235 results about "Test path" patented technology

The invention discloses an intelligent terminal function test method and system, and belongs to the technical field of intelligent terminal function test. The method comprises the steps that a dynamic demand tracking mechanism is constructed, UI elements are analyzed, and a topological graph marking resource occupation types and hierarchical dependence is generated; establishing a demand-use case-defect incidence matrix to realize automatic update of the use case state when the demand is changed; executing a test based on the topological graph and the matrix, traversing a path according to a preset strategy, collecting data and comparing an expected result; and optimizing iteration according to a test result, adjusting a node weight and a matrix mapping relation, and generating a new test path and a use case suggestion. The system comprises a dynamic demand tracking module, an incidence matrix management module, a test execution module, an optimization iteration module and a data storage module. According to the method, the test range is accurately adapted to the demand change, the test coverage and the defect tracing efficiency are improved, a test strategy closed-loop optimization mechanism is formed, and the test requirements of a complex system and an agile development mode are met.

The invention relates to a PCBA automatic testing system and method, and relates to the technical field of PCBA automatic testing, and the system comprises a multi-source data collection module which is used for collecting chip dynamic power consumption waveform, PCB interlayer temperature gradient, and multi-source data of signal loop impedance change, and eliminating the sampling delay error of a sensor through a synchronous collection time sequence alignment algorithm; transmitting the acquired multi-source data to a dynamic modeling engine; according to the invention, by dynamically fusing the multi-physical-quantity data and adaptively generating the test path, the system can detect the fault of the PCBA more comprehensively and accurately, the detection efficiency is improved, and the false detection rate is reduced; the thermal aging and faults of the PCB are predicted by using a dynamic modeling engine, so that potential failure risks can be found in advance, and a powerful guarantee is provided for quality control of the PCB; and the test path is automatically generated according to the dynamic modeling result and the data of the fault knowledge graph, so that the workload and error of manually planning the test path are reduced.

The invention relates to the technical field of communication testing, and provides a multi-mode communication equipment test case generation method and device, equipment and a medium, and the method comprises the steps: obtaining a radio frequency parameter, network flow data and equipment log data of communication equipment, carrying out feature extraction and vectorization processing on the radio frequency parameters, the network flow data and the equipment log data to obtain a multi-modal vector; constructing a communication equipment calling relation graph according to the calling relation and the interaction protocol; constructing a test path evolution model based on a graph neural network, and transmitting the multi-modal vector to the test path evolution model, so as to search an optimal test path in a communication equipment calling relation graph through an attention mechanism; constructing a multi-target reinforcement learning reward function and dynamically adjusting the optimal test path through the multi-target reinforcement learning reward function; and according to the optimal test path, generating a target test case, and according to a test result of the target test case, adjusting model parameters of the test path evolution model, and carrying out multi-target reinforcement learning on the reward function.

The invention discloses a test method for multi-parameter synchronous excitation of a water electrolysis hydrogen production system, and belongs to the technical field of water electrolysis hydrogen production, and the test method comprises the following steps: obtaining key operation parameters of the water electrolysis hydrogen production system to construct a dynamic coupling response model, and generating a multi-parameter synchronous excitation signal sequence; the multi-parameter synchronous excitation signal sequence is applied to the water electrolysis hydrogen production system, system response data are synchronously collected, and a system response data set with a time sequence mark is generated; generating an adaptive test path planning instruction based on the system response data set with the time sequence mark and the dynamic coupling response model; and updating the multi-parameter synchronous excitation signal sequence according to the self-adaptive test path planning instruction, and executing an iterative test. According to the method, the dynamic coupling response model is constructed, multi-parameter synchronous excitation is generated and applied, and a closed-loop strategy based on response data adaptive iterative testing is adopted, so that the dynamic characteristics and the performance boundary of the system can be efficiently and accurately identified, and a comprehensive global performance map is constructed.

