#let m = yaml("/metadata.yml")

= Conclusions and Future Work

== Project Achievements

Throughout the implementation of this graduation thesis, with the valuable
guidance of #m.supervisors.at(0), our team has successfully achieved positive
outcomes and personal growth. Working together on this project has not only
enhanced our professional skills but has also fueled our passion for the
subject matter. Through this experience, we have effectively applied the
knowledge gained from our studies at #m.university, combined with our
understanding of language design and artificial intelligence. Moreover, we have
harnessed the power of cutting-edge technologies like GitHub Actions, Astro,
Tailwind CSS, and the Language Server Protocol, positioning ourselves for
future innovation.

== Strengths and Weaknesses

=== Strengths

The Ungrammar Language Ecosystem serves as a valuable proof of concept for
implementing a robust LSP ecosystem. By providing a comprehensive set of tools
and features, our system empowers users to effectively work with the Ungrammar
language and explore its potential applications.

Key strengths of our system include:

- *Comprehensive LSP Ecosystem*: Offers a wide range of LSP features for
  enhanced language support.
- *AST/CST Conversion*: Facilitates the translation between Abstract Syntax
  Trees (ASTs) and Concrete Syntax Trees (CSTs), enabling deeper language
  analysis and manipulation.
- *Language Prototyping*: Serves as a platform for prototyping new programming
  languages, allowing developers to experiment with different syntaxes and
  semantics.
- *Cross-Platform Compatibility*: Operates seamlessly in various environments,
  from local development to cloud-based platforms.

=== Weaknesses

While our system demonstrates significant potential, there are areas where it
could be further improved:

- *Language Complexity*: The current implementation may not be optimally suited
  for highly complex languages with intricate type systems and dependency
  analysis.
- *Learning Curve*: Users new to LSP or the Ungrammar language may face a
  learning curve when adopting the system.

== Future Directions

Building upon our achievements, we plan to explore the following future
directions:

- *Language Expansion*: Apply the LSP ecosystem to more complex languages like
  Java or C\#, addressing the challenges associated with their intricate
  features.
- *Feature Enhancements*: Continuously improve the system's capabilities by
  adding new features and functionalities.
- *Community Engagement*: Foster a vibrant community around the Ungrammar
  language and its ecosystem, encouraging collaboration and knowledge sharing.
- *Commercialization*: Explore opportunities for commercialization and
  monetization of the LSP ecosystem.

By pursuing these future directions, we aim to further contribute to the
advancement of language support technologies and provide valuable tools for
developers and researchers.
