56results about "Code refactoring" patented technology

The application provides a code analysis method and related equipment. The method comprises the following steps: a server acquires identity information of a change file and a position of a changed code block in the change file, wherein the changed code block is located in a terminal of a distributed system, and the distributed system comprises a plurality of terminals for providing code writing; the server determines a base version of the change file according to the identity information of the change file; and further, according to the position of the changed code block in the change file, the server determines whether the base version of the change file comprises a target code block overlapping with the position of the changed code block, and if the base version comprises the target code block, the server gives a warning to at least one terminal in the distributed system. The above method can give a warning in time under the condition that the changed code block is determined to be modified. In this way, in the process of collaborative development, a developer can know the modification condition of the code in time, so as to determine whether the modified code will affect the program written by the developer.

To provide a method of automatic denoising of machine learning projects, a program, and an electronic device.SOLUTION: A method includes: receiving a machine learning (ML) project; determining one or more atomic steps corresponding to an ML pipeline to determine an atomized ML pipeline; instrumenting the atomized ML pipeline to determine an instrumented ML pipeline including one or more operations corresponding to the received ML project; executing the instrumented ML pipeline to capture one or more data-frame snapshots based on each of the one or more operations; constructing a feature provenance graph (FPG) on the basis of the ML pipeline and the captured one or more data-frame snapshots; and identifying one or more discarded features, from a plurality of features corresponding to the received ML project, based on the constructed FPG.SELECTED DRAWING: Figure 5

The application belongs to the field of reconstruction methods, and particularly relates to a kind of high-efficiency autonomous reconstruction method of satellite-borne software facing constellation network system.A kind of autonomous reconstruction method of satellite-borne software facing constellation network system, wherein, including the following steps: step one: satellite node partition configuration;Step two: constellation autonomous reconstruction scheme.The application has the following beneficial effects relative to prior art:(1) the application realizes the uniformity of software version in constellation, and only needs to make a version of reconstruction file when reconstructing constellation;(2) when reconstructing constellation, only needs to use the injection of star-ground TT&C link once, and the reconstruction of satellite node will be completed autonomously with the aid of inter-satellite network, saving the valuable TT&C arc segment resource;(3) the satellite node outside the visible arc segment can be reconstructed, simplifying the task amount of constellation reconstruction and improving the efficiency.

This invention provides a payload software reconfiguration method for LEO satellites, applicable to ground control stations, payload management equipment within LEO satellites, and target payload units. The method divides the payload software reconfiguration of the target payload unit into two stages: In the first stage, within the data transmission arc, the ground control station fully utilizes the uplink bandwidth of the space-to-ground data transmission link to rapidly upload the software reconfiguration file to the payload management equipment for storage. In the second stage, the payload management equipment transmits the software reconfiguration file to the target payload unit via the internal interconnection bus, thus achieving software reconfiguration of the target payload unit. Furthermore, the accuracy of the software reconfiguration file transmission can be quickly determined through the first feedback information sent by the payload management equipment and the second reception feedback information sent by the target payload unit, allowing for timely re-transmission of the software reconfiguration file. Therefore, this method effectively improves the efficiency and accuracy of payload software reconfiguration for LEO satellites.

The application relates to a hierarchical business change code extraction system and method based on an autonomous positioning algorithm. The method comprises the following steps: obtaining a business code submission record of a user; obtaining difference data and code file content according to the business code submission record; analyzing the difference data through an autonomous extraction algorithm of key character recognition and / or sequential sliding mark disassembly, and extracting change information, wherein the change information comprises a change method, a change line number and newly added change code; extracting formatting information from the code file, wherein the formatting information comprises package information, import information, method definition and parameter information of a class file; and hierarchically storing the change information and the formatting information to support business change code extraction. The hierarchical business change code extraction system and method based on the autonomous positioning algorithm can realize automatic, structured and high-precision analysis of business code changes, and improve the extraction efficiency after code changes.

