5results about How to "Improve debuggability" patented technology

The application discloses a container orchestration deployment package generation method, system, device and storage medium, and relates to the technical field of cloud computing.The method comprises the following steps: identifying configuration files and metadata related to deployment from a target source code warehouse according to target source code warehouse information in obtained deployment package generation instructions; converting the configuration files and metadata into a deployment blueprint through static analysis and collaborative analysis of a preset language model; performing virtualization environment adaptation on the deployment blueprint by using available resources and policy constraints corresponding to target virtualization tenant information to obtain an adapted deployment blueprint; and generating an orchestration deployment package corresponding to the adapted deployment blueprint.The application introduces a deployment blueprint as a core intermediate representation, decouples links such as warehouse analysis, environment adaptation and deployment package generation, improves debuggability and expandability, can stably and efficiently automatically generate a high-quality container orchestration deployment package, and realizes automatic delivery with high availability and high adaptability.

The invention discloses a task decomposition system and method for an intelligent robot with a body based on physical state deduction, and relates to the technical field of artificial intelligence robots. The system comprises a task instruction receiving and initial decomposition module, a state sensing and formatting input module, a task feasibility deduction module, a feedback and optimization closed loop module and a decision and output module. According to the method, a technical framework of sensing, deducing and optimizing a closed loop is constructed, so that the robot can perform virtual rehearsal on a task sequence before executing actual physical actions, thereby identifying environment state conflicts and execution path risks in advance, and fundamentally improving the task execution mode from passive response depending on trial and error, and improving the task execution efficiency. The method is converted into active reliable planning based on physical state deduction, and the adaptability, the safety and the deployment efficiency of the robot for executing complex tasks in an open environment are remarkably improved.

The application relates to the technical field of audio-video synchronization control, and discloses a conference room audio-video synchronization visual control method and system, wherein the conference room audio-video synchronization visual control method comprises the following steps: step S1, calculating audio-video collection time; step S2, calculating compensation time shift; step S3, extracting a target audio packet; step S4, calculating audio playing delay and video waiting delay; step S5, calculating a presentation moment; step S6, calculating a graph strip pixel width; and step S7, generating a joint control instruction. The application calculates the reflection sound path difference through a mirror sound source method, introduces a frame grid coefficient in combination with the interframe optical axis change of a camera, realizes dynamic synchronization compensation based on the physical structure of a conference room and the video frame state, can correct structural synchronization errors, locks the presentation moment to a display refresh grid, realizes the visualization of the synchronization compensation process and the unified control of audio-video and visualization.

The invention discloses an automatic driving lane changing decision-making method and device and a storage medium, and the method combines frequency space action marking (FAST) and Monte Carlo tree search (MCTS): firstly, compressing and coding a continuous driving action sequence into low-dimensional discrete marks by using a FAST model, and constructing an efficient semantic action space; further, a strategy neural network is trained, diversified candidate action marking sequences are predicted in the marking space according to the current environment state, and a plurality of smooth intention tracks are obtained after FAST decoding; and finally, expanding and simulating the intentional tracks as feasible actions of the MCTS, and selecting a lane changing strategy with the optimal long-term benefit through a search evaluation mechanism. According to the method, the search space of the MCTS is greatly reduced through discretization compression of the action space, so that accurate evaluation of decision-making long-term benefits becomes possible, and anthropomorphic, safe and comfortable lane changing behaviors can be efficiently generated.

This application relates to a domain-specific language compiler for cache coherence protocols, belonging to the field of computer architecture modeling and simulation technology. The compiler takes a high-level abstract specification of the cache coherence protocol as input and automatically converts it into cache controller and / or directory controller code executable by a periodic precision simulator. Through systematic mapping and translation of the protocol's finite state machine, event-triggered mechanism, concurrent transaction management, and asynchronous hardware interaction, it achieves event-driven, non-blocking control logic generation. Simultaneously, the compiler supports network communication code generation, debug tracing injection, and formal logical equivalence checks. Furthermore, it incorporates a performance constraint-aware optimization module to automatically optimize the generated state machine, thereby improving simulation efficiency, reducing development complexity, and enhancing verifiability while ensuring the semantic correctness of the protocol.