The invention relates to the technical field of probe testing, in particular to a PCB flying probe test path optimization method based on electrical characteristics, which comprises the following steps: calculating accessibility scores of test points according to the distribution of board surface test points and elements to determine risk types of the test points; determining a risk area grade corresponding to the grid unit according to the accessibility score in combination with the potential shadow area; optimizing the test path of the probe according to the risk area grade corresponding to the grid unit, and adjusting the initial moving speed of the test path of the probe in different grid units; for the same moving time sequence of different probe groups, determining overlapped grids according to the initial probe angles and the test paths corresponding to the probes, and determining whether there is a collision risk between the probes in combination with the initial moving speeds of the probes in different grid units; and when a collision risk exists between the probes, corresponding adjustment measures are taken according to the number of the overlapped grids. According to the invention, the test path is optimized in combination with multi-dimensional design based on the electrical characteristics and testability of the board.

The invention discloses an AI test case intelligent optimization verification method and system, and the method specifically comprises the steps: employing a causal discovery algorithm to analyze an implicit dependency relationship for an entity association structure in a test case knowledge graph, recognizing redundant test cases and invalid test paths, and obtaining a causal dependency network; on the basis of a causal dependence network, traversing uncovered entity relationship paths in the test case knowledge graph, and generating supplementary test case suggestions; dynamically adjusting analysis strategy parameters according to historical optimization data through a self-adaptive engine to obtain an optimization test case set; and based on the optimized test case set, generating an input parameter variation sample by using a fuzzy test engine, and expanding a test boundary. According to the method, the black box test efficiency can be remarkably improved, the test coverage rate and accuracy are improved, meanwhile, the workload of a test engineer is relieved, the user experience is improved, and an efficient and intelligent solution is provided for the field of software test.

The invention relates to the technical field of geotechnical engineering intelligence, in particular to a multi-field coupling intelligent triaxial test method and system combined with machine learning, and the method comprises the following steps: initializing a test device, and establishing a material parameter prior distribution function; defining a target test path and obtaining a target control sequence; acquiring real-time test data through a multi-source fusion sensing array, and preprocessing the real-time test data to obtain multi-dimensional feature fusion data; establishing an online parameter identification module to obtain real-time correction material parameters; establishing a heat-water-force multi-field coupling prediction model to obtain an optimal control sequence; acquiring latest test data, and performing rolling optimization on the model to establish a lightweight control model; and generating an intelligent control instruction to realize self-adaptive intelligent control of the triaxial test. According to the invention, through combination with machine learning, the spanning of the triaxial test from experience control to intelligent control is realized, and an intelligent technical means is provided for the research of the multi-field coupling characteristic of the geotechnical material.

The invention belongs to the technical field of software testing, is suitable for the medical field and the financial field, and discloses a service flow chart-based test path generation method, device and equipment and a medium, and the method comprises the steps: obtaining a service flow chart of a service scene, and extracting nodes of the service flow chart and path topology information between the nodes; on the basis of the service importance weight and the historical execution probability of each node, key test paths in the path topology information are identified, and priorities of the key test paths are sorted; constructing a path coverage rate prediction model based on the dynamically adjusted priority of the key path and the historical execution probability of the key path, and predicting the coverage rate of each key path in the business flow chart based on the constructed path coverage rate prediction model; and configuring a test case set based on the predicted coverage rate of each key path in the business flow chart, and dynamically adjusting the configured test case set based on a multi-objective optimization algorithm. According to the invention, the test efficiency of the business scene is improved.

The invention relates to the technical field of Web component testing, in particular to an automatic test case generation method, system and device for a Web component and a medium, and the method comprises the following steps: extracting a front-end frame type and code features to which the Web component belongs, constructing a visual state transition network, and constructing a unified data flow diagram; based on the code features, the visual state transition network and the unified data flow diagram, semantic reasoning is carried out by utilizing a large language model to generate a test path combination, and a minimum complete test case set is generated by applying a combination test algorithm; generating a composite assertion logic; frame type conversion is executed, and the minimum complete test case set and the composite assertion logic are converted into test codes capable of being executed by a front-end frame type; the test code is executed, and the minimum complete test case set and the composite assertion logic are updated and circulated based on Web component change or test failure in the execution process. According to the method and the device, the Web component automatic test which is high in accuracy, cross-frame adaptive and capable of realizing continuous self-healing can be realized.

