MOMoT is a research prototype tool based on Eclipse technologies, designed for search-based optimization and model transformations. The goal of this thesis is to modernize MOMoT by re-architecting it as a service-oriented application, providing Web API endpoints for MDE integrations…


MOMoT is a research prototype tool based on Eclipse technologies, designed for search-based optimization and model transformations. The goal of this thesis is to modernize MOMoT by re-architecting it as a service-oriented application, providing Web API endpoints for MDE integrations…

Background: MOMoT is a research prototype tool based on Eclipse technologies, designed for search-based optimization and model transformations. While MOMoT has demonstrated its effectiveness in model-driven engineering (MDE), its usability remains limited due to its desktop-based nature. To enhance accessibility and integration within modern engineering workflows, this thesis aims to transform MOMoT into a cloud-native service. The revamped MOMoT will provide a web-based interface for end users and an API for developers, enabling seamless integration into complex MDE workflows.

Aim of the Thesis: The goal of this thesis is to modernize MOMoT by re-architecting it as a service-oriented application. This transformation will involve:

  • Developing a web-based interface to make MOMoT accessible to non-expert users.
  • Refactoring MOMoT into microservices to ensure scalability and cloud compatibility.
  • Providing API endpoints for integration into broader MDE workflows.
  • Evaluating usability, performance, and scalability to ensure the effectiveness of the new architecture.

Tasks:

  1. Definition of Requirements:
    • Identify core functionalities of MOMoT that must be preserved or enhanced.
    • Gather user and developer requirements through surveys or interviews.
    • Analyze existing MDE workflows to determine integration points.
  2. Concept Development:
    • Design a modular architecture that separates MOMoT’s core logic from its Eclipse dependencies.
    • Define a microservices-based approach for cloud deployment.
    • Develop a strategy for API exposure and workflow integration.
  3. Implementation:
    • Frontend: Develop a web-based interface using modern frameworks (to be added).
    • Backend: Refactor MOMoT into microservices, exposing RESTful APIs.
    • Cloud Deployment: Containerize services using Docker and orchestrate them with Kubernetes.
  4. Evaluation
    • Benchmark performance and scalability of the cloud-based MOMoT service.
    • Analyze integration success within existing MDE workflows.
    • Conduct usability tests with real users to assess the effectiveness of the web interface.
  5. Expected Results:
    • A fully functional web-based MOMoT service accessible to end users.
    • A set of APIs enabling integration into complex model-driven engineering workflows.
    • A performance and usability evaluation comparing the new service-oriented MOMoT with its original Eclipse-based version.
    • Recommendations for best practices in modernizing research prototypes into cloud-native applications.

Supervision:
This thesis will be supervised by Manuel Wimmer and Luca Berardinelli. Interested individuals can contact them for further details or collaboration opportunities.

Marrying Search-Based Optimization and Model Transformations in the Cloud: Revamping MOMoT into a Cloud-Native Service