160 research outputs found

    Understanding understandability of conceptual models - what are we actually talking about? - Supplement

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    Investigating and improving the quality of conceptual models has gained tremendous importance in recent years. In general, model understandability is regarded one of the most important model quality goals and criteria. A considerable amount of empirical studies, especially experiments, have been conducted in order to investigate factors in-fluencing the understandability of conceptual models. However, a thorough review and reconstruction of 42 experiments on conceptual model understandability shows that there is a variety of different understandings and conceptualizations of the term model understandability. As a consequence, this term remains ambiguous, research results on model understandability are hardly comparable and partly imprecise, which shows the necessity of clarification what the conceptual modeling community is actually talking about when the term model understandability is used. This contribution represents a supplement to the article „ Understanding understandability of conceptual models – What are we actually talking about?” published in the Proceedings of the 31st International Conference on Conceptual Modeling (ER 2012) which aimed at overcoming the above mentioned shortcoming by investigating and further clarifying the concept of model understandability. This supplement contains a complete overview of Table 1 (p. 69 in the original contribution) which could only be partly presented in the conference proceedings due to space limitations. Furthermore, an erratum concerning the overview in Table 2 (p. 71 in the original contribution) is presented

    Understanding understandability of conceptual models - what are we actually talking about? - Supplement

    Get PDF
    Investigating and improving the quality of conceptual models has gained tremendous importance in recent years. In general, model understandability is regarded one of the most important model quality goals and criteria. A considerable amount of empirical studies, especially experiments, have been conducted in order to investigate factors in-fluencing the understandability of conceptual models. However, a thorough review and reconstruction of 42 experiments on conceptual model understandability shows that there is a variety of different understandings and conceptualizations of the term model understandability. As a consequence, this term remains ambiguous, research results on model understandability are hardly comparable and partly imprecise, which shows the necessity of clarification what the conceptual modeling community is actually talking about when the term model understandability is used. This contribution represents a supplement to the article „ Understanding understandability of conceptual models – What are we actually talking about?” published in the Proceedings of the 31st International Conference on Conceptual Modeling (ER 2012) which aimed at overcoming the above mentioned shortcoming by investigating and further clarifying the concept of model understandability. This supplement contains a complete overview of Table 1 (p. 69 in the original contribution) which could only be partly presented in the conference proceedings due to space limitations. Furthermore, an erratum concerning the overview in Table 2 (p. 71 in the original contribution) is presented

    A family of experiments to validate measures for UML activity diagrams of ETL processes in data warehouses

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    In data warehousing, Extract, Transform, and Load (ETL) processes are in charge of extracting the data from the data sources that will be contained in the data warehouse. Their design and maintenance is thus a cornerstone in any data warehouse development project. Due to their relevance, the quality of these processes should be formally assessed early in the development in order to avoid populating the data warehouse with incorrect data. To this end, this paper presents a set of measures with which to evaluate the structural complexity of ETL process models at the conceptual level. This study is, moreover, accompanied by the application of formal frameworks and a family of experiments whose aim is to theoretical and empirically validate the proposed measures, respectively. Our experiments show that the use of these measures can aid designers to predict the effort associated with the maintenance tasks of ETL processes and to make ETL process models more usable. Our work is based on Unified Modeling Language (UML) activity diagrams for modeling ETL processes, and on the Framework for the Modeling and Evaluation of Software Processes (FMESP) framework for the definition and validation of the measures.In data warehousing, Extract, Transform, and Load (ETL) processes are in charge of extracting the data from the data sources that will be contained in the data warehouse. Their design and maintenance is thus a cornerstone in any data warehouse development project. Due to their relevance, the quality of these processes should be formally assessed early in the development in order to avoid populating the data warehouse with incorrect data. To this end, this paper presents a set of measures with which to evaluate the structural complexity of ETL process models at the conceptual level. This study is, moreover, accompanied by the application of formal frameworks and a family of experiments whose aim is to theoretical and empirically validate the proposed measures, respectively. Our experiments show that the use of these measures can aid designers to predict the effort associated with the maintenance tasks of ETL processes and to make ETL process models more usable. Our work is based on Unified Modeling Language (UML) activity diagrams for modeling ETL processes, and on the Framework for the Modeling and Evaluation of Software Processes (FMESP) framework for the definition and validation of the measures