A method and Product Data Management (PDM) system for configuring a product are disclosed. The PDM system is configured for obtaining a plurality of original constraints from a source. Further, a plurality of sequence groups is identified from the plurality of original constraints, wherein constraints within each sequence group of the plurality of sequence groups have relative sequential effects on each other. Further, each constraint within each sequence group is remodeled to a modified expression suitable for processing using a declarative solver. The modified expression is indicative of a sequential processing priority for the constraint within the sequence group. The sequence groups are processed simultaneously, using the declarative solver, to determine one or more valid product configurations. Each constraint is processed based on the respective sequential processing priority within the corresponding sequence group. The one or more valid product configurations are outputted on an output unit.

This application discloses a database-based operation method, apparatus, device, and storage medium, belonging to the field of database technology. The method includes: receiving input text, whereby the input text describes database-related operational requirements in natural language; generating a first DSL statement, whereby the first DSL statement implements at least one database-related operation, and the at least one operation satisfies the operational requirements described in the input text; parsing the first DSL statement according to the syntax corresponding to the type of the at least one operation in the DSL syntax, to execute the at least one operation, wherein the database-related operations supported by the DSL include operations on database query results. The DSL provided in this application supports operations on database query results and can be widely used in various scenarios requiring additional operations on database query results.

Embodiments of the present application provide a code generation method and a computing device, the method comprising: obtaining request information sent by a terminal, the request information being used to request code generation; generating initial reply information corresponding to the request information, the initial reply information comprising initial code corresponding to the request information; determining a test case according to the initial reply information, and testing the initial code based on the test case to obtain a test result; determining target reply information corresponding to the request information according to the test result and the initial reply information, the target reply information comprising target code determined based on the initial code; and sending the target reply information to the terminal. The method does not require manual testing of the initial code, generates a test case based on the initial reply information and tests the initial code through the test case, and determines the target reply information in combination with the test result and the initial reply information, which is conducive to quickly and accurately generating code corresponding to the request information.

The application discloses a Flutter application reverse reconstruction method based on large model semantic alignment, collects Dart source code and corresponding APK file data of an open-source Flutter application, extracts intermediate language IL and semantic clue information therefrom, and constructs a relationship mapping table of the intermediate language IL and the semantic clue information; an alignment sample data set of Dart source code segments and intermediate language IL segments is constructed; a Flutter application reverse generation model is built, the model is trained by using the alignment sample data set; the trained reverse generation model is used to generate function-level Dart source code segments according to inputted intermediate language IL, the semantic clue information corresponding to the intermediate language IL is fused with the Dart source code segments generated corresponding to the intermediate language IL, the semantic aggregation, dependency sorting and structure reconstruction of the Dart source code segments are performed by using the semantic understanding and context reasoning capability of a large model, and finally, a Dart source code file with complete syntax and capable of being compiled is generated.

The application discloses a C++ conditional member definition method and system based on meta-precompilation, and relates to the field of computer programming language processing.A meta-precompilation stage is introduced before the standard C++ compilation process, a custom conditional member syntax block contained in an original C++ source file is parsed, a parent template class and a conditional branch inside the parent template class and starting from a specific syntax mark are identified, a plurality of standard C++ template partial specialization definitions are generated according to a compile-time condition expression in the conditional branch, and member definitions in the corresponding conditional branch are directly injected into a top-level scope of the partial specialization class.Finally, the original class definition is replaced with the generated partial specialization definition, and a standard C++ source file is output for subsequent compilation.The application significantly improves the code readability, maintainability and development efficiency of C++ template metaprogramming, and is particularly suitable for high-reliability software fields such as industrial control and embedded systems.

