26 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 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 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 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 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 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.

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 provides a test document updating method and device, electronic equipment and storage medium. The method comprises: acquiring project data related to a software project; constructing a project knowledge base and a global traceability graph based on the project data, wherein a node in the global traceability graph represents different entities in a test life cycle, and an edge represents a traceability relationship between entities; when a change event representing a change in the software project is monitored, the global traceability graph is used as an index to locate a target entity affected by the change event; based on the project knowledge base, at least one document generation agent corresponding to the target entity is started to update the test document related to the target entity; and the global traceability graph is updated according to the updated test document. The mechanism guarantees the timeliness, consistency and traceability of the test document and the actual state of the project.

The invention discloses an AI-based test knowledge graph construction method, which relates to the technical field of software testing, and comprises the following steps: extracting original test text data from a requirement specification and a historical test document of target software, labeling test behavior words, input objects and constraint conditions, and generating a structured test corpus set; extracting a test entity set, and vectorizing the test entity set to obtain a test entity vector set; inputting the graph attention network to carry out edge weight calculation to obtain a test relation matrix; and constructing an initial test knowledge graph based on the test entity set and the test relationship matrix, and weakening the same-layer loop path in the initial test knowledge graph to obtain a final test knowledge graph. According to the method, semantic association and time sequence characteristics of a test entity are described by utilizing vectorization modeling, so that test elements have computable and comparable representation forms; the hierarchical clarity of the knowledge graph structure is improved, and the expression accuracy and reuse value are enhanced.

The invention relates to a test document data generation method, computer equipment and a storage medium. The method comprises the following steps: acquiring a service attribute information set corresponding to each service field in a target service document, and associated fields in an associated document corresponding to the target service document; determining a field mapping relationship between the business field and a corresponding associated field based on an associated field identifier in a business attribute information set corresponding to the business field; determining a field value construction mode of the business field based on a field label in a business attribute information set corresponding to the business field; determining a field value set corresponding to the business field based on the field value construction mode of the business field; and determining test document data corresponding to the target business document based on the field value set corresponding to each business field and the field mapping relationship. By adopting the method, the flexibility of testing the document data can be improved.

The invention discloses a key information extraction method and device, equipment, a medium and a product. The method comprises the steps that a to-be-tested document image and a problem text sequence of the to-be-tested document image are received; obtaining a target key information extraction model; the to-be-tested document image and the question text sequence of the to-be-tested document image are input into a target key information extraction model, an answer text sequence of the to-be-tested document image is generated, and the answer text sequence of the to-be-tested document image is obtained by querying a target mark generated by the target key information extraction model. The hidden state of the target mark implicitly encodes the physical position information of the answer in the to-be-tested document image. According to the method, the target mark is introduced, the target key information extraction model is guided to perceive the physical position information of the answer file sequence in the to-be-tested document image, and the answer is positioned through the physical position information, so that the answer text sequence of the to-be-tested document image is obtained, and the accuracy and effect of key information extraction are improved.

This invention relates to a method and system for constructing a knowledge graph in the vehicle testing domain based on global semantics. The method includes extracting tables and related text from vehicle testing PDF documents; outputting a table image that retains its complete two-dimensional layout; inputting the table image into a multimodal large model to generate a global semantic description containing the table's business themes and row-column logical relationships; performing topic clustering on the global semantic description, identifying representative entities under each topic, and selecting entities with appropriate granularity and high relevance as seed entities; using the seed entities as guides, combining the table image and the global semantic description, extracting candidate knowledge triples from the vehicle testing PDF document; and performing global knowledge fusion on the candidate knowledge triples to form a globally consistent knowledge graph. This invention can effectively solve the problems of table logic breakage, entity omission, and relationship generalization in existing technologies when processing vehicle testing documents.

This invention provides a website automated testing method, apparatus, and electronic device, belonging to the field of automated testing technology. The method includes: acquiring test documents uploaded by users under a target project; parsing, segmenting, and vectorizing the test documents; storing the vectors in a vector database; and constructing a knowledge base associated with the target project; receiving test requirements input by the user; starting an AI orchestration engine; loading the large language model configuration, toolset, and knowledge base associated with the target project; and, based on the test requirements, having the AI ​​orchestration engine execute test tasks cyclically through an agent to obtain test execution results. This invention enables intelligent orchestration and execution of the entire website automated testing process, improving testing efficiency and robustness.

A computer-implemented method, a computer system, and a computer program product for generating an automation test script. Existing testing documents of a product under test can be acquired. A testing topology describing steps, containers, elements and actions of the test can be generated by extracting keywords in the existing test documents, wherein each element defines a user interface (UI) element of the product, each action defines an action attribute for an associated UI element, each container defines an operation area containing one or more UI elements, and each step defines one or more operations for one or more actions associated with one or more UI elements. An automation test script for the product can be generated based on the testing topology.

This invention discloses a computing resource planning method and system based on a large model. The computing resource planning method includes: constructing a structured performance database based on benchmark test documents; generating a set of configuration data points corresponding to each configuration node based on the performance database; generating optimal data points based on the configuration data point sets; obtaining the business target concurrency; traversing the optimal data points corresponding to the configuration nodes; generating at least one candidate deployment scheme that meets the business target concurrency; calculating the cost information of the candidate deployment schemes; and generating the target deployment scheme based on the cost information. Specifically, the optimal data point has a first token latency less than a preset latency time threshold, a single-user throughput greater than or equal to a preset throughput threshold, and the concurrency number is the maximum value in the configuration data point set. This invention achieves accurate prediction of concurrency carrying capacity under strict latency constraints through structured modeling and interpolation calculation, exhibits strong cross-scenario generalization ability, and reduces computing resource planning errors.

The invention relates to a vehicle-mounted interaction large model test case generation enhancement method and system, and the method comprises the following steps: S1, obtaining and extracting a plurality of original test documents, and obtaining a semantic feature library; s2, generating an initial test case by adopting a pre-trained generation large model; s3, performing structured fusion on the initial test case and the original test document to obtain an enhanced document set; s4, generating a large model, generating a supplementary test case based on the enhanced document set, and obtaining a stop judgment function at the moment; s5, judging whether the stop judgment function reaches a preset threshold value or not, if yes, stopping iteration, and outputting a current enhanced document set; if not, dynamically adjusting a generation prompt strategy for generating the large model according to a stop judgment function, and returning to the step S4 to continue iteration; and S6, performing final duplicate removal and screening on the test cases in the enhanced document set to obtain a final enhanced test case set. The coverage and distribution rationality of the test cases are better.

The invention discloses an engineering document quality evaluation method, device and equipment and a storage medium, and is applied to the field of financial science and technology. The method comprises the steps of obtaining a to-be-evaluated engineering test document, performing text segmentation processing on the engineering test document, and performing semantic feature extraction on segmented text units to generate semantic context features; based on a bidirectional long-short-term memory network, performing dependency feature extraction on the semantic context features, endowing a dependency feature extraction result with a position attention weight through a gating mechanism, and generating a domain entity tag space; based on a legal label transfer rule and the domain entity label space, determining an optimal label sequence, and based on the optimal label sequence, determining a structured entity tree corresponding to the engineering test document; and performing quality evaluation on the engineering test document based on the structured entity tree. According to the technical scheme, the quality evaluation precision of the engineering test document is improved.