49 results about "Test document" patented technology

The embodiment of the invention discloses a test case generation method and device based on a service scene and related equipment. The method comprises the following steps: acquiring historical test data, and identifying and extracting entities and corresponding entity relationships in the historical test data through a pre-trained identification model; according to the entities and the corresponding entity relationships, storage is carried out in a triple form, and a test knowledge graph is constructed; analyzing based on the test document of the current test item, and determining the test requirement and the test item of the test document; based on the test requirements and the test items, matching corresponding standard triads and reference test cases from the knowledge graph and a preset test case library to obtain a target triad set and a target reference case; and generating a target cue word based on the test requirement, the test item, the target triple set and the target reference case, and generating a target test case through a pre-trained large language model. According to the method, the scene coverage of the test case is higher, and the logic continuity of the test case is improved.

The invention relates to a vehicle test field knowledge graph construction method and system based on global semantic driving. The method comprises the following steps: extracting a vehicle test PDF document table and a table associated text; outputting a table image in which the complete two-dimensional layout is reserved; inputting the table image into a multi-modal large model, and generating global semantic description containing a table business theme and a row-column logic relationship; performing topic clustering on the global semantic description, identifying representative entities under each topic, and screening out entities with moderate granularity and high relevancy as seed entities; extracting candidate knowledge triples from a vehicle test PDF document by taking the seed entity as guidance and combining the table image and the global semantic description; and performing global knowledge fusion on the candidate knowledge triples to form a global consistent knowledge graph. According to the method, the problems of table logic breakage, entity omission and relation generalization during vehicle test document processing in the prior art can be effectively solved.

The invention discloses a chip test retrieval method and system based on a large model, and the method comprises the following steps: collecting chip test documents, and constructing a chip test vector knowledge base; receiving user query, and executing search in the knowledge base by using the word vector model structure; richer context information is generated based on a retrieval result and user query, and a test case or a test analysis report is generated through a fine-tuned large model. According to the method, the retrieval capability and the generation capability are effectively integrated, efficient retrieval of test instructions and knowledge and automatic generation of test cases / reports are achieved, and the chip test efficiency and quality are remarkably improved. Meanwhile, the retrieval generation system adopts a Django framework development platform, performs real-time streaming output and real-time feedback of retrieval results by means of the MyWebsocket technology, and writes question and answer data into MySQL. The system comprises a knowledge base construction module, a retrieval module, a generation module, a streaming interaction module and a data storage module. Compared with the prior art, the method has the advantages that the test instruction retrieval accuracy is improved by more than 18%, the test case generation time is shortened by 60%, and the test knowledge is shared and reused.

The disclosure includes a system and method to obtain at least one image of a document under test, wherein valid instances of the document under test include at least one perforation-based three-dimensional security feature; obtain a first image snippet from the document under test, the first image snippet corresponding to at least a first portion of the perforation-based three-dimensional security feature present in the valid instances of the document; analyze the perforation-based three-dimensional security feature for one or more characteristics; and modify a likelihood that the document under test is accepted as valid, or rejected as invalid, based on a presence, or an absence, of the one or more characteristics.

The invention discloses an automatic testing system and method for a modular interface, and relates to the technical field of interface testing, and the system comprises an interface analysis module which is used for loading a to-be-analyzed interface document and extracting interface basic information from the to-be-analyzed interface document; the test case generation module is used for generating test cases of normal and abnormal scenes based on the interface basic information and a preset case template; the interface information comparison module is used for automatically detecting updating of an interface document, positioning changed content and synchronously updating a test case before the test is executed; the test execution module is used for executing an interface test by calling a test tool or a built-in Selenium interface automation framework; the test data analysis module is used for collecting test data generated in a test process in real time, and calling AI model analysis to quickly position an interface error reason; and the test document output module is used for summarizing the test data and the AI analysis result and generating a test report in multiple dimensions. According to the invention, the test and maintenance work of various interfaces can be rapidly and accurately completed.

