022

Frontiers in Artificial Intelligence and Applications

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Today, vast amounts of data are collected from the internet, and the general public generates most data using social networks. There is a need to have a comprehensive approach to characterize the quality of such user-generated data collection from the internet. The data quality characteristics accepted among database and computer science communities have definitions that are not domain-specific. Therefore, there is no clear understanding of the data quality characteristics specific to user-generated content. This research examines different user-generated content platforms against the general data quality characteristics to determine which quality characteristics are essential for user-generated content. The research contributes to a list of definitions of those data quality characteristics specific to user-generated content. These definitions help identify quality characteristics useful for user-generated content platforms and their implementations. The quality of the content of Atlas of Living Australia, Twitter, YouTube, Wikipedia, and WalkingPaths is evaluated to assess the essence of the quality characteristics defined in this research.

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Testing Web Applications Using Poor Quality Data

Cited by 2 publications

References 17 publications

Testing data-centric services using poor quality data: from relational to NoSQL document databases

Testing data-centric services using poor quality data: from relational to NoSQL document databases

Quality Characteristics for User-Generated Content

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