606results about "Reverse engineering" patented technology

The invention discloses an intelligent contract vulnerability detection and repair system based on a heterogeneous graph neural network, and belongs to the technical field of block chain security, and the system comprises a contract analysis module, a multilayer graph construction module, a heterogeneous graph neural network module, a vulnerability feature library, a vulnerability recognition engine, an automatic repair module and a visual interface. After the source code of the intelligent contract is input, code analysis and standardization are completed by a contract analysis module; the multi-layer graph construction module constructs a contract internal heterogeneous graph, an inter-contract interaction graph and an ecosystem relation graph based on a graph theory; the heterogeneous graph neural network module learns a vulnerability feature mode; the vulnerability recognition engine combines the vulnerability feature library to realize vulnerability classification and risk assessment; the automatic repairing module generates a repairing scheme; and the visual interface realizes detection progress monitoring, result display and encrypted report export. The intelligent contract vulnerability detection and restoration system based on the heterogeneous graph neural network provided by the invention provides technical support for block chain digital asset security and ecological stability.

The invention provides a code generation and evaluation method and system based on RAG and a multilevel decision tree, and the method comprises the steps: integrating project related design documents, and constructing a knowledge base capable of semantic retrieval through a vectorization technology; associating business demand description with related documents in the knowledge base based on an RAG technology, and performing demand semantic enhancement to generate a technology demand cue word; receiving the technical requirement cue word by adopting a large language model so as to generate a complete code conforming to business logic; constructing a four-level decision tree evaluation system, and sequentially executing code quality scanning, deployability verification, dynamic test verification and demand satisfaction verification through an evaluation assembly line to generate an evaluation result; and generating an optimization suggestion according to the evaluation result so as to trigger an iteration generation process when the code does not pass the verification, thereby solving the problems of disjunction between code generation and business requirements, low verification efficiency and insufficient iteration optimization.

The invention discloses a knowledge extraction and envelope coverage-oriented software vulnerability test method and related equipment, and the method comprises the steps: obtaining vulnerability key information of target software, and obtaining sensitive function features through defect dependence analysis and construction based on the vulnerability key information; performing semantic analysis on the analysis report and the code abstract associated with the sensitive function characteristics, screening to obtain a target sensitive function, performing path envelope reverse tracking on the target sensitive function, and constructing to obtain a target path envelope; and obtaining coverage information enveloped by the target path, and carrying out fuzzy testing on the basis of the coverage information in combination with the iteratively optimized variation sample. According to the method, through intelligent closed loop of analysis-positioning-testing-feedback-optimization, static analysis provides accurate guidance for dynamic testing, and the static analysis strategy is inversely optimized by the result of the dynamic testing, so that the maximum improvement of the testing efficiency and the vulnerability discovery accuracy is realized in limited testing resources, and the testing efficiency and the vulnerability discovery accuracy are improved. The method can be widely applied to the technical field of software security.

The invention provides a network security malicious code binary search method and system, and relates to the technical field of data processing, and the method comprises the steps: calculating the multi-dimensional structural similarity between a to-be-detected binary file and each standard binary reference file based on a function level control flow semantic feature vector; determining a finally matched standard binary reference file according to the multi-dimensional structural similarity; performing fine-grained difference analysis on the binary file to be detected and the finally matched standard binary reference file to obtain a fine-grained difference analysis result; and on the basis of a fine-grained difference analysis result, in combination with sensitive data operation behavior feature detection, judging whether the to-be-detected binary file is a maliciously tampered version, and positioning a malicious code injection point. According to the method, the defects that in the prior art, dependence on fixed features is too high, and compilation optimization is sensitive are overcome.

Techniques for natural language based chat are described. In some examples, a chat service receive a request to answer a natural language query (NLQ), generate one or more embedding vectors for the NLQ, performs a search of a vector database having information regarding one or more of enterprise context, natural language summaries of enterprise context, embedding vectors for the enterprise context, and embedding vectors for natural language summaries of the enterprise context according to the request to generate a search result, augmenting the NLQ using the search result, predicts a response for the NLQ using the search result augmented NLQ, and provides the predicted response in the chat.