The invention discloses an aerospace field test case generation method based on a knowledge graph. The method comprises the following steps: establishing a test field knowledge graph model comprising four layers of entities, namely a test item, a test case, a test process and a problem list; identifying test entities from a historical test document, and establishing inclusion, execution, generation and association relationships among the entities; filling the identified entities and relationships into the knowledge graph model to construct a knowledge graph, and optimizing the constructed knowledge graph; based on an input test item of a to-be-tested item, recommending a most relevant test case entity and a relevant test process and question list information thereof in the constructed and optimized knowledge graph; and inputting the recommended test case, test process and question list information into the large model to generate a structured test case text conforming to a project language style and a test environment. The invention aims to solve the problems of insufficient structuralization, weak reasoning ability and poor dynamic adaptability of the existing test case generation.

The invention relates to the technical field of data processing, in particular to an automatic test report generation method and device, equipment, a medium and a programmer.The method comprises the steps that a test standard, a test image and a test document of a target test are obtained; extracting test data in the test image and the test document by using an optical character recognition technology; analyzing the test data based on the test standard to obtain a test conclusion of the target test, and calling a target report template according to the type of the test conclusion; and generating a test report according to the test data, the test conclusion and the target report template. Therefore, the problem that the working efficiency is low due to the fact that the test data and the test report are edited manually in the related technology is solved.

The invention relates to a software testing method and device, computer equipment, a readable storage medium and a program product. The method comprises the steps of obtaining a deep learning model based on a multi-stage training strategy, wherein the deep learning model is used for performing mapping test on a source code file and a demand design document; obtaining a multi-task model based on the deep learning model, wherein the multi-task model is used for performing a mapping test on the demand design document and the test document; based on a relation extraction model, optimizing the test document; the optimization at least comprises enhancement of semantic association between entities. By adopting the method, the software testing quality can be improved.

The invention relates to the technical field of electromagnetic compatibility testing, in particular to a test document automatic generation method based on intelligent plan making. The method comprises the following steps: firstly, locking an effective standard based on environment-standard capability mapping, and triggering cascade constraints to determine a to-be-tested sample and a working mode; then analyzing a script to construct a parameter vector, and executing multi-dimensional Cartesian product operation; in the test data generation process, frequency parameters are extracted to serve as dynamic index keys, real-time retrieval is conducted, standard limit value constraints are injected, and a structured object list with embedded criteria is generated; and finally, positioning to a project XML document tree, serializing and injecting the data, driving a document object model to perform row-level style cloning and data filling by utilizing structured data, and associating resources to generate a persistent file. According to the method, full-coverage generation of the test data and automatic closed-loop of the criterion are realized, the problem of self-adaptive rendering of the variable-length data in a strict-format template is solved, and the completeness and normalization of document generation are improved.

The application belongs to the field of trusted software security testing, and discloses a putty trusted software testing method and system based on Python. The application replaces traditional manual operation with an automatic control mode taking Python as the core, so that the full test process of the SIS (Supervisory Information System) safety and trusted infrastructure can be quickly carried out after the version is released. The application automatically processes test case analysis, command execution, output collection, matching judgment, screenshot recording and report generation, thereby avoiding the cumbersome process of manually executing test instructions, manually comparing outputs, manually taking screenshots and manually arranging test documents.

The invention provides an embedded software automatic testing method and system based on a model, and relates to the technical field of embedded software testing. The method comprises the steps of obtaining a software demand design project, obtaining a software interface design project, constructing a software test model, automatically decomposing the test model, automatically generating test data, automatically generating a test script, automatically performing test execution and automatically generating a test document. The system comprises a software requirement design engineering analysis module, a software interface design engineering analysis module, a software test model generation module, a test model automatic decomposition module, a test data automatic generation module, a test script automatic generation module, a test execution module and a test document generation module. According to the method, demand design, interface design and a software test platform are integrated together, resources are shared, integrated management of software design and software test is achieved, and the efficiency and quality of software test demand analysis are improved.

This invention provides a method for automatically generating test cases based on SysML state machine diagrams, comprising the following steps: S1, SysML state machine diagram parsing; S2, model conversion, converting the SysML state machine diagram into an intermediate model that is easy to analyze; S3, test path generation; S4, test data and test case generation; S5, test document generation. This invention also provides a readable storage medium. The beneficial effects of this invention are: it provides a method for automatically generating test cases based on SysML state machine diagrams, which can discover potential problems as early as possible in the development process, improve testing efficiency, reduce testing time and cost, and better meet the sufficiency requirements of testing.