The invention discloses a road test route design method and system for an intelligent connected automobile, and the method comprises the steps: determining a full path based on starting point coordinate information and terminal point coordinate information, and processing the full path in combination with user path selection preference and historical test path preference data to generate a plurality of test paths; acquiring historical operation parameters and current operation parameters of path points in the test paths, inputting the parameters into a preset safety evaluation model to output a safety evaluation result, comparing, determining credible path points, and determining candidate test paths from the plurality of test paths according to the credible path points; and selecting a final test path from the candidate test paths according to a preset selection rule. According to the method, pertinence of path design is improved by combining user path selection preference and historical test path preference data, accuracy of safety evaluation is ensured by combining historical and current operation parameters, and scientificity and optimality of final test path selection are realized through a multi-stage objective screening mechanism.

The invention relates to the technical field of software quality assurance, and discloses an internet-based software engineering automation test system, which comprises a test environment perception module, a test intelligent arrangement module and a test execution and optimization module, a server resource state, a network delay parameter and a code structure feature are collected in real time through an environment dynamic sensing module, a multi-dimensional environment adaptation degree evaluation model is constructed, and when it is detected that the environment adaptation degree is lower than a threshold value, container resource expansion and network strategy adjustment are automatically triggered; establishing a mapping relation between multi-level defect features and code modules through a defect root positioning system, searching an optimal diagnosis scheme in a strategy space by applying an improved particle swarm algorithm, and accurately positioning a fault point to a source code line number; finally, closed-loop control of test environment self-adaption, test path self-correction and defect positioning self-optimization is realized, and the accuracy of a test result and the fault repair efficiency are improved.

Testing a semiconductor can be time-consuming as the chip architecture becomes more complex. Testing the possible scenarios becomes increasingly difficult. Chip quality characteristics relating to the chips on a wafer can be used to estimate a probability or rating relating to bypassing system-level testing (SLT). A chip can bypass SLT if there is a high likelihood of passing SLT. Thousands of chip characteristics can be received from wafer testing, chip probe testing, environmental parameters, factory parameters, and other parameters. A chip quality model can use chip quality characteristics as input to generate chip group and SLT parameters. The chip quality model can be a machine learning model or other types of machine learning systems. The chip group parameter or the SLT parameter can be used to direct the testing path of a chip where some chips can bypass SLT thereby saving production time.

The invention belongs to the field of cross-application function automatic testing in mobile applications, and relates to a large model driven cross-application function testing method and system based on memory implantation. The method comprises the following steps: constructing a cross-application function knowledge base for storing and organizing complete information of historical cross-App tasks; searching a historical path most similar to the current test task from the cross-application function knowledge base, reconstructing the historical path into a dialogue memory format conforming to the natural interaction habit of the large language model, and implanting the large language model; and dynamically generating a test path matched with task semantics by utilizing a large language model according to an implanted dialogue memory format, and realizing test state monitoring and feedback correction in the whole process in combination with a local state sensing mechanism. According to the method, a cross-application function knowledge base is constructed, and a global + local memory implantation mechanism is designed, so that the model has a long-term memory ability and a real-time state sensing ability, and therefore, the model can stably run in a complex scene, and a test task can be efficiently completed.

The invention provides a test method and system for a storage chip, and relates to the technical field of storage chips, and the method comprises the steps: obtaining the physical parameter data of the storage chip; mapping each physical parameter data to a low-dimensional manifold space in a coupling manner by taking a storage unit as a unit; calculating the local curvature of each storage unit in the low-dimensional manifold space; the storage units are screened according to the size relation between the self-adaptive local curvature threshold value based on the average value and the standard deviation and the local curvature; in combination with a low-dimensional manifold space, a test path of a fault potential area is generated based on an optimal transmission theory; testing the memory chip once according to the test path; and verifying whether the fault potential area is completely tested or not by combining a homology group in algebraic topology, if so, outputting the tested fault storage unit, otherwise, generating a supplementary test path, and performing secondary test according to the supplementary test path. The test efficiency and the identification accuracy of the fault unit can be effectively improved.

