Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
Empirical studies of software engineering: a roadmap
Proceedings of the Conference on The Future of Software Engineering
Web Modeling Language (WebML): a modeling language for designing Web sites
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Types of software evolution and software maintenance
Journal of Software Maintenance: Research and Practice
Designing Data-Intensive Web Applications
Designing Data-Intensive Web Applications
Matching methodology to problem domain
Communications of the ACM - New architectures for financial services
Evidence-Based Software Engineering for Practitioners
IEEE Software
Cross versus Within-Company Cost Estimation Studies: A Systematic Review
IEEE Transactions on Software Engineering
An update to experimental models for validating computer technology
Journal of Systems and Software
SEAA '09 Proceedings of the 2009 35th Euromicro Conference on Software Engineering and Advanced Applications
PROFES'10 Proceedings of the 11th international conference on Product-Focused Software Process Improvement
A model-driven measurement procedure for sizing web applications: design, automation and validation
MODELS'07 Proceedings of the 10th international conference on Model Driven Engineering Languages and Systems
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Model-driven Engineering (MDE) approaches are often recognized as a solution to palliate the complexity of software maintainability tasks. However, there is no empirical evidence of their benefits and limitations with respect to code-based maintainability practices. To fill this gap, this paper illustrates the results of an empirical study, involving 44 subjects, in which we compared an MDE methodology, WebML, and a code-based methodology, based on PHP, with respect to the performance and satisfaction of junior software developers while executing analysability, corrective and perfective maintainability tasks on Web applications. Results show that the involved subjects performed better with WebML than with PHP, although they showed a slight preference towards tackling maintainability tasks directly on the source code. Our study also aims at providing a replicable laboratory package that can be used to assess the maintainability of different development methods.