The invention discloses an automatic compiling method and device for a test case, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: carrying out the structural analysis of a demand document for creative and creative transformation, and extracting the demand information of the demand document; the code warehouse is connected to obtain the source code and performs static analysis to generate code logic; establishing a semantic association mapping table of the demand information and the code logic, generating a test scene library according to the semantic association mapping table, and automatically generating a test case according to the parameter type and the constraint rule; and performing multi-dimensional verification on the generated test case to generate a verification result, and adjusting the priority of the test case according to the verification result. The method has the technical effects of improving marginal scene coverage depth and breadth, improving test case writing efficiency and accuracy, reducing manual dependence, and optimizing test case quality and execution pertinence.

The invention relates to the technical field of software engineering and information processing, in particular to a semantic verification method and device based on a large model.The method comprises the steps that a source code file and a corresponding software requirement and design document are obtained, code semantic representation is generated based on grammar analysis and static program analysis, and a semantic verification result is obtained; based on text analysis and business flow chart structure identification, generating a design demand semantic representation; respectively inputting the code semantic representation and the design demand semantic representation into a pre-training language large model to generate a code implementation logic description and a design demand logic description; and performing semantic consistency verification on the two types of logic descriptions to obtain a semantic inconsistency result, determining a code position in the source code file based on the semantic inconsistency result, and outputting a scanning report. According to the invention, the automation degree and the rechecking performance of consistency checking of requirements can be improved, and the leak detection and reworking cost can be reduced.

The invention provides an automatic vulnerability detection rule generation method based on LLM and static code analysis, and relates to the technical field of network security and software engineering. The method comprises the following steps of: constructing unified structured representation of project code semantics and vulnerability features, classifying taint'source 'and'sink' based on a heuristic rule and LLM (Logical Language Model), and constructing a taint propagation path assisted by a large language model and performing risk assessment; automatically generating a rule based on a'generation-verification-repair 'closed loop mechanism; according to the method, uniform structured representation of code side information and vulnerability side information is constructed, accurate identification of specific project taint sources and sinks and effective paths in multiple environments is achieved, a path risk sorting mechanism is introduced to achieve priority detection of high-risk paths, an automatic rule of error feedback circulation aiming at correction is established, and the accuracy of detection is improved. And the correctness and the performability of the rule grammar are greatly improved, and logic vulnerabilities are reduced, so that the manual debugging and maintenance cost is reduced.

The invention discloses a code similarity detection method and system based on a large language model, and the method comprises the steps: obtaining a to-be-detected source code pair, and marking the to-be-detected source code pair as a source code A and a source code B; performing code cleaning and format standardization on the source code A and the source code B, and mapping a variable name and a function name which are customized by a user into a uniform placeholder; analyzing the source codes A and B based on the abstract syntax tree, respectively replacing variable names and function names in the source codes A and B with unified serialized placeholders, and maintaining a mapping table; meanwhile, expanding a lexical dictionary of the pre-training large language model, and inserting a special identifier; splicing the replaced code snippets with special identifiers, and constructing a structure sensing input sequence; inputting the structure perception input sequence into a pre-trained large language model backbone network for feature coding to obtain a high-dimensional semantic feature vector containing global context information; connecting a multi-task prediction head behind the large language model backbone network, inputting the feature vector into the multi-task prediction head, outputting probability distribution of code clone types through a classification task head, and respectively outputting a row level similarity score and a lexical element level similarity score through a regression task head; and according to the classification probability and the regression score, performing comprehensive judgment by combining a preset threshold, and generating a detection report. According to the method, similar codes after variable renaming, statement rearrangement or control flow transformation can be accurately recognized, and the accuracy and robustness of code similarity detection are improved.

Various embodiments of the present disclosure include systems, methods, and / or apparatuses for executing an agentic-AI-based software modernization system. An example system may be configured to receive one or more portions of monolithic legacy code of a legacy software program product, the monolithic legacy code comprising a plurality of code segments, group the monolithic legacy code by functionally related code segments of the plurality of code segments to define a plurality of groups, generate an API for each identified group, generate modern microservice code for each identified group to define a modernized software program product, and validate the modernized software program product.