According to the multi-step test case generation method and system based on state-behavior map modeling, the filled Prompt template is used for guiding the large language model to recognize the key state and behavior, the large language model is used for recognizing the key state and behavior planned by the to-be-tested application instead of directly generating the test case, and the test efficiency is improved. The problems of randomness and illusion existing in direct generation of the test case by using a large language model are solved; through a mode of constructing a state-behavior map and traversing the state-behavior map, various complex scenes can be systematically covered, and the test coverage breadth and depth are far better than those of an existing test method based on recording and playback; the multi-step test case can be reliably generated by matching each step in one or more groups of test path sequences generated by traversal with the corresponding implementation template to generate the test case script file.

Illustrative embodiments include a method, an electronic device, and a computer program product for test case generation. The method includes, in response to a target function of a system being developed, determining updated knowledge, corresponding to the target function, in a knowledge base for the system. The method further includes identifying at least one test path from the updated knowledge in the knowledge base based on a predetermined test range for the target function. The method further includes extracting a test object from each of the at least one test path to generate a test case for the target function. By this method, ontology-based automatic generation of test cases can be realized. For example, whenever a product is iteratively updated, incremental knowledge is used as a test target, which can ensure comprehensive coverage of a test strategy without missing any test points, while also improving efficiency and case quality.

A specific logic circuitry of a semiconductor Integrated Circuit (IC) is measured by a sensor. The sensor includes: a signal splitter that splits a signal from the specific logic circuitry into two test paths; a delay element that receives and applies a delay to a first test path, the delay based on a predetermined timing margin that is selected from a group of discrete timing margin values comprising a shortest timing margin value and at least one longer timing margin value; a comparison circuit that compares the delayed first test path and a second test path and provides a measurement output according to the comparison for an instance of measuring; and a controller that sets the predetermined timing margin such that, over the instances of measuring, a frequency of selection of the shortest timing margin value is higher than a frequency of selection of each longer timing margin value.

The invention discloses a semantic perception kernel fuzzy test method and device based on a large language model, and the method achieves the structural and context-related semantic analysis of a system call sequence in a variation stage through the introduction of the large language model with the language understanding and code modeling capabilities. And a variation strategy with logic consistency and attack potential is dynamically generated, so that the effectiveness and diversity of fuzzy test input are greatly improved. Specifically, semantic modeling and structured understanding are performed on a system call sequence by using a large language model, a variation strategy instruction with context relevance and execution reasonability is generated, and fuzzy test path exploration is continuously optimized through a dynamic feedback mechanism. The defects of a traditional fuzzy test method in variation efficiency, coverage depth and complex state adaptation are effectively overcome, and a more intelligent, self-adaptive and efficient vulnerability detection and security guarantee solution is provided for an operating system kernel.

The invention relates to the technical field of software testing, in particular to an AI-based low-code intelligent test generation system which comprises a demand analysis module, a test path generation module, a test script conversion module, an execution environment management module and a result analysis module. A test path of the test path generation module is supplied to the test script conversion module and the result analysis module, a test script generated by the test script conversion module is sent to the execution environment management module, and an execution result of the execution environment management module is fed back to the result analysis module; and an optimization suggestion generated by the result analysis module is sent to the test path generation module and the test script conversion module. Through cooperation of multiple modules, full-process automation of low-code testing is achieved, testing paths and scripts are dynamically optimized, testing efficiency and coverage pertinence are improved, manual intervention and the error rate are reduced, and dynamic adaptation and execution stability of a testing scheme are ensured.

The invention provides a domain controller test case intelligent generation method and system based on a knowledge graph, belongs to the technical field of automobile electronic testing, and is used for solving the problems of insufficient coverage rate, low efficiency and difficulty in knowledge inheritance of domain controller testing in related technologies. According to the method, a test knowledge graph fusing a functional architecture, historical data and expert experience is constructed, vector representation of nodes and relationships is learned by using a graph neural network, an optimized test path is generated through intelligent reasoning, then an extended test case is generated through a multi-dimensional generalization technology, and finally continuous optimization is performed through closed-loop quality evaluation. The test coverage rate and the design efficiency can be remarkably improved, and systematic precipitation and reuse of test knowledge are achieved.