The invention relates to the field of computers, in particular to a test document generation method and device based on FPGA software testing. The method comprises the following steps: displaying an input interface; the input interface is used for prompting a user to input the test content corresponding to the FPGA software test; in the input interface, receiving a first user operation used for inputting first test content; according to the first test content, generating a target test document conforming to a preset document template; the target test document comprises at least one of a test plan used for describing the test content of the FPGA software test or a test report used for describing the test result of the FPGA software test.

This invention relates to a method and system for constructing a knowledge graph based on software testing, belonging to the field of knowledge graph technology. It solves the problems of low reusability and inability to intelligently store software test documents in existing technologies. The method includes: preprocessing and segmenting the received software test documents; updating the multi-level thesaurus with new terms based on the segmentation results; and updating IDF model files for various research directions based on the segmentation results and the research direction to which the document belongs. The method also involves parsing the preprocessed documents to obtain basic data; periodically extracting knowledge entities and their attributes based on the basic data, and establishing the relationships between knowledge entities, their attributes, and the relationships between them; extracting keywords from the attributes of knowledge entities based on the multi-level thesaurus and the IDF model files for various research directions, establishing keyword entities and the relationships between keyword entities and knowledge entities, and obtaining a knowledge graph. This achieves intelligent storage and retrieval of test knowledge, improving the overall utilization rate of data.

The application discloses a kind of keyword-driven spaceflight TT&C software automation test method and system, method includes: based on the formation keyword of spaceflight TT&C software operation process;Spaceflight TT&C software operation process uses multiple programming languages;Keyword uses uniform programming language;Configuration test case template, template element is defined based on test case template and forms test case;Wherein, at least one of natural language, keyword and test data defines template element;According to the attribute of test type, filter test case and pack the test case filtered into test suite;Execute test case in test suite and collect execution, according to mapping rule, fill execution into corresponding test document template to form test document.The application can complete multiple complex spaceflight TT&C software test by the keyword and test case design compatible with multiple programming languages, realize that test script writing language is uniform and forms general operation to multiple spaceflight TT&C software.

The invention discloses an engineering FPGA automatic simulation test system and method based on an RAG enhanced large language model, and relates to the field of FPGA test and verification, and the system comprises a system input processing module which is used for carrying out the preprocessing of a received technical document and a to-be-tested piece source code, and carrying out the verification of the received technical document and the to-be-tested piece source code; the document analysis LLM enhancement module analyzes the preprocessed technical document based on a large language model; the code analysis LLM enhancement module analyzes the preprocessed source code of the to-be-tested piece based on a large language model; the fusion module is used for fusing the document analysis result, the code analysis result and the to-be-tested piece source code to obtain a fused prompt word; a test incentive generation LLM enhancement module generates multiple groups of test incentives according to the fused cue words; and the simulation module obtains the optimal excitation from the multiple groups of test excitation, calls the FPGA simulation test tool, tests the optimal excitation, obtains a test conclusion and a test document, and outputs the optimal excitation, the test conclusion and the test document. The accuracy of the test result and the test efficiency can be improved.

The invention provides a full-link automatic collection method for test requirements, cases and scripts in an HIL test, and the method specifically comprises the following steps: (1) extracting the test requirements and the test cases from a structured test requirement and test case text, and matching corresponding test scripts from vTESTstudio; and (2) establishing a mapping relationship among the test requirements, the test cases and the test scripts, and completing automatic collection of the test requirements, the test cases and the script data. By quickly and efficiently extracting test requirements and test cases of PDF test documents and Excel test files, automatically analyzing vTESTstudio script data and automatically establishing accurate association among the PDF test documents, the Excel test files and the vTESTstudio script data, test asset management efficiency is remarkably improved, a traceable and reusable structured test asset library is finally constructed, and meanwhile high-quality structured data is provided for AI training.

