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Data and information obtained from data analysis is an essential asset to construct and support information systems. As data is a significant resource, the quality of data is critical to enhance data quality and increase the effectiveness of business processes. Relationships among all four major data quality dimensions for process improvement are often neglected. For this reason, this study proposes to construct a reliable framework to support process activities in information systems. This study focuses on four critical quality dimensions; accuracy, completeness, consistency, and timeliness. A qualitative approach was conducted using a questionnaire and the responses were assessed to measure reliability and validity of the survey. Factor analysis and Cronbach-alpha test were applied to interpret the results. The results show that the items of each data quality dimension and improvement process are reliable and valid. This framework can be used to evaluate data quality in an information system to improve the involved process.

Keywords

Data Quality Dimension, Framework, Relationship, Validation, Information Systems, Factor Analyzing

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Feasibility Study of Aspect Mining at Requirement Level

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Authors

Hema Subramaniam ¹, Hazura Zulzalil ², Marzanah A. Jabar ², Saadah Hassan ²

Affiliations
1 Faculty of Computer Science and Information Technology, Universiti Selangor (UNISEL), MY
2 Computer Science and Information Technology, Universiti Putra Malaysia (UPM), MY

Source

Indian Journal of Science and Technology, Vol 7, No 5 (2014), Pagination: 559-565

Abstract

Modularity is categorized as quality characteristic which can increase the maintainability of a software program. Although modularity is gaining popularity, yet it is hard to be realized since there are many crosscutting concerns scattered and tangled in object oriented programs. Thus, more efforts are needed to maintain the software program which uses object oriented approach. On the other hand, aspect oriented approach has been viewed as it can encourage modularization. Since majority of the existing application is using object oriented approach, restructuring process known as refactoring become essential in increasing the program modularity. Refactoring means the process of restructuring the internal section without changing the system behaviour. Even though refactoring becomes the solution for this yet it does not seem to increase the modularity of a software program. This is due to lack of a comprehensive aspect mining method which helps in extracting the crosscutting concern from the existing applications before the refactoring takes place. At the present time, software practitioner preferred to conduct aspect mining at coding level which resulted in incomplete crosscutting concern extraction. Since the requirement stage being the initial stage before coding, it is believed to have the ability to extract more crosscutting concerns. Thus, it creates a space for aspect mining at requirement level as an alternative to aspect mining at coding level. In that case, the feasibility of aspect mining at requirement level becomes a need. This study aims to demonstrate the opportunity of conducting aspect mining at requirement level. Interview conducted among the Certified Professional Requirement Engineers (CPRE) has revealed that aspect mining at the requirement level is feasible and needed. The result of this study represented in SWOT analysis matrix is useful in justifying the alternative method of aspect mining. This alternative analysis also highlighted on the frequency of crosscutting concern that used among the CPRE indicating the worthiness of aspect mining at the requirement level.

Keywords

Aspect Mining, Feasibility Study, Refactoring

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