Temporal Edit Patterns for Precise Source Code Refactoring
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Solution Overview
Problem
Existing editing tools struggle to facilitate the efficient and precise invocation of editing subtools at appropriate times and places within a document, particularly in large source code changes, due to user unawareness of available functionalities and complex regex requirements.
Innovation Solution
The implementation of edit automation functionalities, including anchor target lists and temporal edit patterns, which identify appropriate places for applying subtools and recommend or automate edits, leveraging a transform provider and a library of automatable edit sequences to stay within the user's current editing workflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing editing tools use simple string replacement or regex-based search and replace, then the operation is simple and familiar to users, but the precision and comprehensiveness of edits in large source code changes are insufficient
Solution Approach 1:
The patent introduces an intermediary system that sits between the user and the document editing process. This intermediary analyzes the document structure, identifies relevant elements, and presents curated editing options to the user. The intermediary translates complex structural analysis into simple user interactions, achieving precise edits without requiring users to understand complex tools or patterns.
Solution Approach 2:
The patent replaces traditional mechanical search-and-replace mechanisms with an intelligent system that understands document structure and semantics. Instead of relying on regex patterns or simple string matching, the system uses structural analysis to identify edit targets, substituting the mechanical approach with a cognitively-aware approach that achieves higher precision.
2Measurement precision
If editing tools provide comprehensive functionality for large source code changes, then the potential for precise edits is improved, but the difficulty of detecting and using appropriate functionalities increases
Solution Approach 1:
The system performs self-service by automatically analyzing the document structure and identifying relevant editing opportunities without requiring user intervention to configure or activate specific functions. The system serves itself by detecting its own capabilities and applying them contextually, presenting only the most relevant editing options to the user rather than requiring users to search through comprehensive functionality lists.
Solution Approach 2:
The system performs preliminary analysis of the document structure before presenting editing options to the user. By pre-processing the document to identify relevant elements and potential edits, the system makes functionality detectable and ready for use, eliminating the need for users to understand or configure complex tools during the editing process.
3Measurement precision
If users manually invoke editing subtools at appropriate places, then the edits can be precise and controlled, but the time and effort required for large source code changes increases significantly
Solution Approach 1:
The system provides continuous feedback to the user during the editing process, presenting relevant editing options as the user works through the document. The system monitors user actions and document state, dynamically adjusting and presenting the next appropriate editing opportunities, thereby maintaining precision while reducing the time required compared to manual invocation of subtools.
Solution Approach 2:
The system maintains continuity of useful action by automatically progressing through editing opportunities in a logical sequence based on document structure and user intent. Rather than requiring users to pause and manually invoke subtools at each step, the system continuously presents and executes relevant edits, maintaining the editing flow and significantly reducing total editing time while preserving precision.
Data Source
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AI summary
Edit automation functionality generalizes edits performed by a user in a document, locates similar text, and recommends or applies transforms while staying within a current workflow. Source code edits such as refactoring are automated. The functionality uses or provides anchor target lists, temporal edit patterns, edit graphs, automatable edit sequence libraries, and other data structures and computational techniques for identifying locations appropriate for particular edits, for getting transforms, for selecting optimal transforms, for leveraging transforms in an editing session or later, and for displaying transform recommendations and results. The edit automation functionality enhances automation subtool generation, discoverability, and flexibility, for refactoring, snippet insertion, quick actions in an integrated development environment, and other automatable edit sequences.