The invention belongs to the technical field of artificial intelligence and aviation engineering crossing, and provides an aero-engine test document automatic generation method and system based on demand analysis. Segmenting the test technical requirement document by adopting a hybrid text segmentation algorithm based on semantic vector similarity, and constructing a bimodal storage structure; high-precision fusion of multiple paths of retrieval results is realized by utilizing a reciprocal ranking fusion algorithm and a weighted reciprocal ranking fusion algorithm, and a high-correlation context is extracted; structured test points are automatically analyzed and generated based on a fine-tuning large model, and multi-target task grouping is carried out in combination with test rules such as a safety envelope, positive and negative temperature isolation and single-day duration; and checking and outputting compliance test task groups through a rule-driven post-processing mechanism. According to the method, the production scheduling efficiency and the resource utilization rate are remarkably improved, dynamic adjustment is supported, and the method is suitable for multi-equipment and high-complexity aero-engine test scenes.

The invention relates to the technical field of automatic testing, and discloses a vehicle-mounted voice testing method and device, a vehicle and a medium, and the method comprises the steps: obtaining a corpus test set, each corpus in the corpus test set being generated based on a preset rule, and each corpus being correspondingly provided with an expected field and an expected intention; analyzing the corpus test set, and generating a test document containing a plurality of corpora and corresponding expected fields and expected intentions thereof; determining a target NLU engine of each corpus according to the test document, and performing semantic recognition on the corresponding corpus in the test document by using the target NLU engine to obtain a target semantic result containing a plurality of corpora and corresponding actual measurement fields and actual measurement intentions thereof; comparing the actual measurement field and the actual measurement intention of each corpus in the target semantic result with the expected field and the expected intention of the corresponding corpus in the corpus test set to obtain a semantic judgment result; and the test report is generated based on the test document, the target semantic result and the semantic judgment result, so that the test cost, efficiency and quality can be remarkably improved.

The invention discloses a cross-language knowledge transfer and expression consistency evaluation method for a large-scale language model. The method comprises the following steps: 1) selecting m test questions, and translating each selected test question into n different target language questions; 2) sending n different target language questions corresponding to the same test question to the target model, and recording an answer corresponding to each target language question; 3) evaluating the answer consistency of answers in different languages of the target model based on the answers; 4) constructing a plurality of test documents containing the setting information, and creating a query question for each test document according to the setting information; then translating each test document and the corresponding query question into a plurality of different target languages; 5) generating a plurality of pieces of query information for each test document and the corresponding query problem; 6) inputting each piece of query information into the target model, and storing each piece of query information-response pair; and 7) evaluating the cross-language knowledge transmission capability of the target model according to each query information-response.

The invention discloses a test document generation system and a test document generation method, which are used for automatically generating an office document with a certain format requirement in a man-machine collaboration mode according to structured data required by a software test process and recorded by a management software database and test process data set information manually edited and stored in a disk. Collaborative operation of software structured data generation and manual document modification is achieved, and it is ensured that content and typesetting do not interfere with each other; through collaborative operation, non-interference, repeated modification of support and automatic templating of fragments, the document editing and generating efficiency can be greatly improved, and repeated work is reduced; the same document is supported to be repeatedly modified by software tools and manual work, and the modified contents of the software tools and the manual work do not cover each other; the modification authority of a software tool to the document area can be flexibly switched at any time, and the automation authority of the document area can be manually controlled; and the complexity of manual document editing operation is reduced.

The invention relates to the technical field of software testing, in particular to an intelligent generation method and system for a software testing scheme based on a generative large model, and the method comprises the steps: obtaining the testing information of to-be-tested software; establishing a software test relation model according to the historical test document, and storing the software test relation model into a historical scheme database; obtaining recommendation information according to a historical scheme database and the test information of the to-be-tested software; and obtaining a to-be-tested software test scheme according to the recommendation information and the generative large model. According to the embodiment of the invention, by forming the structured historical test scheme and the'software demand-test item-test case 'relation model, the thought of hierarchical pre-recommendation of the test scheme is proposed, the understanding and reasoning ability of a large model for background knowledge is effectively improved, AI hallucination output is greatly reduced, and the quality of the generated test scheme is further guaranteed.

The invention discloses a test case generation method and device, a medium and a product, relates to the technical field of software testing and data processing, and can be applied to the technical field of financial science and technology. The method comprises the following steps: receiving and analyzing a to-be-tested document uploaded by a user to obtain a function modification point; based on the function modification point, determining an influence function node corresponding to the function modification point from a business knowledge graph, and generating a target test demand; generating a basic test case for the target test demand based on a case generation model; the basic test case comprises basic test logic; and generating a target test case according to the basic test logic and the target format template. Through the technical scheme, the case generation quality can be improved.

