Automated Privacy Documentation via Source Code Analysis
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Solution Overview
Problem
Current systems lack effective methods for managing and documenting personal data processing activities, leading to inefficiencies in compliance with privacy and security regulations, and inadequate documentation of software code, which hinders understanding and maintenance.
Innovation Solution
A data processing system that generates and populates a data model to map relationships between data assets, includes features for analyzing computer code to identify personal data collection, and automatically documents the purpose and usage of personal data, thereby creating a comprehensive data inventory and privacy impact assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If programmers focus on coding rather than documenting, then development productivity is improved, but code documentation quality deteriorates
Solution Approach 1:
The system performs self-service by automatically analyzing source code and generating documentation without requiring programmer intervention. The code analysis module scans code files, identifies personal data processing operations, and automatically creates privacy documentation, allowing the system to document itself rather than relying on external programmers.
Solution Approach 2:
The patent replaces the manual mechanical process of programmers writing documentation with an automated computational system. The code analysis module uses automated code scanning and parsing techniques to extract documentation information, substituting human effort with machine-based analysis and generation processes.
2Reliability
If manual documentation of personal data processing is implemented, then privacy compliance is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system automatically generates privacy compliance documentation by analyzing its own codebase. The code analysis module identifies personal data processing operations and the system automatically creates the required documentation, eliminating the need for manual tracking and reporting by personnel.
Solution Approach 2:
The system provides continuous automated monitoring and documentation generation as code is developed and modified. Rather than periodic manual reviews, the code analysis module continuously scans code changes and updates privacy documentation in real-time, ensuring ongoing compliance without interrupting development workflows.
3Measurement precision
If comprehensive code analysis is performed to identify personal data collection, then privacy assessment accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the code analysis process into distinct functional modules: a code scanning module that identifies potential personal data operations, a pattern recognition module that matches code patterns to privacy concerns, and a documentation generation module that creates compliance reports. This modular segmentation manages complexity while maintaining comprehensive analysis capability.
Solution Approach 2:
The code analysis module serves multiple functions: it scans source code for personal data processing operations, identifies the specific type of data being processed, determines the purpose of processing, and generates comprehensive privacy documentation. This multi-functionality reduces overall system complexity by consolidating multiple tools into a single unified system.
Data Source
AI summary
Data processing systems and methods according to various embodiments are adapted for automatically detecting and documenting privacy-related aspects of computer software. Particular embodiments are adapted for: (1) automatically scanning source code to determine whether the source code include instructions for collecting personal data; and (2) facilitating the documentation of the portions of the code that collect the personal data. For example, the system may automatically prompt a user for comments regarding the code. The comments may be used, for example, to populate: (A) a privacy impact assessment; (B) system documentation; and/or (C) a privacy-related data map. The system may comprise, for example, a privacy comment plugin for use in conjunction with a code repository.