Empirical Validation of Metrics for Conceptual Models of Data Warehouses

Serrano, Manuel; Calero, Coral; Trujillo, Juan; Luján-Mora, Sergio; Piattini, Mario

doi:10.1007/978-3-540-25975-6_36

Cited by 36 publications

(19 citation statements)

References 18 publications

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“…Let us summarize the two previous studies developed with the metrics [55,56] and then we will deeply present the last experiment we have carried out. In all the cases our goal is the same: trying to select which of the proposed metrics are correlated with data warehouse conceptual schema understandability.…”

Section: Empirical Validationmentioning

confidence: 99%

“…The first experiment [55] was performed by 17 professionals working in a Spanish software consultancy that specialized in information systems development. The subjects were thirteen men and three women (one of the subjects did not give us this information), with an average age of 27.59 years.…”

Section: Previous Experimental Workmentioning

confidence: 99%

“…This process includes, among other steps, theoretical and empirical validation of the metrics to assure the utility of the proposed metrics [17,37]. Following this consideration, we have previously defined a set of metrics for the conceptual modelling of data warehouses [55]. The proposed metrics have been defined for measuring the understandability of data warehouse conceptual models, focusing on the complexity of the models.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, we are getting involved in the empirical validation of these metrics. In [55,56], we presented the first experiments we accomplished for the empirical validation of our proposed metrics. Nevertheless, it is widely accepted that only after performing a family of experiments, it is possible to build up the cumulative knowledge to extract useful measurement conclusions to be applied in practice [4].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Metrics for data warehouse conceptual models understandability

Serrano

Trujillo

Calero

et al. 2007

Information and Software Technology

Self Cite

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Section: Empirical Validationmentioning

confidence: 99%

Section: Previous Experimental Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Metrics for data warehouse conceptual models understandability

Serrano

Trujillo

Calero

et al. 2007

Information and Software Technology

Self Cite

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“…Hence, the metrics failed to prove their practical utility. Serrano et al [14] proposed measures for object oriented models of DW on the basis of design elements such as dimension classes, fact classes, dimension hierarchies, etc. They proposed metrics at different levels -diagram, star and class.…”

Section: Related Workmentioning

confidence: 99%

Formal Validation of Data Warehouse Complexity Metrics using Distance Framework

Aggarwal¹,

Sabharwal²

2017

IJISA

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Abstract-DataWarehouse is the cornerstone for organizations that base their strategic decisions on the large scale processing of numerical data. The success of the organization depends on these decisions and hence it becomes extremely important to have a quality data warehouse. Conceptual models have been widely recognized as a key determinant of data warehouse quality during the early stages of design. Recently, metrics have been proposed by authors based on hierarchies to quantify the complexity and inturn quality of the conceptual models of data warehouse. They have formally corroborated the measures against Briand's property based framework to ensure their validity. However, Briand's set of properties for software measures are a set of necessary but not sufficient measure axioms. They are advantageous to refute software metrics but not to validate them. Thus, we focus on the theoretical validation of the data warehouse conceptual model metrics using the Distance framework whose sufficiency is ensured by the measurement theory. The results indicate that the metrics are valid measures of the complexity of data warehouse conceptual models. Besides, validation by Distance framework assures that the metrics are in the ratio scale which further aids in data analysis.

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Applying a framework for the improvement of software process maturity

et al. 2005

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This article presents the results and lessons learned in the application of the Framework for the Modelling and Measurement of Software Processes (FMESP) in a software company dedicated to the development and maintenance of software for information systems. The aim of FMESP is to provide companies with a conceptual and technological framework for the management of their process models and measurement models in an integrated way. Modelling and measurement are two key factors to promote continuous process improvement. As a result, important benefits were obtained. The company improved the maturity of its processes which allowed it to obtain the ISO 9000 certification. From a research point of view, are Capability Maturity Model for Software (SW-CMM) [1], Capability Maturity Model Integration (CMMI) [2] and Software Process Improvement and Capability Determination (SPICE), which has been standardized as ISO 15504 [3].Nowadays, it is common for customers to demand companies to be certified according to quality standards such as ISO 9000: 2000 [4] or that they have high maturity levels in their processes in accordance with assessment models such as CMMI or ISO 15504. For this reason, software organizations are increasingly focusing on the management of their processes.Management of software processes requires that four key responsibilities be assumed [5]: definition, measurement, control and improvement of processes. It is very important to consider the integrated management of two key aspects.• Process modelling. Process models constitute the starting point for analysing, enacting and improving processes. Bearing in mind that there is a huge diversity among existing process modelling proposals, a reference process metamodel should be helpful. The Object Management Group has recently proposed the Software Process Engineering Metamodel Specification (SPEM) metamodel [6], which defines a reference language for process modelling. • Process evaluation. The first step in software processes improvement is its evaluation. Due to the vast diversity of elements which could be measured in the context of software process evaluation (process models, projects and products), the establishment of an homogeneous terminology for the definition, calculation and exploitation of metrics is needed for the integrated and effective management of the measurement process.In this paper we present the results and lessons learned from the application of the Framework for the Modelling and Evaluation of Software Processes (FMESP) in a software company. The FMESP framework includes the conceptual and technological elements which are needed to facilitate the management of the definition and evaluation of software processes.The rest of the paper proceeds as follows. We first describe the characteristics of the framework FMESP. Then we present a general overview of the software company in which FMESP was applied. This is followed by a detailed description of the application of FMESP in the software company. Next we highlight the benefits for the com...

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Empirical Validation of Metrics for Conceptual Models of Data Warehouses

Cited by 36 publications

References 18 publications

Metrics for data warehouse conceptual models understandability

Metrics for data warehouse conceptual models understandability

Formal Validation of Data Warehouse Complexity Metrics using Distance Framework

Applying a framework for the improvement of software process maturity

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