The invention discloses a de-signed binary code reverse analysis method based on library function matching. The method comprises the following steps of: obtaining de-signed binary codes and a candidate library file list thereof in the embedded equipment, and extracting a library function and information of each object file of each candidate library file; performing matching operation on each object file in sequence to establish a library function matching table; and acquiring addresses for calling other library functions in each library function, performing consistency comparison with the addresses of the successfully matched library functions, and confirming the calling relationship of the library functions, thereby determining the function of the de-signed binary code in the embedded equipment. According to the method, the library function in the de-signed binary code can be accurately identified, the calling relation is checked, and the method is suitable for component analysis and traceability of scenes such as computer programs, embedded firmware and DSP programs so as to accurately identify the function of the de-signed binary code in embedded equipment.

An impact analysis device acquires a list of method information related to a difference between a new version of a library and an old version of the library, based on a source code of the new version of the library and a source code of the old version of the library; extracts, from the list, a first difference related to a method existing in a first call graph of software that uses the old version of the library; extracts, from the list, a second difference related to a method added to a second call graph of the software that uses the new version of the library; extracts a set of method information of a caller of a transition added to the second call graph in comparison with the first call graph; and outputs a union of the first difference, the second difference, and the set, thereby enhancing support for determining a likelihood that a library update could affect operations of software.

The invention provides a large language model-assisted coding function bypassing input data automatic generation method, which comprises the following steps of: after compiling a source code of target binary software, extracting assembly fragments, input data parameters and data length parameter information corresponding to a coding and decoding function so as to construct a vector database; disassembling the target binary software, extracting a target function fragment, performing retrieval and recognition on the basis of a large language model and in combination with a vector database, and determining a coding / decoding function and parameter information in the target binary software; in the program execution process, after the related encoding / decoding function is executed, decoding or encoding is carried out according to the recognition result of the step S2, and the input data are compared to obtain the offset of the encoding / decoding data in the input data; when the program is executed to the analysis end point state, the expected data is mapped to the offset position corresponding to the input data based on the offset, and generation of new input data is completed.

One embodiment of a method for modifying program code includes processing, using a first trained language model, program code to identify one or more modifications to the program code; processing, using a second trained language model, the program code and the one or more modifications to generate a plan for applying the one or more modifications; and processing, using a third trained language model, the program code and the plan to generate a modified program code.

The invention discloses a method and a device for generating a software vulnerability analysis report, and relates to the field of information security. The method comprises the following steps: acquiring auditing information of software vulnerabilities; a code feature matching rule for the software vulnerability is generated according to the auditing information through the large language model, and the code feature matching rule is used for matching a code calling mode related to the software vulnerability in the target software project; constructing a calling graph of the target software project; according to the code feature matching rule and the call graph, the correlation degree between each code snippet of the target software project and the software vulnerability is detected, and the correlation degree is used for evaluating the risk level of each code snippet of the target software project; and generating a software vulnerability analysis report of the target software project according to the association degree between each code snippet of the target software project and the software vulnerability. The technical problem that in the prior art, an open source software vulnerability detection tool cannot accurately evaluate the real influence of vulnerabilities in specific project contexts is solved.

Systems and methods for uses and / or improvements to artificial intelligence applications, particularly in the realm of code development. As one example, systems are described herein for an artificial intelligence tool for software code development that estimates runtime processing efficiency of serverless applications as well as provide recommendations for more efficient code for the serverless applications.

A system and method for generating computer code are provided. The system receives data indicating a trigger event to initiate code generation and selects a code generation agent based on attributes of the trigger event. The selected agent requests indexed context information from a context indexing component. The context indexing component generates indexed context information including project data associated with a user account, such as existing code, text data, file structure data, open file information, and project documentation. First embeddings are generated from the processed project data and stored in a vector database configured to be queried by the code generation agent. The system can further generate environmental data, hierarchical file structure summarizations, and indexed external data, creating additional embeddings stored in the vector database to provide comprehensive context for code generation.

