Automated File Change Detection via Post-Header Masking
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Solution Overview
Problem
Current systems lack an automated method to accurately identify files that have changed between builds, leading to manual errors and delays in patch preparation, as existing attempts to automate file comparison have been ineffective, especially with common header files and portable executable files showing false differences.
Innovation Solution
A computer-implemented method that identifies and masks specific data fields within post-file-header sections of program files to exclude known changing elements, allowing for accurate comparison and determination of file changes, even when source code remains unchanged.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If developers manually inspect files to determine patch inclusion, then accuracy can be maintained, but time consumption and error risk increase
Solution Approach 1:
The system performs automatic file comparison and change detection without requiring manual developer inspection. The computer-implemented method autonomously identifies changed files between builds by comparing file contents, section headers, and metadata, thereby eliminating manual labor while maintaining accuracy.
Solution Approach 2:
The patent replaces manual mechanical inspection with automated computer-based comparison systems. The method uses computational algorithms to compare file structures, section headers, and data fields between builds, substituting human manual review with automated digital comparison.
2Loss of time
If existing automated comparison systems are used, then time is saved, but false differences are identified due to inability to handle common header files and relocation tables
Solution Approach 1:
The system applies different comparison strategies to different parts of the file structure. It handles common header files, section headers, and data fields differently from code sections, using specialized comparison logic for each component type to avoid false differences while maintaining automated processing.
Solution Approach 2:
The method performs preliminary identification and classification of file components (headers, sections, data fields) before comparison. By pre-characterizing the file structure and identifying which components are likely to change independently of source code, the system prepares appropriate comparison parameters in advance to avoid false positives.
3Reliability
If all files are included in patches to be safe, then completeness is ensured, but patch size and complexity increase
Solution Approach 1:
The system extracts and separates truly changed files from unchanged files by performing detailed comparison of file contents, section headers, and metadata. Only files with actual changes are extracted for patch inclusion, while files with only expected variations (such as header file changes) are excluded, thereby reducing patch complexity while maintaining reliability.
Data Source
AI summary
A computer-implemented method for automatically identifying changes in deliverable files may include (1) identifying, within first and second versions of a program file, at least one post-file-header section that is located after a file header of the program file, (2) locating, within the post-file-header section of the first version of the program file, a first set of characters that correspond to at least one data field that is known to potentially change between builds of the program file even when source code of the program file has not changed, (3) locating, within the post-file-header section of the second version of the program file, a second set of characters that correspond to the data field, and (4) masking both the first and second sets of characters from a comparison between the first and second versions of the file. Various other methods, systems, and computer-readable media are also disclosed.