    Quality metrics for ASOME data models

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    The relation between BPM culture, BPM methods, and process performance: Evidence from quantitative field studies

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    Business process management (BPM) research conceptualizes BPM culture as a type of organizational culture that supports BPM. No quantitative fieldwork has so far examined how such a supporting role manifests itself. We study the relationship between BPM culture, BPM methods, and process performance empirically. Our analysis of multiple survey data sets from a total of 581 practitioners of multiple industries suggests that BPM methods indirectly contribute to process performance by establishing a BPM culture. This finding updates the prevalent assumption that the correct application of methods yields direct performance benefits. We discuss several implications for theory and practice

    Approach for testing the extract-transform-load process in data warehouse systems, An

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    2018 Spring.Includes bibliographical references.Enterprises use data warehouses to accumulate data from multiple sources for data analysis and research. Since organizational decisions are often made based on the data stored in a data warehouse, all its components must be rigorously tested. In this thesis, we first present a comprehensive survey of data warehouse testing approaches, and then develop and evaluate an automated testing approach for validating the Extract-Transform-Load (ETL) process, which is a common activity in data warehousing. In the survey we present a classification framework that categorizes the testing and evaluation activities applied to the different components of data warehouses. These approaches include both dynamic analysis as well as static evaluation and manual inspections. The classification framework uses information related to what is tested in terms of the data warehouse component that is validated, and how it is tested in terms of various types of testing and evaluation approaches. We discuss the specific challenges and open problems for each component and propose research directions. The ETL process involves extracting data from source databases, transforming it into a form suitable for research and analysis, and loading it into a data warehouse. ETL processes can use complex one-to-one, many-to-one, and many-to-many transformations involving sources and targets that use different schemas, databases, and technologies. Since faulty implementations in any of the ETL steps can result in incorrect information in the target data warehouse, ETL processes must be thoroughly validated. In this thesis, we propose automated balancing tests that check for discrepancies between the data in the source databases and that in the target warehouse. Balancing tests ensure that the data obtained from the source databases is not lost or incorrectly modified by the ETL process. First, we categorize and define a set of properties to be checked in balancing tests. We identify various types of discrepancies that may exist between the source and the target data, and formalize three categories of properties, namely, completeness, consistency, and syntactic validity that must be checked during testing. Next, we automatically identify source-to-target mappings from ETL transformation rules provided in the specifications. We identify one-to-one, many-to-one, and many-to-many mappings for tables, records, and attributes involved in the ETL transformations. We automatically generate test assertions to verify the properties for balancing tests. We use the source-to-target mappings to automatically generate assertions corresponding to each property. The assertions compare the data in the target data warehouse with the corresponding data in the sources to verify the properties. We evaluate our approach on a health data warehouse that uses data sources with different data models running on different platforms. We demonstrate that our approach can find previously undetected real faults in the ETL implementation. We also provide an automatic mutation testing approach to evaluate the fault finding ability of our balancing tests. Using mutation analysis, we demonstrated that our auto-generated assertions can detect faults in the data inside the target data warehouse when faulty ETL scripts execute on mock source data