Predicting attack paths using code analysis, including: detecting a vulnerability in code by performing a static code analysis of the code; identifying an attack surface for the vulnerability in a cloud deployment; and generating an alert for the vulnerability by assigning a priority to the alert based on the attack surface.

In various examples, a technique for resolving a standards violation includes receiving a violation notification of a standards violation detected in a software codebase. The technique also includes determining additional information relevant to the standards violation and included in one or more information sources. The technique further includes generating a prompt based at least on the violation notification and the additional information, generating, using a machine learning model and based at least on the prompt, one or more corrective suggestions associated with the standards violation, and modifying the software codebase based at least on the one or more software code changes.

The invention discloses a code change generation method based on a multi-agent proxy library migration scene, which can accurately locate all code action ranges related to library migration in a file range by performing structured analysis on a source code file and combining source library import information and code feature recognition, and can improve the code change generation efficiency. The problems of omission and misjudgment caused by manual analysis or simple rule matching are avoided, and the integrity and accuracy of migration site recognition are improved. According to the method, the corresponding migration plan is generated by combining key information of the source library and the target library aiming at the identified action range to be migrated, so that the code change process is not limited to simple interface replacement any more, targeted adjustment can be performed according to a specific use scene, and the consistency of migrated codes in terms of semantics and behaviors is ensured. According to the method, through a collaborative code change generation and verification mechanism, the code change related to library migration is automatically generated and evaluated, and the reliability and availability of a generation result are improved while manual intervention is reduced.

The invention discloses a method for dynamically constructing a UDF based on a large model. The method comprises the following steps: S1, constructing a multi-dimensional requirement cue word of a user-defined function according to characteristics and use requirements of a target platform; s2, the multi-dimensional requirement cue words are input into a pre-trained large language model for code generation, the large language model is subjected to multi-round iteration based on the multi-dimensional requirement cue words, and an optimal code sequence for achieving the user-defined function is output; s3, code style standardization is carried out on the optimal code sequence, and a compiler or an interpreter and a static analysis tool are respectively called to carry out grammar check and static analysis on the optimal code sequence, and constructing an optimization cue word according to an error log output by the compiler or the interpreter and a static analysis result output by the static analysis tool, and inputting the optimization cue word into the large language model to carry out iterative optimization on the optimal code sequence.

A computer-implemented system analyzes program and data flows in a software system comprising code written in multiple programming languages using a generative large language model (LLM) directed by programming-language-specific prompts. The LLM identifies functional components within the code, generating labeled graph nodes that include a node type, a node name, and dependency information. A graph construction computer system processes the labeled graph nodes to generate a directed graph, where nodes represent functional components and directed edges represent dependencies. The system stores the graph in a database and provides a web-based interface for visualization, allowing users to explore, query, and analyze program and data flows across the software system. The system enables automated, language-agnostic dependency mapping, facilitating software analysis, debugging, and modernization.

A system includes a processor that is configured to acquire source code, analyze the acquired source code and extract operational functions and error conditions, automatically generate a user manual and FAQ in natural language based on the generated data, automatically generate images and videos of operation procedures as rich content, and integrate and distribute the generated content via a management system.

The invention relates to the technical field of artificial intelligence, in particular to an ST-language-oriented assistant system and method, electronic equipment and a storage medium, and the method comprises the steps: constructing an ST-language-oriented intelligent programming system through the cooperative work of a data processing module, a model training module, a deployment integration module and a data production module; firstly, multi-source industrial ST data is processed to construct a training sample, then a special large language model is obtained through continuous pre-training and supervised fine tuning, finally, the model is integrated into a development environment to provide the functions of code completion, question and answer interaction and the like, and a closed-loop optimization mechanism is formed by collecting user interaction and model generation data. According to the method, a closed-loop system integrating four modules is constructed, deep compatibility and local security deployment of ST grammar specifications of multiple manufacturers are achieved, the code generation accuracy and development efficiency of industrial ST programming are improved, and meanwhile the system has the continuous self-adaptive optimization capacity by means of a data driving mechanism.

