431 results about "Test failure" patented technology

Method for prediction of test failures are disclosed. A method may include retrieving, by a test failure prediction computer program, test results for a test; training, by the test failure prediction computer program, a machine learning engine based on one or more hypotheses; receiving, by the test failure prediction computer program, metrics for a code file; providing, by the test failure prediction computer program, the metrics for the code file to the trained machine learning engine; receiving, by the test failure prediction computer program, an output from the trained machine learning engine that provides a probability of failure; and outputting, by the test failure prediction computer program, the output.

Embodiments of the disclosure provide for improved automation of software change management. Such embodiments enable automatically managing and testing software modifications. Some embodiments receive a change request data object indicative of a software modification, generate a risk level of the software modification based on the change request data object, and generate a test scheduling data object based on the change request data object and the risk level, where the test scheduling data object is indicative of a testing operation for the software modification. Some embodiments initiate performance of the testing operation at a testing environment and receive, from the testing environment, test performance data. Some embodiments determine a test failure based on the test performance data and, in response to determining the test failure, generate a communication bridge between a subset of a plurality of computing devices based on the test failure and a development flow data object.

The invention discloses an electric energy meter verification fault intelligent judgment system, and relates to the technical field of electric energy meter fault judgment, and the system comprises the following components: a high-precision monitoring and collection unit which collects various parameters of an electric energy meter in real time through a high-precision metering chip and a sensor, so as to more comprehensively understand the operation environment of the electric energy meter, and improve the detection accuracy of the electric energy meter; according to the method, the fault mode recognition model is constructed through the logistic regression model, the relation between the features and the fault modes can be accurately mapped, the cross entropy loss function and the optimization algorithm are adopted, the accuracy of model prediction is effectively improved, and the accuracy of model prediction is improved. According to the method, model hyper-parameters are adjusted and optimized through the random search technology, the performance of the model is further improved, the stability and reliability of the model in practical application are ensured through inspection of a verification set and a test set, powerful support is provided for rapid and accurate judgment of electric energy meter faults, and the efficiency and accuracy of electric energy meter verification are improved.

The invention relates to the field of chip packaging testing, in particular to a BGA chip packaging testing method. The method comprises the following steps: carrying out full-flow thermal imaging scanning on a BGA chip packaging process, carrying out space temperature gradient diffusion distribution analysis, and constructing a temperature diffusion distribution map of each region; according to the probe array, acoustic scanning is carried out on the BGA chip solder ball contact surface, abnormal frequency detection is carried out, and abnormal acoustic nodes are marked; performing transient temperature mutation detection and potential packaging defect positioning analysis on the temperature diffusion distribution map based on abnormal acoustic nodes, and extracting a potential packaging defect area; and carrying out multi-threshold micro-vibration excitation on the potential packaging defect area, carrying out comprehensive evaluation on the reliability of the defect area structure, and generating a reliability evaluation report of the solder ball contact surface structure. According to the invention, accurate packaging test failure prediction is realized, packaging process parameters are optimized, and chip packaging quality and stability are improved.

The present disclosure provides techniques and solutions for automatically correcting software tests. When a test failure is detected, it is determined whether a screenshot or code associated with a second version of a software artifact includes a user interface element that has a semantically equivalent identifier to a user interface element in a screenshot or code associated with a first version of the software artifact. Identifying a semantically equivalent identifier can include determining a section of the user interface, in the screenshot of the code, of the first version of the software artifact where the user interface is located and searching the corresponding section of the user interface of the second version of the software artifact. A definition of the software test can be updated to reference the semantically equivalent user interface element.

The present disclosure relates to the technical field of autonomous driving. Provided are a method and apparatus for determining a failure probability in an autonomous driving simulation test. The method comprises: performing high-coverage uniform sampling in a high-dimensional parameter space, so as to obtain a set of first test scenarios; performing a simulation test on each first test scenario in the set of first test scenarios, so as to obtain a first test index value; determining a scenario weight of each first test scenario, and determining a first test failure probability on the basis of the scenario weight and the first test index value; if the first test failure probability does not meet an accuracy requirement, performing sensitivity analysis on a first scenario parameter that affects the first test index value, so as to determine sensitive scenario parameters, and then reducing the high-dimensional parameter space to a low-dimensional parameter space formed by means of the sensitive scenario parameters; and performing reliability analysis on the low-dimensional parameter space, so as to determine a final failure probability. By using the method and apparatus for determining a failure probability in an autonomous driving simulation test, the problem of the efficiency of calculation of related methods for determining a failure probability being low is solved.

The invention provides an automatic test method, which is applied to a host to perform EAP simulation test on semiconductor equipment, and comprises the following steps: obtaining a test case set comprising a plurality of test cases, the test cases comprising a plurality of test steps arranged in order and preconditions and expected results respectively corresponding to the test steps; a target test case group is obtained in the test case set, test cases included in the target test case group are target test cases, and input data corresponding to preconditions and expected results in the target test cases are obtained; on the basis of the sequence of the test steps contained in the target test case, testing the current test steps in sequence to obtain a case test result of the target test case, wherein the case test result indicates that the test of the target test case is successful or failed; and obtaining a case test result of each target test case in the target test case group. According to the invention, automatic testing of the semiconductor equipment is realized.