    Systematic construction of goal-oriented COTS taxonomies

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    El proceso de construir software a partir del ensamblaje e integración de soluciones de software pre-fabricadas, conocidas como componentes COTS (Comercial-Off-The-Shelf) se ha convertido en una necesidad estratégica en una amplia variedad de áreas de aplicación. En general, los componentes COTS son componentes de software que proveen una funcionalidad específica, que están disponibles en el mercado para ser adquiridos e integrados dentro de otros sistemas de software. Los beneficios potenciales de esta tecnología son principalmente la reducción de costes y el acortamiento del tiempo de desarrollo, a la vez que fomenta la calidad. Sin embargo, numerosos retos que van desde problemas técnicos y legales deben ser afrontados para adaptar las actividades tradicionales de ingeniería de software para explotar los beneficios del uso de COTS para el desarrollo de sistemas.Actualmente, existe un incrementalmente enorme mercado de componentes COTS; así, una de las actividades más críticas en el desarrollo de sistemas basados en COTS es la selección de componentes que deben ser integrados en el sistema a desarrollar. La selección está básicamente compuesta de dos procesos principales: La búsqueda de componentes candidatos en el mercado y su posterior evaluación con respecto a los requisitos del sistema. Desafortunadamente, la mayoría de los métodos existentes para seleccionar COTS, se enfocan en el proceso de evaluación, dejando de lado el problema de buscar los componentes en el mercado. La búsqueda de componentes en el mercado no es una tarea trivial, teniendo que afrontar varias características del mercado de COTS, tales como su naturaleza dispersa y siempre creciente, cambio y evolución constante; en este contexto, la obtención de información de calidad acerca de los componentes no es una tarea fácil. Como consecuencia, el proceso de selección de COTS se ve seriamente dañado. Además, las alternativas tradicionales de reuso también carecen de soluciones apropiadas para reusar componentes COTS y el conocimiento adquirido en cada proceso de selección. Esta carencia de propuestas es un problema muy serio que incrementa los riesgos de los proyectos de selección de COTS, además de hacerlos ineficientes y altamente costosos. Esta disertación presenta el método GOThIC (Goal- Oriented Taxonomy and reuse Infrastructure Construction) enfocado a la construcción de infraestructuras de reuso para facilitar la búsqueda y reuso de componentes COTS. El método está basado en el uso de objetivos para construir taxonomías abstractas, bien fundamentadas y estables para lidiar con las características del mercado de COTS. Los nodos de las taxonomías son caracterizados por objetivos, sus relaciones son declaradas como dependencias y varios artefactos son construidos y gestionados para promover la reusabilidad y lidiar con la evolución constante.El método GOThIC ha sido elaborado a través de un proceso iterativo de investigación-acción para identificar los retos reales relacionados con el proceso de búsqueda de COTS. Posteriormente, las soluciones posibles fueron evaluadas e implementadas en varios casos de estudio en el ámbito industrial y académico en diversos dominios. Los resultados más relevantes fueron registrados y articulados en el método GOThIC. La evaluación industrial preliminar del método se ha llevado a cabo en algunas compañías en Noruega.The process of building software systems by assembling and integrating pre-packaged solutions in the form of Commercial-Off-The-Shelf (COTS) software components has become a strategic need in a wide variety of application areas. In general, COTS components are software components that provide a specific functionality, available in the market to be purchased, interfaced and integrated into other software systems. The potential benefits of this technology are mainly its reduced costs and shorter development time, while maintaining the quality. Nevertheless, many challenges ranging form technical to legal issues must be faced for adapting the traditional software engineering activities in order to exploit these benefits.Nowadays there is an increasingly huge marketplace of COTS components; therefore, one of the most critical activities in COTS-based development is the selection of the components to be integrated into the system under development. Selection is basically composed of two main processes, namely: searching of candidates from the marketplace and their evaluation with respect to the system requirements. Unfortunately, most of the different existing methods for COTS selection focus their efforts on evaluation, letting aside the problem of searching components in the marketplace. Searching candidate COTS is not an easy task, having to cope with some challenging marketplace characteristics related to its widespread, evolvable and growing nature; and the lack of available and well-suited information to obtain a quality-assured search. Indeed, traditional reuse approaches also lack of appropriate solutions to reuse COTS components and the knowledge gained in each selection process. This lack of proposals is a serious drawback that makes the whole selection process highly risky, and often expensive and inefficient. This dissertation introduces the GOThIC (Goal- Oriented Taxonomy and reuse Infrastructure Construction) method aimed at building a domain reuse infrastructure for facilitating COTS components searching and reuse. It is based on goal-oriented approaches for building abstract, well-founded and stable taxonomies capable of dealing with the COTS marketplace characteristics. Thus, the nodes of these taxonomies are characterized by means of goals, their relationships declared as dependencies among them and several artifacts are constructed and managed for reusability and evolution purposes. The GOThIC method has been elaborated following an iterative process based on action research premises to identify the actual challenges related to COTS components searching. Then, possible solutions were envisaged and implemented by several industrial and academic case studies in different domains. Successful results were recorded to articulate the synergic GOThIC method solution, followed by its preliminary industrial evaluation in some Norwegian companies
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