13 results about "Reference software" patented technology

The invention provides a website detection method and device and electronic equipment, and relates to the technical field of artificial intelligence, in particular to the technical fields of artificial intelligence, intelligent search, large models and the like. According to the specific implementation scheme, a software library is determined, the software library comprises reference software with software downloading data larger than set software downloading data, combination is carried out according to the reference software and set search terms, at least one to-be-detected sample is determined, and the to-be-detected sample at least comprises a to-be-detected website; according to the to-be-detected sample, obtaining a reference example sample during large model reasoning; a detection result of the to-be-detected sample is determined through a large model according to the to-be-detected sample and the example sample, and the detection result is used for indicating whether the to-be-detected website is a counterfeit website or not.

The invention discloses a system deployment method and device and a storage medium. The method comprises the following steps: determining a target system to be deployed and a target server to which the target system is to be deployed; benchmark information of a benchmark server is obtained, a target system is deployed on the benchmark server, and the benchmark information comprises benchmark software and hardware information and benchmark configuration information; target information of a target server is obtained, and the target information comprises target software and hardware information; determining target configuration information of the target server according to the reference software and hardware information, the reference configuration information and the target software and hardware information; and deploying the target system on the target server according to the target configuration information. Through the method and the device, the problem that the deployment efficiency of the target system is low due to the fact that the number of the working processes which should be started when the target system is deployed on the target server depends on manual adjustment in the related technology is solved.

The invention belongs to the technical field of computer software engineering, and relates to a software demand intelligent analysis and prediction method and system, and the method comprises the following steps: obtaining a user operation log of target software, and constructing dynamic task chain data reflecting the actual process of a user based on a continuous operation sequence in the user operation log; associating a behavior pattern recorded in the dynamic task chain data with a feedback text submitted by a user, performing cross validation on the feedback text, and generating a credibility score representing the authenticity of the feedback text; the potential demand value is evaluated by combining high-credibility feedback and dynamic task chain data screened out through credibility scoring; performing constraint optimization according to preset development resource evaluation data to obtain a function combination after constraint optimization; according to the method, the problem that when the reference software and the target software have a large difference in function positioning or user groups, the built function model can generate dislocation, and large deviation occurs in analysis of user behaviors is solved.

This paper proposes a low-complexity, hardware-friendly technique for video decoding systems to mitigate striping artifacts while maintaining compression efficiency. Generally, the proposed technique consists of two stages: a striping detection stage and a destripping stage. The striping detection stage identifies potential striping artifact regions in the image / video based on gradient information and other data. The destripping stage applies correction techniques to these identified regions. In one implementation, the destripping modifies the filtering logic proposed by previous video decoding standards for other filtering applications to mitigate striping. When implemented on the AVI video decoding standard and the AOM Video Model (AVM) reference software, the proposed technique significantly improves subjective quality at a reasonable hardware implementation cost. The methods and implementations presented in this document can be beneficially applied to various image / video decoding standards and systems.

The application relates to the technical field of software cost evaluation, and discloses a software cost evaluation method based on function point analysis, which comprises the following steps: performing semantic analysis on software function requirement text to obtain software function points; performing similarity measurement on the software function points and software function question and answer description data; selecting question and answer description data with the highest similarity as the basis for function point complexity rating of the software function points; and performing complexity rating on the software function points and software cost evaluation. In the application, software function words are selected in combination with neighborhood knowledge graph and semantic similarity analysis, software functions are described, question and answer description data of the software function words are obtained in combination with software function question and answer description data, various complexities are extracted from the question and answer description data to perform complexity rating on the software function points, a cost adjustment factor is set by referring to a software cost evaluation standard, and the complexity rating result is subjected to software cost evaluation based on software function point analysis in combination with the cost adjustment factor.

The invention provides a software asset analysis method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of big data and the technical field of artificial intelligence. The method comprises the steps of obtaining a target event; determining at least one target analysis dimension and a corresponding affected data range based on the target event and preset event rule information; according to the affected data range, incremental updating is conducted on a dynamic topological graph, an updated topological graph is obtained, and the dynamic topological graph represents the relation between software assets and corresponding associated entities; performing incremental aggregation calculation on the reference software asset analysis result of the target analysis dimension based on the updated topological graph to obtain an updated software asset analysis result; and generating a software asset analysis result for target software based on the updated software asset analysis result.