Presented herein are systems and methods for optimizing legacy source code using generative models. A computing system may generate, for each function of a plurality of functions of a software program, a performance profile comprising a performance attribute during runtime. The computing system may identify, from the plurality of functions of the software program, a function based on the performance attribute of the performance profile for the function being lower than a threshold. The computing system may select first source code of the function for refactoring, responsive to identifying the function. The computing system may provide the first source code of the function to a generative model to determine refactoring opportunities within the first source code. The computing system may generate, based on providing the first source code to the generative model, second source code for the function corresponding to the refactoring opportunities within the first source code.

The invention provides an interface change risk management and control method and device based on multi-source evidence fusion, and the method comprises the steps: carrying out the standardization processing of interface call data from various heterogeneous evidence sources, and generating a unified endpoint set and a call relation set; fusing the multi-source data pointing to the same calling relationship to calculate the confidence of the multi-source data, and constructing a service dependency topological graph based on a high-confidence relationship; when an interface change is detected, analyzing an influence range of the change in the topological graph, quantitatively calculating an influence surface score, and dynamically judging a risk level; and implementing corresponding automatic management and control actions in the continuous integration / continuous delivery process according to the risk levels. According to the method and the device, the problem of frequent interface change online faults caused by inaccurate dependence identification, inaccurate change influence evaluation and risk management and control lagging can be solved, the risk discovery and management and control of interface definition destructive change can be advanced from online to before-online, and the online fault rate is further remarkably reduced.

The invention provides a program data query method which can be applied to the technical field of financial science and technology. The program data query method comprises the following steps: in response to an input operation in an input box of a program data query client, obtaining index content in the input box; according to the index content, a program list and a relation list in a pre-constructed program data query database are called, the program list comprises m programs, program types corresponding to the m programs and program attributes corresponding to the m programs, the relation list comprises program relations among the m programs and attributes of the program relations, m is an integer larger than or equal to 10, and the m is an integer larger than or equal to 10; the program data query database comprises a mapping relation among the index content, the program list and the relation list; and in response to a click on a download button of the program data query client, sending the program list and the relationship list to the program data query client. The invention further provides a program data query device and equipment, a storage medium and a program product.

The invention provides a display control method and a generation method of programming simulation operation questions and a related product, and relates to the technical field of programming education. The programming simulation run question comprises question codes and questions corresponding to code blocks needing to be investigated in the question codes. The code blocks needing to be investigated are code blocks generating actual operation in the title codes. When the program simulation operation question is used, all code blocks of the question codes are displayed, all the code blocks are sequentially triggered according to the operation logic of the question codes, under the condition that the currently-triggered code blocks are code blocks which are provided with the questions and need to be investigated, the questions are displayed, and after the questions are answered, the next-generation code blocks of the currently-triggered code blocks are allowed to be triggered. According to the method, the understanding difficulty of a user on the change condition of variable and other difficult contents related to actual operation in the whole code running process can be reduced.

Systems, methods, and a computer readable storage medium are disclosed for submission of a software application to one or more application stores. The method includes receiving one or more inputs from a user and determining requirements to submit the software application to the one or more application stores based on the received one or more inputs. The method further includes generating metadata for the software application based on the determined requirements and submitting the software application to the one or more application stores based on the generated metadata.

The application is applied to the field of architecture anti-corrosion technology, and discloses a method, device and equipment for preventing and controlling system architecture corruption, and a storage medium. The method comprises the following steps: acquiring a visual architecture topology graph; the visual architecture topology graph is drawn through a preset graphical editor; the visual architecture topology graph is a logical topology graph corresponding to a distributed application system; acquiring architecture model data based on the visual architecture topology graph; generating rule data corresponding to the distributed application system based on the architecture model data; and performing rule monitoring on business code by using the rule data to determine whether the business code meets the rule data. In this way, the automatic and comprehensive review of the business code is realized by the rule data generated by the architecture model data corresponding to the visual architecture topology graph without depending on the ability of an architect, thereby improving the anti-corrosion effect of the system architecture.