DESMET: a methodology for evaluating software engineering methods and tools

Kitchenham, Barbara; Linkman, Stephen; Law, D.

doi:10.1049/cce:19970304

Cited by 171 publications

(161 citation statements)

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“…We have evaluated the methodologies reviewed in the previous section through applying the feature analysis approach [17], which is widely used for evaluating software development methodologies. As this approach is based on qualitative evaluation, the development of a set of Qualitative Criteria (QC) has been an important objective of our research.…”

Section: Qualitative Criteria For Evaluation Of Model-driven Adaptivementioning

confidence: 99%

Methodologies for Model-Driven Development of Adaptive Web Applications: An Analytical Survey

Fadavi

Ramsin²

2016

JSW

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Due to the rapid expansion of web applications, the information and services provided on the web have proliferated, leading to ever-increasing complexity. This has not only resulted in the utmost significance of information quality and accuracy on the web, but has also necessitated that access to information be improved. Hence, adaptive web systems have emerged, which focus on adapting web content, presentation, and navigation to meet the needs of the users according to their individual circumstances and preferences. In this field, focus has gradually shifted from creation of new adaptive techniques to solving the problems of analysis and design of adaptive applications; in other words, it has become important to handle the dynamism of the runtime environment and the complexity involved in developing these applications. Model-Driven Engineering (MDE) is considered a promising approach for overcoming these problems, mainly due to its modeling features: Models are created at different levels of abstraction (thus enhancing complexity management), and the process can potentially be automated through the use of transformation rules. We provide a review of several prominent methodologies that utilize MDE for developing adaptive web applications, and propose a criteria-based evaluation approach that highlights their strengths and weaknesses. Evaluation results can be used for comparing and selecting methodologies for use in web development projects; they can also be used for constructing a new methodology that exploits the strengths and addresses the shortcomings of existing methodologies.

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Section: Qualitative Criteria For Evaluation Of Model-driven Adaptivementioning

confidence: 99%

Methodologies for Model-Driven Development of Adaptive Web Applications: An Analytical Survey

Fadavi

Ramsin²

2016

JSW

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“…in these experiments. Data from the usage of the architecture are collected combining qualitative and quantitative techniques [Kit96a], and analyzed using the mixed method proposed in [Mar03].…”

Section: Objectives and Contributionsmentioning

confidence: 99%

“…with other loosely-coupled integration approaches. This comparison includes a feature analysis [Kit96a], and an analysis of the development e ort This evaluation has partially been published in [Ala12a], showing the results and conclusions of the four authentic experiments, as well as the comparison of the development e ort in loosely-coupled integration approaches. Besides, an extended evaluation focused on two of the experiments can be found in [Ala12b].…”

Section: Objectives and Contributionsmentioning

confidence: 99%

GLUE!: An architecture for the integration of external tools in Virtual Learning Environments

Alario-Hoyos

Bote‐Lorenzo

Sánchez

et al. 2013

Computers & Education

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A mis padres. AcknowledgementsThe opening lines of this document serve to close this dissertation. In them, I want to sincerely thank all those who have made this work possible, and without whom this dissertation could not have been accomplished. First, I would like to thank my supervisors Miguel and Eduardo, with whom I share the credit of this work, and who have supported me throughout all these years in which we have worked together very closely. They believed in me from the very rst moment I ran into them, and they spent much time and e ort to make this dissertation succeed.Yannis is also one of the great minds that has most in uenced me over these years, and so I owe him much of this work. He insisted in showing me the right way, and he never hesitated to give me on-the-y advice or answers to my questions, despite his busy schedule. Of course, I have to specially thank Asen, Guillermo and Adolfo, who have very closely followed my dissertation, and with whom I had deep and intense discussions.Regarding the development tasks, I have been very lucky to be supported by David and Javier; without their work, this dissertation would have needed much more time, and the de- This fellowship gave me economic stability for almost three years and allowed me to make several short research stays abroad.Despite this ideal working environment, I could never have nished this dissertation without the support of my family and friends. Among them, special words of thanks are to Martín, iii Eduardo, Natalia, Miguel Ángel, Dani, Quini and many others who stood by my side to a greater or lesser extend throughout these years. Here, I would also like to remember all my college friends which led me to the front door of this PhD after a ve-year degree in which we all shared great times and memories.My parents, Julián and Tere, deserve my best words. They raised me in the values of sacri ce and knowledge. They always backed me up in every choice, and helped me overcome the di culties, and what is more important, they still keep doing it day by day. They are the ones that encourage me to get the best out of myself.Finally, my last words of gratitude must be for Bea, because she su ered this dissertation as I did. She was always by my side and never gave up on me. She gave me the strength to face this challenge, being even able to follow me to the end of the world. This dissertation proposes a middleware integration architecture called GLUE! (Group Learning Uniform Environment) that enables the lightweight integration of multiple existing external tools in multiple existing VLEs, overcoming these limitations. GLUE! fosters this integration by imposing few restrictions on VLE and tool providers, as well as by expecting an attainable e ort from developers. Besides, GLUE! facilitates the instantiation and enactment of collaborative learning situations within VLEs, leveraging the VLEs distinctive features for the management of users and groups. By means of GLUE!, practitioners may use external tools as if they were VLE built-in tools, and w...

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“…• Insertion Impact Analysis Method -Foco em mudanças no processo de desenvolvimento de software e as principais variáveis que afetam o desempenho da ferramenta (BRUCKHAUS, 1995(BRUCKHAUS, , 1997 • DESMET -Lista tipos de estudos relacionados ao estudo de impactos de ferramentas, e mostra boas práticas necessárias para a execução desses estudos (KITCHENHAM et al, 1996(KITCHENHAM et al, , 1997; …”

Section: Modelos E Métodos Relacionados Com a Avaliação De Impactos Dunclassified

“…DESMET (KITCHENHAM et al, 1996(KITCHENHAM et al, , 1997) é método para a avaliação de processos de desenvolvimento ou ferramentas dentro de uma particular organização. Ela lista diversas técnicas utilizadas para a avaliação de ferramentas e as principais condições necessárias para que a avaliação seja feita da melhor maneira possível..…”

Section: Desmetunclassified

Modelo de identificação e análise de impactos da implantação de ferramentas case.

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DESMET: a methodology for evaluating software engineering methods and tools

Cited by 171 publications

References 13 publications

Methodologies for Model-Driven Development of Adaptive Web Applications: An Analytical Survey

Methodologies for Model-Driven Development of Adaptive Web Applications: An Analytical Survey

GLUE!: An architecture for the integration of external tools in Virtual Learning Environments

Modelo de identificação e análise de impactos da implantação de ferramentas case.

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