This application proposes a method, apparatus, device, and storage medium for customizing configuration pages. The method includes: parsing a page configuration file of a page to be generated; obtaining a page code template that conforms to the parsed page type information and page code technology stack information; obtaining the first code of each container block contained in the page to be generated based on the parsed page block structure information, and filling the first code into the page code template; obtaining the second code of the component contained in each container block based on the parsed component information, and filling the second code into the page code template; and generating a page code file of the page to be generated based on the completed page code template. This application can dynamically generate pages, realizing effective customization and modification of pages.

The application provides a model training method, which comprises the following steps: determining a sample abnormal subprogram in a sample program, and determining sample syntax structure information of the sample abnormal subprogram based on the sample abnormal subprogram; constructing an initial program repair model, and setting state information, action information and reward information for the initial program repair model; training the initial program repair model after the setting based on the sample abnormal subprogram and the sample syntax structure information by using a target reinforcement learning algorithm, to obtain a target program repair model, thereby solving the problems of poor efficiency and low accuracy of the related art in repairing the smart contract. The application also discloses a program repair method, an electronic device, a storage medium and a program product.

Distinguishing pattern differences from non-pattern differences. A set of differences is identified. The set comprises a plurality of differences between first and second versions of a document. A pattern is identified. The pattern explains a transformation from a first string in the first version of the document to a second string in the second version of the document. A subset of differences are identified. The subset comprises a plurality of differences, from among the set, which match the pattern. While presenting a user interface that visually highlights differences between the first and second versions of the document, a first visual treatment is applied to a first difference, based on the first difference being included in the subset. A second visual treatment is also applied to a second difference, based on the second difference being excluded from the subset. The second visual treatment is different than the first visual treatment.

The ability to accurately estimate the Lines of Codes (LoC) needed to complete migration of application has been a challenge over the past decades. Embodiments disclosed herein provide a method and system for estimation of efforts in migrating applications to post quantum cryptography (PQC) state. The system, based on a determined cyclomatic complexity for one or more components present in a refined slicing output and a refined coupling output is estimated. Further, an effort of migration is estimated using the cyclomatic complexity and number of LoC impacted by the one or more cryptographic APIs.

The present disclosure relates to a method, device and system for automatic execution of an interactive interface based on interface context representation information. The method comprises: receiving an execution instruction for a target interactive interface; constructing and maintaining interface context representation information of the target interactive interface, the interface context representation information comprising page fingerprint information for representing interface state and operation history graph information for modeling inter-interface operation flow dependency relationship; determining a control strategy required for executing the execution instruction based on the interface context representation information and current interface state, the control strategy at least comprising a target interface element positioning strategy; and executing an automatic operation on the target interactive interface using the control strategy, and updating the operation history graph information and the page fingerprint information based on the operation result. The present disclosure can utilize context awareness capability and multi-level fault tolerance mechanism to realize adaptive repair of automatic operation when interface structure changes, thereby improving the robustness and maintenance efficiency of automatic execution.

A code management method is provided that includes receiving an input task description, decomposing the task description into a plurality of subtask descriptions, and generating code for a plurality of subtasks based on the plurality of subtask descriptions, where the code for the plurality of subtasks corresponds one-to-one to the plurality of subtask descriptions. A task is decomposed into a plurality of general-purpose tasks or atomic tasks (i.e., tasks that do not support further decomposition) by introducing decomposition of a task description to improve accuracy of code generation in a complex multi-step task, achieve a favorable code generation effect, and meet a service requirement.

This disclosure discloses devices and methods, media, equipment, and systems-on-chips for patching boot code. [Solution] The boot code patching device stores the boot code in a first memory and pre-configured patch data in a second memory. The processor reads and executes the boot code from the first memory, reads the patch data in response to execution to reach a first pre-configured instruction, sets a breakpoint in the boot code via a debug control path based on the patch data, continues executing the boot code, jumps to the patch code corresponding to the breakpoint in response to execution to reach any of the breakpoints in the boot code, jumps to the return address corresponding to the breakpoint in response to completion of execution of this patch code, and continues executing the boot code.

