Embedded Data Dump Debugging with Hash Tag Fingerprinting
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Solution Overview
Problem
Debugging embedded software using data dumps is challenging due to difficulties in reconstructing memory layouts and bandwidth constraints limiting metadata description, making it hard to identify and diagnose issues in complex data structures.
Innovation Solution
A system that generates a hash tag for each data structure in the data dump, creates a lookup table associating hash tags with corresponding data structures, and embeds these hash tags in the data stream to facilitate efficient reconstruction of data structures while minimizing bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metadata descriptions are added to data dump to help reconstruct data structures, then data structure reconstruction accuracy is improved, but bandwidth consumption increases
Solution Approach 1:
The patent extracts only the essential identifying features of data structures (hash tags) rather than including complete metadata descriptions. This allows the system to identify and reconstruct data structures using minimal bandwidth while maintaining accuracy, as the hash tag serves as a compact reference to the full structure definition stored elsewhere in the data stream.
Solution Approach 2:
The hash tag acts as an intermediary between the data structure and its metadata. Instead of directly embedding full metadata descriptions in the data dump, the system uses hash tags as intermediate references that point to structure definitions, thereby reducing bandwidth consumption while preserving reconstruction accuracy.
2Adaptability or versatility
If manual reconstruction of data structures is performed from data dump, then flexibility in handling complex structures is improved, but human error and complexity increase
Solution Approach 1:
The system performs self-service by automatically generating hash tags for data structures and using these hash tags to identify and reconstruct structures during debugging. This eliminates manual reconstruction efforts, reducing both human error and complexity while maintaining the ability to handle complex data structures through automated processing.
Solution Approach 2:
The system performs preliminary action by pre-computing hash tags for all data structures during the instrumentation phase. This preparation work is done in advance, so that during actual debugging and reconstruction, the system can quickly identify and reconstruct structures without performing complex manual analysis, thereby reducing complexity and error.
3Speed
If hash tags are embedded in data stream for each data structure, then data structure identification speed is improved, but data stream size increases
Solution Approach 1:
The patent uses hash tags as cheap, compact identifiers that can be freely embedded in the data stream. Each hash tag is a small fixed-size value that provides rapid identification without significantly increasing data stream size. The hash tags are disposable references that enable quick structure identification while maintaining minimal overhead in the data stream.
Data Source
AI summary
An example of a system comprises a fingerprint calculator configured to receive data structure information and create a fingerprint as a function of the data structure information, a code generator configured to generate modified machine code, the modified machine code including the fingerprint embedded therein, a fingerprint identifier configured to identify the fingerprint in data received from a data dump, a data structure lookup table including the fingerprint and the data structure information associated with the fingerprint stored thereon, and a data interpreter configured to interpret, using data from the data dump and the data structure information, the data structure of at least a portion of the data from the data dump.