The invention provides a test script generation method and device, electronic equipment, a medium and a program product, relates to application of a large model in a financial science and technology scene, and can be applied to the technical field of artificial intelligence, the technical field of big data and the field of financial science and technology. The method comprises the following steps: acquiring a pre-constructed multi-agent cluster; obtaining a target test demand by using a user interaction agent; performing semantic understanding on the target test requirement by using a semantic analysis agent to obtain semantic representation information; generating candidate test paths based on the semantic representation information and a preset interface structure knowledge graph by using an operation reasoning agent, and outputting a test path sequence based on the candidate test paths; and receiving the test path sequence by using a script generation agent, and constructing a test script based on the test path sequence and a script template to generate a target test script.

The invention discloses an automatic penetration test path planning method and system based on agent collaboration, and relates to the technical field of network security. Performing initialization starting on the plurality of intelligent agents based on the penetration test target range; collecting the target system and writing the target system into a shared blackboard mechanism; matching the asset feature information with a preset vulnerability knowledge base according to the test strategy mode to generate vulnerability utilization conditions, and constructing a global attack graph according to the asset feature information and the vulnerability utilization conditions; generating an attack path based on the global attack map, executing an attack operation on the target system according to an attack step sequence of the attack path, when an execution result is failure, updating the global attack map according to a feedback failure result, and re-planning to generate a new attack step sequence; and when the execution result is successful, generating a penetration test report for the penetration test target range according to the success result. By implementing the method, the actual demand of deep security assessment of the complex heterogeneous system is met.

The invention relates to the technical field of power equipment testing, in particular to a power test intelligent testing system which comprises a nameplate analysis module, a channel optimization module, a path configuration module, an interference identification module and an excitation regulation and control module. According to the method, the content of the nameplate of the equipment is extracted through image recognition to complete structural analysis of electrical parameters, a parameter feature set is established through information such as frequency, capacity, phase number and current, and test channel screening is achieved according to a set frequency point and channel capacity matching relation. The method comprises the steps of setting a path sorting mode and mapping response time parameters in combination with physical wiring characteristics and a phase number structure, marking channel combination interference levels based on an inductive interference identification mode, optimizing channel interference in an excitation process by adjusting an excitation sequence and a grounding strategy, and executing interval discrete regulation and control operation in combination with a frequency interval real-time judgment result. And collaborative optimization of test path construction, interference control and excitation sequence allocation is realized.

The application relates to a high-precision addressable ring oscillator test chip, method, device and medium, which comprises an addressing module, an output module and a plurality of ring oscillator test modules; the ring oscillator test module comprises a signal transmission module, a multifunctional test module and a plurality of ring oscillator test structures; the addressing module is used for selecting a ring oscillator test structure from the ring oscillator test structures of the plurality of ring oscillator test modules to perform a communication test; the multifunctional test module can switch the voltage compensation mode or the small-current test mode of the ring oscillator test structure based on a received control signal; when the characteristic parameters of the ring oscillator are measured, the voltage compensation mode can utilize voltage drop compensation to reduce the influence of the resistance voltage drop introduced in the test path, effectively improving the measurement precision, and the small-current test mode can effectively measure the static power supply current of the ring oscillator.

The invention discloses a large model security test method and device and a computer program product, and the method comprises the steps: firstly, screening out a target starting node with the highest semantic similarity with a target malicious query text from a pre-constructed state diagram database, and then when the value of the highest similarity is higher than a preset threshold value, starting the target malicious query text; a path multiplexing mode is adopted, a complete test path corresponding to the target starting node is directly multiplexed to test the target large model, and when the value of the highest similarity is not higher than a preset threshold value, a path exploration mode is adopted to search the target large model; and a new test path is generated by using a test strategy library, a guide large model, an attack large model and the like for testing (and is stored for subsequent direct multiplexing), so that effective accumulation and intelligent multiplexing of historical experience are realized, and repeated exploration is avoided. Compared with existing testing methods such as a static template, the testing efficiency is continuously improved along with experience accumulation, a complete closed loop of self-evolution is formed, and an ideal testing effect is achieved.