A computer-implemented method and system standardize code patterns within enterprise software environments. A code modernization system utilizes a Large Language Model (LLM) and a specialized prompt library. The library includes pattern recognition prompts to guide the LLM in identifying specific code patterns within selected software code, potentially using enterprise-specific context. It also includes standardized solution prompts to guide the LLM in generating replacement code conforming to predefined enterprise standards for the identified patterns. The system orchestrates communication, transmitting code and relevant prompts to the LLM and receiving identified patterns and subsequently the generated standardized replacement code. This automated approach facilitates improved code quality, consistency, maintainability, and can support code translation efforts within the enterprise.

This application provides a method and apparatus for generating code-based module design documents. The method includes: obtaining target code; deleting compiler directives and comments from the target code to obtain code text; identifying and extracting global variables and function structures from the code text; comparing the identifiers in each function structure in parallel with global variables, and comparing the identifiers before the left parenthesis in each function structure in parallel with the function names of other function structures, and associating the global variables and / or function names that match the comparison with the corresponding function structures, wherein the other function structures are the function structures outside the current function structure in each function structure; and generating and outputting a target module design document in a preset format based on each function structure and its associated global variables and / or function names. This achieves efficient and accurate generation of module design documents.

A method includes receiving, from a client device associated with an enterprise, information regarding software code, generating, via a large language model (LLM), a recommendation regarding the software code based on the information and a plurality of software library profiles, wherein each of the plurality of software library profiles is associated with a corresponding software library of a plurality of software libraries associated with the enterprise, and wherein each of the plurality of software library profiles indicates a corresponding key performance indicator (KPI) associated with usage of the corresponding software library, and providing, to the client device, the recommendation.

This invention discloses a Java code layout optimization method that does not interrupt application services. The method includes: acquiring front-end bottleneck data of the application; when it is determined that code layout optimization is needed based on the front-end bottleneck data, collecting the dynamic control flow graph of the application service; calculating a new code layout based on the dynamic control flow graph; generating new code according to the new code layout; correcting relocation information in all code, that is, redirecting function calls and data references pointing to the old code to the new code. During the correction process, memory barriers and cache maintenance instructions are used to ensure the atomicity and consistency of the modification operations, so as to achieve uninterrupted application services; only reclaiming the memory space used by the old code that is no longer executed to store the new code generated in the next optimization, retaining the function code still on the call stack, so that most of the memory space can be reclaimed without interrupting application services. This method effectively alleviates the processor front-end bottleneck of Java applications and improves application performance.

The application provides a software reconstruction method based on deep reinforcement learning, which monitors the software running process, analyzes the software running live from two aspects of the software itself and the hardware device where the software is located, judges whether each algorithm module of the algorithm architecture platform of the software is in a normal running state or not, and performs deep learning training and reconstruction on the algorithm of the corresponding algorithm module, so as to reduce the inspection workload of the software, and improve the reliability and accuracy of the overall correction and reconstruction of the software.

The application provides a ROM patching method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: patching a first to-be-modified function on a ROM by using a first method; the first to-be-modified function is located at an upper layer of a call tree; the first to-be-modified function is a function that needs to call a basic function; patching a second to-be-modified function on the ROM by using a second method; the first method and the second method are different; the second to-be-modified function is located at a bottom layer of the call tree; the second to-be-modified function is a basic function.

The embodiment of the specification discloses a SysML v2 model code AI generation control method, comprising: determining a target model for generating a SysML v2 model code from each candidate AI large language model, and establishing natural language information for describing a SysML v2 model modeling task; making each target model generate a SysML v2 model code according to the natural language information, and acquiring model codes output by each target model; after acquiring the model codes output by each target model each time, verifying whether the model codes acquired this time conform to specifications; if none of the model codes acquired this time conforms to the specifications, generating code correction guide information according to error conditions of the model codes acquired this time, and instructing each target model to generate new SysML v2 model codes according to the code correction guide information; if one or more model codes output by the target model in the model codes acquired at a certain time conform to the specifications, determining a target code corresponding to the SysML v2 model modeling task from the model codes conforming to the specifications.

