project-proposal-2025

SmartDoc AI

Abstract

SmartDoc AI is a plugin embedded in existing document editors such as Word or WPS. Its core functionality leverages AI algorithms to intelligently process text within documents. The plugin supports text enhancement, expansion, condensation, and grammar checking, directly inserting modification suggestions and revised text into the document to help users improve writing quality and efficiency.

In the MVP phase, the project will focus on AI-powered text rewriting. Future iterations will expand AI reading capabilities, including translation and text summarization, further enhancing workplace productivity. To ensure practical applicability, this project will emphasize four key quality attributes: Extensibility, Reliability, Security, and Scalability.

Author

Name: Wenmin Liu

Student number: 48490667

Functionality

Full System Functionality Overview:

• AI Text Rewriting Features:
  • Enhancement: Improves the language style of the input text, making it more elegant and logically clear.
  • Expansion: Expands key information by adding supporting arguments and details.
  • Condensation: Compresses lengthy text while retaining core information for easier readability.
  • Grammar Checking: Automatically detects and corrects grammatical errors and punctuation mistakes.
• AI Reading Features:
  • AI Translation: Automatically translates text into multiple languages.
  • AI Summarization: Generates concise summaries of long documents, extracting key information.
• Plugin Integration:
  • Integrates with mainstream document editors (initially targeting WPS or Microsoft Word), providing a sidebar or floating window for users to access AI features.
  • Allows users to select text and invoke AI functions directly via the right-click menu or a quick-access toolbar.
• User Feedback & Customization:
  • Users can accept or reject AI-generated suggestions and provide feedback to continuously improve the algorithm.
  • Provides customization options to adjust AI-generated text styles (e.g., formal, conversational, academic).

    Scope

    To ensure the project is deliverable within the given timeframe while maintaining practical usability, the MVP version will focus on the following core functionalities:

• Core AI Rewriting Features:
  • Implement four key AI-powered text processing functions: enhancement, expansion, condensation, and grammar checking.
  • Users can select a text segment, click the respective AI function, and receive AI-generated rewritten content displayed in an intuitive manner (e.g., side-by-side comparison in a sidebar or appended after the original text).
• Single-Platform Plugin Integration:
  • Initially targeting WPS or Microsoft Word, developing a lightweight plugin-based interface.
  • The plugin will feature a simple and user-friendly UI, supporting text input, result display, and user feedback collection.
• Feedback Collection:
  • A built-in feedback system will track user adoption rates and satisfaction with AI suggestions.

    Quality Attributes

    The success of this project will depend on the following key quality attributes:

Extensibility

The system should allow new features to be added seamlessly over its lifespan without requiring major modifications to the existing architecture. Each AI rewriting function should be designed as a standalone, pluggable module, enabling future integration of AI-powered translation and summarization without disrupting existing functionality. Additionally, the system should provide well-documented APIs and extension points, ensuring that developers can easily incorporate new AI capabilities or adapt the plugin for different document editors.

Reliability

The AI-powered features must maintain high availability during document editing, preventing crashes or excessive delays that could disrupt the user experience. Ensuring reliability will allow users to consistently receive accurate and efficient text refinements, making the system a dependable tool in real-world office environments.

Security

Since the plugin interacts with external AI services and processes document content, it must prioritize data security and confidentiality. Measures should be in place to prevent unauthorized access or data leaks, ensuring that sensitive information remains protected. A strong security framework is also crucial for fostering user trust in the system.

Scalability

The system should be capable of handling increasing user demand and text processing workloads efficiently. As more users access the plugin and concurrently invoke AI-powered rewriting functions, it must maintain stable performance and responsiveness. The architecture should support high concurrency, ensuring a smooth experience even under heavy usage.

Evaluation

In addition to the basic implementation of the MVP, the core quality attributes must also be met. Their achievement will be evaluated based on the following criteria.

Extensibility

• Conduct a code review to ensure that each AI rewriting function is implemented as a standalone, pluggable module.
• Review the development documentation to verify that the API and extension interfaces are well-defined and intuitive, allowing future developers to integrate new features without difficulty.
• Assess the extent of code modifications required to add new functionality (e.g., AI summarization), aiming to keep changes within 10% of the total codebase.

Reliability

• Conduct 100 consecutive AI calls to test the system’s error rate, with the target error rate being less than 2%.
• Perform high concurrency testing by simulating 50/100/200 concurrent users calling the AI rewriting function, measuring the system’s response time under different loads, and ensuring the average response time is ≤ 2 seconds.
• Run long-duration stability tests (e.g., 24-hour continuous AI function calls), observe any system crashes or significant performance degradation, and analyze log data.

Security

• Perform static code analysis to identify potential security vulnerabilities such as SQL injection and cross-site scripting (XSS), ensuring compliance with security standards.
• Conduct penetration testing to simulate malicious attacks, including man-in-the-middle (MITM) attacks and token hijacking, to assess the plugin’s resistance to security threats.
• Verify data transmission encryption, ensuring that API communication between the plugin and external AI services is secured with HTTPS/TLS and that encryption keys are not exposed in the code repository.

Scalability

• Conduct high-concurrency testing by simulating 1,000+ users simultaneously invoking AI rewriting functions to assess server response time, throughput, and resource utilization.
• Perform server scalability testing by incrementally increasing backend service instances to evaluate whether the load-balancing strategy effectively distributes traffic and ensures system performance scales with computing resources.
• Execute stress testing by continuously sending a large volume of AI task requests to verify that the system does not experience request loss or prolonged response times.