The present application relates to four-probe flying probe test equipment path optimization method, device and storage medium, the method includes task input module receives basic constraint condition and test task information, if using fixed grouping mode, according to the basic constraint condition fixedly divide four probes into two groups, the distance of two groups of probes from the current test task to the selectable next test task is calculated in turn and the moving path of each group of probes is planned, if using the variable grouping mode that allows probe to change group in each step test process, the optimization objective function of each step of each probe is calculated in turn and the moving path of each probe is planned, according to the moving path of each planned probe, control execution module controls each probe to move in turn and completes test task. The mathematical model constructed more comprehensively and accurately reflects the actual situation of four-probe flying probe test, provides more reliable theoretical basis for path optimization, and helps to improve the optimization precision of test path.

The invention relates to a probe head, which comprises a probe seat, a plurality of vertical probes and a plurality of coaxial probes, the vertical probes slidably penetrate through guide holes of the probe seat, the lower ends of the vertical probes are used for contacting conductive contacts of a tested device, and each coaxial probe comprises a probe body and a tip unit arranged at the lower end of the probe body. The probe body comprises a plurality of conductors which are mutually insulated, the needle point unit comprises a first needle point and a second needle point which are electrically connected with the plurality of conductors respectively and are used for being in contact with a conductive contact of a tested device, and the plurality of coaxial probes comprise a first return probe and a second return probe which form a return probe pair and are used for being configured to be a local part of a return test path; therefore, the high-frequency loopback test requirement can be met.

The invention relates to the technical field of computers, in particular to a test case generalization method for automobile network and data security, which comprises the following steps: collecting and preprocessing multi-source heterogeneous data, fusing the data to construct a dynamic risk feature model to extract an attack vector, and constructing a layered scene space based on real-time topology of a vehicle-mounted network; a two-channel generalization engine is utilized, unknown threat scene cases are generated by means of a structure causal model, and variation is injected into nodes of a protocol syntax tree to generate fuzzy test cases so as to enrich case types; a reinforcement learning framework is introduced to dynamically optimize a test path, and a closed-loop feedback mechanism is adopted to expand high-risk scene nodes, so that the multi-source heterogeneous data processing capability is effectively improved, the unknown threat simulation capability is enhanced, the test efficiency is improved, and the problem that a test method in the prior art is incomplete in multi-source heterogeneous data processing and poor in reliability is solved. The technical problems of influence on subsequent analysis accuracy, single test case generation type, lack of unknown threat simulation and low test efficiency in the prior art are solved.

The application discloses a UI test script visual arrangement method and system based on reinforcement learning, relates to the technical field of user interface testing, and discloses a UI test script visual arrangement method based on reinforcement learning, which comprises the following steps: receiving an initial test path constructed by a user through a preset first visual arrangement interface; performing path optimization on the initial test path to obtain an optimized test path; displaying comparison information of the optimized test path and the initial test path on a preset second visual arrangement interface, and generating a UI test script in response to a user interaction operation received on the second visual arrangement interface. The application can efficiently and at low cost create and maintain a UI automatic test with clear business intention and stable execution.

The invention discloses a method and system for software automatic testing, and relates to the technical field of computer software testing, and the method comprises the steps: building a constraint initial test target set covering path input and output; dynamically adjusting a test case generation strategy for the demand document; and updating the reconstructed test case to the constraint initial test target set, and constructing a path priority for the second time to complete the software automatic test. According to the invention, the accuracy of test case generation and the demand coverage integrity are improved; dynamic weight distribution of a test path and self-adaptive adjustment of a test case generation strategy are realized, and the coverage capability on a deep path and a high-risk module is effectively improved; the response capability of the test system to frequent iteration and the reuse efficiency of test resources are enhanced, and the software automatic test with higher automation degree, stronger environmental adaptability and more comprehensive coverage is realized on the whole.