This invention discloses a software development method and system, relating to the field of software engineering technology. After precise code modification based on anchoring relationships, this invention performs a dual verification process: syntax correctness verification and business logic consistency verification. Syntax verification ensures that the modified code snippets themselves have no compilation errors or syntax violations. Business logic consistency verification compares and analyzes the business intent defined by the changed requirement semantic unit with the logic implemented in the affected code area after modification. This ensures that the added and modified logic will not have implicit conflicts or contradictions with other existing business rules in the system that are not directly anchored by this change, guaranteeing code adaptation for each instance. The result is not only syntactically correct but also semantically compatible and logically self-consistent in complex business contexts. While supporting high-frequency, fine-grained requirement changes, it maintains the overall consistency of the codebase.

This specification provides a method for training a code processing model and a method for processing code tasks. The method for training the code processing model includes: obtaining multiple initial question-answer pairs, each corresponding to at least two code language types; using multiple target code models to perform cross-language knowledge transfer on the initial question-answer pairs to obtain target question-answer pairs, wherein the multiple target code models are trained on the initial code models based on the multiple initial question-answer pairs and the code language types, with a one-to-one correspondence between the target code models and the code language types; and training the initial processing model based on the multiple initial question-answer pairs and the target question-answer pairs to obtain a code processing model. By collaborating and sharing information among multiple target code models, cross-language knowledge transfer is performed on the initial question-answer pairs, thereby using the obtained target question-answer pairs to help the code processing model learn the commonalities and differences between different languages, improving the model performance of the code processing model.

The application discloses a kind of based on multi-layer graph embedding atomization component intelligent mapping and process reconstruction method, system, equipment and medium, belong to component reconstruction technical field, comprising: component feature matrix is constructed by multi-source feature extraction, and based on this, multi-layer dependency graph is established to learn component embedding representation;Similarity matching and mapping are carried out using embedding, and the mapping result is optimized in combination with dependency consistency constraint, and then the process dependency topology is constructed and optimized to eliminate redundancy and cycle;Adaptively update dependency graph by detecting historical changes, and introduce expert knowledge constraint to correct and jointly optimize the result, and feed back the revised knowledge to knowledge base.The application realizes unified modeling and deep fusion of component structure, semantics and execution layer dependency relationship by multi-layer graph embedding technology, improves the precision and panoramic understanding ability of component mapping;Ensure the timeliness and accuracy of mapping and reconstruction result.

The application provides a resource allocation method and system based on risk prediction and multi-agent cooperation, wherein when a user intention is captured through an interceptor, a user prompt and a code context related to the user prompt are collected, a composite metric index representing an architecture risk and an impact score is predicted based on the user prompt and the code context related to the user prompt, and a customized execution plan is actively constructed according to the composite metric index and the current user intention, so that the complexity and rigor of the execution plan are proportional to the risk level.

The application discloses a code processing method and device and related products, the method comprises the following steps: in response to the obtained code merging request, determining the target test case information based on the preset test mapping table; then, jointly compiling the target test code corresponding to the target test case information and the to-be-merged code to obtain a target binary file; further verifying the target test result to obtain a target verification result; if the execution success rate is greater than or equal to a first threshold value, and the code coverage rate is greater than or equal to a second threshold value, then allowing the to-be-merged code to merge the code corresponding to the target business module; if the execution success rate is less than the first threshold value, or the code coverage rate is less than the second threshold value, then rejecting the to-be-merged code to merge the target business module. In this way, the to-be-merged code is compiled, tested and verified according to the test granularity of the business module, the code quality during code merging is improved, and the entire test process is realized through automatic testing, thereby improving the test efficiency.