The application discloses an OPC software verification method, an OPC software verification device, an electronic device and a storage medium. The method comprises the following steps: obtaining first data, wherein the first data comprises data for establishing an OPC model and a test layout; obtaining reference data and a reference correction program corresponding to reference OPC software and verification data and a verification correction program corresponding to to-be-verified OPC software according to the first data, the reference OPC software and the to-be-verified OPC software; and evaluating a verification result of the to-be-verified OPC software according to the reference data and the reference correction program, the verification data and the verification correction program and a preset evaluation threshold. The application introduces the reference OPC software as a verification standard for verifying the to-be-verified OPC software, so that actual feature sizes can be collected without actual exposure of a photomask when the OPC software is verified, and the verification cost can be effectively reduced. Meanwhile, the OPC software can be verified in advance when the OPC software is verified, and the verification time can be greatly reduced.

This invention discloses a dynamic user profile update method based on multimodal data, relating to the field of user modeling technology. The method includes: acquiring the collaborative analysis software of each software in the user's device; obtaining the association weight based on the association filtering value of the collaborative analysis software; acquiring status update words and updating the user's profile based on the collaborative analysis software of the updated reference software and the association weight of the collaborative analysis software. This invention addresses the problem in existing dynamic user profile update methods that lack analysis of multimodal data generated by users based on user software usage data. This results in the inability to effectively acquire dynamic profile data related to the user's immediate interests and needs, leading to inaccurate user profiles and a loss of dynamism after data processing.

The invention discloses a task load determination method and device, equipment, a medium and a program product, and relates to the technical field of computers. Comprising the steps that first item information of first software is obtained, and the first item information comprises information used for describing the first software needed in the software life cycle; processing the first project information according to the reference software project basic information, the reference software transformation details and the preprocessing information to obtain a software project basic information table and a software transformation detail and preprocessing table comprising M to-be-processed records, and the to-be-processed records are records of tasks of which the task load is to be determined in the first software; and determining the task load of the ith to-be-processed record according to the ith to-be-processed record in the M to-be-processed records and the basic information corresponding to the ith to-be-processed record in the software project basic information table. Therefore, manual participation is not needed, the task load of each task in the first software can be quickly and accurately determined, and the accuracy and efficiency of determining the task load of the software are improved.

The application discloses a software defect repair information determination method and device and electronic equipment, and is applied to the fields of artificial intelligence technology and intelligent automobile technology. The method comprises the following steps: obtaining software defect information, wherein the software defect information comprises an error log and software defect code information corresponding to the error log; screening reference software defect repair information related to the software defect information from a software defect repair information set according to the similarity value of the error log and each software defect repair information in the software defect repair information set; and determining defect repair information for the software defect code information according to the similarity value of the error log and the reference software defect repair information and the reference software defect repair information. The method screens the reference software defect repair information based on the similarity, and generates adaptive defect repair information accordingly, thereby reducing the dependence on manual work and improving the accuracy of software defect repair.

Low complexity, hardware-friendly techniques are proposed for video coding systems to mitigate banding artifacts while maintaining the compression efficiency. In general, the proposed techniques consist of two stages including a banding detection stage and a de-banding stage. The banding detection stage may identify the image / video regions where the banding artifact may be present based on gradient information and other information. The de-banding stage may apply corrective techniques to regions identified as likely to possess banding artifacts. In one embodiment, the de-banding adapts the filtering logic proposed by prior video coding standards for other filtering applications to mitigate banding. When implemented over the AV1 video coding standard and the AOM Video Model (AVM) reference software, the proposed technique improves subjective quality significantly at a reasonable hardware implementation cost. The methods and embodiments presented in this document can be beneficial find application in a wide variety of image / video coding standards and systems.

An adaptive quality assessor assesses quality of source code, taking into account feedback from software engineers. A modification to source code of a software system is detected. A plurality of metrics are selected from source code metrics available for the source code, the selection being at least in response to feedback about the modification to the source code. A score is computed comprising a weighted combination of the selected plurality of metrics. An automated action on a consuming process is triggered in response to the computed score, such as to control integration of the modified source code into the software system or to prioritize tasks in a queue.

The invention discloses a software defect prediction method, a related device, equipment and a storage medium, and the method comprises the steps: extracting a first feature set of reference software based on a program code of the reference software; wherein the first feature set comprises code feature representations of the reference software about a plurality of preset feature categories; based on the first feature set of the reference software, measuring to obtain information entropies of a plurality of preset feature categories in the reference software; based on the information entropies of the same preset feature category in different reference software, determining to obtain a weight factor corresponding to the preset feature category; on the basis of a second feature set extracted from the program code of the to-be-detected software, predicting to obtain a defect detection result of the to-be-detected software; wherein the second feature set comprises code feature representations of the to-be-tested software about a plurality of preset feature categories and weight factors of the code feature representations. According to the scheme, the objectivity of feature selection can be improved, so that the accuracy and generalization ability of software defect prediction are improved.