In search of evidence for model-driven development claims: An experiment on quality, effort, productivity and satisfaction

Model-Driven Development (MDD) is a paradigm that prescribes building conceptual models that abstractly represent the system and generating code from these models through transformation rules. The literature is rife with claims about the benefits of MDD, but they are hardly supported by evidences. T...

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Bibliographic Details
Published in:Information and software technology Vol. 62; pp. 164 - 186
Main Authors: Panach, Jose Ignacio, España, Sergio, Dieste, Óscar, Pastor, Óscar, Juristo, Natalia
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.06.2015
Elsevier Science Ltd
Subjects:
Automatic programming
Experiments
Mathematical models
Methodologies
Product development
Productivity
Programming paradigms
Quality analysis and evaluation
Software engineering
Software industry
Studies
Quality analysis and evaluation
Automatic programming
Methodologies
Programming paradigms
ISSN:0950-5849, 1873-6025
Online Access:Get full text
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Summary:Model-Driven Development (MDD) is a paradigm that prescribes building conceptual models that abstractly represent the system and generating code from these models through transformation rules. The literature is rife with claims about the benefits of MDD, but they are hardly supported by evidences. This experimental investigation aims to verify some of the most cited benefits of MDD. We run an experiment on a small set of classes using student subjects to compare the quality, effort, productivity and satisfaction of traditional development and MDD. The experiment participants built two web applications from scratch, one where the developers implement the code by hand and another using an industrial MDD tool that automatically generates the code from a conceptual model. Outcomes show that there are no significant differences between both methods with regard to effort, productivity and satisfaction, although quality in MDD is more robust to small variations in problem complexity. We discuss possible explanations for these results. For small systems and less programming-experienced subjects, MDD does not always yield better results than a traditional method, even regarding effort and productivity. This contradicts some previous statements about MDD advantages. The benefits of developing a system with MDD appear to depend on certain characteristics of the development context.
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ISSN:0950-5849
1873-6025
DOI:10.1016/j.infsof.2015.02.012