In this work, the applicability of model-driven development to increase, above all, the produc- tivity and quality of applications in software teams was researched. A tool called MoDev was developed following a model-driven software development iterative methodology consisting of the following phases: prototyping, reference implementation, analysis, meta-modeling, DSL design, model transformations building, DSL editor building and testing. MoDev requires well defined software architectures to work. Initially an illustrative software architecture was specified to test MoDev. However, any abstractable software architecture can be im- plemented using the tool. Moreover, MoDev was created with independent and composable models to enable reusing. That means, that components of some architecture can be used in another one and code generation templates can be customized to support any platform, technology or language. The creation of applications using MoDev is relatively easy. The analysts, architects and developers create a set of models, then create a main model im- porting the previous ones. The next step is to trigger the generation with a simple click requiring just seconds to get a lot of code automatically generated. Then, developers com- plete the code and tests manually. Once the code is fully functional, continuous integration and continuous delivery processes are recommended. Compared to a traditional development approach, which is code-centric, developing applications with MoDev involves the creation of models and the completion of artefacts which are automatically generated. It means that the process is model-centric. This change in the paradigm has to be taken into account when creating applications using model-driven engineering in software development teams.
A case study was delivered proving that MoDev leads software teams to significant improve- ments in multiple aspects and other few drawbacks that should be resolved in future research (see Table 5-1). In terms of productivity, approximately 70% of the code of the finished case study was automatically generated. In addition, other artefacts like configuration files and documentation were generated. Regarding quality, an automated software metrics tool was used to show that the generated code has no important quality issues. Besides, every generated artefact is fully compliant with the architecture, forcing developers to respect them as well. Concerning maintainability, an example of which tasks are necessary to create a new business method and the implications of doing the same work manually were illus- trated. MoDev does not only generate artefacts, but it really knows what changes to apply and where. With MoDev the problem of tool lock-in does not occur and as it uses textual languages the ability to model and code in large software teams is increased. In regard to
to testability, it helps by making the tests processes easier as it generates the skeleton of test modules and tests cases for every modelled method. Finally, respecting portability, as models were developed independent of technologies, model-to-text transformations can be performed for any platform.
Contrary to many related work and tools found in the literature, MoDev not only serves as a starting point for software projects, that means, it does not only generate the project’s base structure from scratch but it can be used iteratively and multiple times during the entire life cycle of an application. This is achieved thanks to the protected regions which allow re- generations. However, during the development of the case study, it was noted that changing or modifying accidentally these protected regions can be a bit harmful. Developers should pay attention to this because protected regions should keep always the same structure and identifiers.
Table 5-1.: The good and the bad of MoDev The good The bad
Improvements in productiv- ity, quality, maintainability, flexibility, testability, porta- bility and the ability to work in teams
Some minor drawbacks in terms of maintainability be- cause of the use of protected regions.
Serves not only as starting point for a project. It is use- ful in the entire project life- cycle.
Training required to learn new languages (DSL)
It is a generic solution and it is not heavily scoped to a particular domain.
It was not applied with different software architec- tures.
It is (relatively) easy to be extended and reused.
Lack of domain expressive- ness
One model, multiple imple- mentations.
Architecture conformance.
Two additional negative points were detected in this solution. First, it was not tested in multiple and bigger case studies. This is a weakness because the explained benefits could not be as bigger as with other applications. The same occurs for the people involved in the development of the case study. Maybe other developers could have different impressions of what the tool offers. On the other hand, MoDev was implemented with independent models
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that allows to be reusable, composable and extensible to different and heterogeneous soft- ware architectures. However, the second negative point comes from this because just one illustrative software architecture was taken as a reference. Having multiple and different software architectures could prove that MoDev is really reusable, composable and extensible as expected.
According to these results, MoDev can be initially used in production environments in small software projects and within small software teams. Once tested and evaluated in this kind of projects it can be improved and maintained to help the development of big projects in large teams.
5.0.3. Future work
Two directions are proposed for future research of this work. First of all, to extend MoDev in order to resolve some of the drawbacks explained in the previous section. Applying this tool in real software teams in real companies with many developers could give this research additional support to be implemented in big projects. Secondly, extending the tool to sup- port heterogeneous software architectures would provide additional reasons for the adoption of the tool.
Secondly, and looking forward to more interesting researches about model-driven develop- ment, MoDev lays the foundations for more extensible approaches. For example, Cabot et. al. [15] and Shroff et. al. [49] combine MDD with cloud-computing. Taking advantage of the approach followed by MoDev, where models are created independent in order to be reusable, a cloud repository of models can be created. This repository can publish a di- rectory of languages that any developer can use, extend and modify to create customized software architectures. Another topic related to cloud computing has to do with language editors. At this moments, languages have to be manipulated within Eclipse. However, recent approaches use web technologies to provide online editors with features like offline edition, online collaboration, integration with online services like github and tight integration with web browsers and mobile devices. Having online editors and a models directory would be a great start to collaborative modeling and generation services in the cloud.
for the software architecture
Figure A-1.: The document meta-model
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Figure A-3.: The Mongo-Config meta-model
Figure A-4.: The entity meta-model
Figure A-6.: The document-repository meta-model. An extension of the repository meta- model.
Figure A-7.: The relational-repository meta-model. An extension of the repository meta- model.
65
Figure A-9.: The route meta-model.
the case study
67
Figure B-2.: The repository DSL instance for the case study
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