Feat/LDG-537--nano-app-implement-initialize-method #40
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- Add new instruction INS_INIT_CONTRACT (0x07) for contract initialization - Create initContract.c/.h files with handler implementation - Add UI flow for displaying contract amount and module reference - Add new error codes for name/params length and module ref validation - Implement chunked processing for contract name and parameters - Add Python test client support for init contract instruction - Add test case with snapshots for contract initialization flow - Update handler.c and globals.h to support new instruction The implementation allows users to initialize contracts by providing the amount, module reference, contract name, and parameters, with appropriate UI confirmation steps and chunked data processing for larger inputs.
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| // typedef struct { | ||
| // uint8_t version[32]; | ||
| // uint8_t sourceLength[32]; | ||
| // } deployModuleBlob_t; |
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Commented-out code Note
GuilaneDen
reviewed
Dec 11, 2024
- Increase amountDisplay buffer from 21 to 30 chars in initContract.h - Update test to use max uint64 value (0xFFFFFFFFFFFFFFFF) - Update test signature to match new amount value - Update snapshot images to reflect larger amount display Fixes buffer overflow issue when displaying large contract amounts by increasing the display buffer size to accommodate maximum uint64 values.
- Subtract data length from MAX_APDU_LEN when splitting messages - Fix chunk size calculation in deployModule and initContract - Update split_message calls to account for header bytes - Ensure first chunk (len + data) stays within MAX_APDU_LEN limit Fixes APDU length overflow where first chunk (2 bytes length + data) exceeded MAX_APDU_LEN by not accounting for the length bytes in the available space calculation.
- Generate golden snapshots
n4l5u0r
approved these changes
Dec 11, 2024
n4l5u0r
deleted the
feat/LDG-537--nano-app-implement-initialize-method
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The implementation allows users to initialize contracts by providing the
amount, module reference, contract name, and parameters, with appropriate
UI confirmation steps and chunked data processing for larger inputs.