The application relates to a software testing method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: obtaining a deep learning model based on a multi-stage training strategy, the deep learning model being used for mapping test of a source code file and a requirement design document; obtaining a multi-task model based on the deep learning model, the multi-task model being used for mapping test of the requirement design document and a test document; and optimizing the test document based on a relationship extraction model, wherein the optimization at least comprises enhancing semantic association between entities. The method can improve the software testing quality.

The application provides a test document detection method and device, electronic equipment and a computer readable storage medium. The method comprises: obtaining a document to be detected; analyzing the document by a large language model to obtain semantic information of the document; constructing a knowledge graph according to the semantic information; and determining a detection result of the document based on a preset rule set, the semantic information and the knowledge graph. The application deepens the examination level and improves the logical examination ability. Furthermore, the application can realize multi-dimensional document examination based on the rule set, finally realizes an efficient, transparent and interpretable test document examination scheme, and improves the overall examination quality.

A secure document collection and storage container includes an opening positioned at or below a top edge of the front facet, and above a midpoint of the front facet. The facets form a chamber. The opening is sized to receive ballots or test documents into the container. A sealing material is placed over the guide markings after the documents are in the chamber.

The application discloses a chip back appearance detection method and device based on file filing, and the method comprises the following steps: obtaining an electrical test document of a product to be tested, establishing a standard filing file of the product to be tested according to the electrical test document, and the number and distribution of the dies, the size and position of the mask in the standard filing file are consistent with the electrical test document; after the back appearance detection scanning of the product to be tested is completed, a corresponding scanning result file is generated, the scanning result file and the standard filing file are simulated to file, and the size and position of the mask empty area after the simulation are calculated; whether the size and position of the mask empty area after the simulation change is judged, and when the size and position of the mask empty area do not change, it is determined that the back appearance detection of the product to be tested is qualified. The application solves the problem that the cost is increased due to the fact that whether the chip back appearance detection is qualified cannot be found in time in the prior art.

The application relates to the technical field of large models, in particular to a document understanding large model optimization method based on model failure analysis, which comprises the following steps: obtaining a to-be-optimized large language model, an initial test document set corresponding to the to-be-optimized large language model and an optimization application model corresponding to the to-be-optimized large language model; obtaining an initial failure document set corresponding to the to-be-optimized large language model according to the to-be-optimized large language model, the initial test document set and the optimization application model; generating target instructions corresponding to the to-be-optimized large language model according to the to-be-optimized large language model and the initial failure data set; generating target fine-tuning data corresponding to the to-be-optimized large language model according to the target instructions; and performing optimization processing on the to-be-optimized large language model according to the target fine-tuning data to obtain a new to-be-optimized large language model; the application can systematically repair model defects, thereby significantly improving the accuracy and generalization ability of the model when processing document question and answer tasks containing complex graphs, tables and deep reasoning.

The application discloses a kind of big model automatic paper setting methods, system, equipment and medium for self-study examination, suitable for the full automation paper setting construction of self-study examination, and the paper setting method steps are as follows: scanning different self-study examination subject paper, self-study examination exercises and self-study examination class textbook obtains electronic document image;OCR recognizes and archives text content;Mapping relationship between textbook content and subject test is established, and textbook-test document dataset is obtained;Big model is trained using textbook-test document dataset;Deploy big model, realize offline scene available;The textbook content and knowledge point to be set are input into the trained big model, and the test paper, answer and paper setting basis related to textbook content are output.The application trains big model by constructing the dataset of mapping textbook to test paper, effectively improves the setting efficiency of self-study examination test paper, and realizes accurate paper setting for different subjects in self-study examination.

The invention relates to the field of computer software testing, and particularly provides a rapid generation method and device for a test delivery document, which is based on an AI large model and comprises the following steps: S1, long text analysis and feature extraction; s2, generating a test plan; s3, generating prompt words and interacting with the AI; s4, analyzing and storing a result; and S5, performing standardized output. Compared with the prior art, the method has the advantages that the test document writing time can be effectively shortened, the test case quality can be guaranteed, meanwhile, the service coverage rate is higher, a tester can have more time to execute the case, and the project quality is guaranteed.