The invention provides a method and device for determining a code patch, equipment and a storage medium, and the method comprises the steps: generating a test case for a set fragment in a to-be-tested file by executing a first large language model; running the test case for the to-be-tested file; if the error description of the test failure is obtained, inputting the error description and the problem code block into a second large language model to obtain at least one code patch for the problem code block; wherein the at least one code patch is obtained by the second large language model according to at least one code repair strategy through a cluster search mode; the at least one code patch is in one-to-one correspondence with the at least one code repair strategy; a final patch is determined from the at least one code patch and the set segment is replaced. According to the method, the test case is automatically generated through the first large language model, the patch is automatically generated for the problem code block through the second large language model, and the automation degree and efficiency of the test are improved.

The invention discloses an automatic UI self-healing test method and system based on multi-agent AI, and belongs to the technical field of automatic UI tests.The automatic UI self-healing test method comprises the steps that an original test script is semantized through a test reasoning interpretation class, and an expected intention is output; when the test fails, synchronously collecting multi-source data and extracting multi-modal features, constructing a fault propagation graph according to an expected intention and the multi-modal features, and performing fault propagation analysis by using a graph attention network to obtain a fault diagnosis result; according to a fault diagnosis result, a deep Q network, a greedy strategy and a Byzantine fault-tolerant algorithm are adopted to negotiate and decide a repair strategy through a distributed agent cooperation mechanism, and feedback is obtained; optimizing and dynamically adjusting the repair strategy and the test reasoning interpretation class through a meta-learning algorithm based on feedback; a test intention is deeply understood by constructing a test reasoning interpretation class, and fault diagnosis and automatic repair are cooperatively completed by adopting a distributed intelligent agent, so that the semantic understanding capability, the diagnosis accuracy and the repair success rate are improved.

The invention provides a testing device, a testing system and a testing method, and relates to the technical field of semiconductor memory device testing. The testing device comprises a testing needle card, a DC testing circuit, an AC testing circuit, a mode switching circuit and a main control circuit. Two functions of AC testing and DC testing are integrated, the system can execute the DC testing process, the storage Die with faults is selected out, and then the performance of the storage Die at high frequency or actual working speed is further verified through the AC testing process, so that the storage Die with potential problems is identified, and the testing accuracy is improved. Meanwhile, the mode switching circuit is arranged to switch the connection of the DC test circuit and the connection / disconnection between the AC test circuit and the test needle card, so that the possible interference of the DC part on the AC high-frequency test in the same test device is effectively avoided, and the risk of AC test failure is reduced.

The invention discloses a network card control method and device, electronic equipment, a storage medium and a product, and relates to the technical field of computers.The method comprises the steps that whether a mirror image module has data packet interaction or not is detected in real time, and a data packet is sent to a network card when a to-be-tested computer board card is subjected to a pre-start execution environment start test; the working mode of the network card is a first working mode; when it is detected that the data packet interaction does not exist in the mirror image module within the preset time period, detecting whether the network card in the first working mode executes an over-plugging operation or not; and if not, sending a first cut-off instruction to the link cut-off module, the first cut-off instruction being used for instructing the link cut-off module to execute a plugging operation on the network card in the first working mode. According to the embodiment of the invention, the problems of test failure and manpower and time cost waste caused by the fact that the offline of the network card cannot be found in time in the starting test process of the to-be-tested computer board card can be solved.

Some examples of the present disclosure relate to risk analysis of test failures that occurred during a testing phase of a continuous integration pipeline. In one particular example, a system can detect a failure of a test during a testing phase of a continuous integration pipeline. The testing phase can involve executing a group of tests in a plurality of configurations prior to merging an update to source code into a code base of a software application. Based on detecting the failure of the test during the testing phase, the system can access historical data associated with prior executions of the test, determine a risk score associated with the failure of the test based on the historical data, and perform an action associated with the source code based on the risk score.

The invention relates to a testing method, computing equipment and a computer readable storage medium in the technical field of automatic testing. The method comprises the following steps: representing competitive resources of a test case when the test case is used for testing by utilizing a competitive resource indication in annotation information corresponding to the test case, determining a target test case during testing, determining the competitive resources according to the competitive resource indication in the annotation information of the target test case, and determining a set of competitive resources of all test cases which are currently in a running state, and then determining the relationship between the competitive resource of the target test case and the competitive resource set, if the competitive resource of the target test case is not included in the competitive resource set at present, indicating that the target test case can occupy the competitive resource exclusively after the target test case is operated, so that the condition of test failure caused by resource competition does not occur, and the test efficiency is improved. Therefore, the target test case can run, the test efficiency can be effectively improved, and the test period can be shortened.

The invention relates to the technical field of software engineering management, and discloses a computer software development information management system and method. According to the method, real-time multi-dimensional association among four entities, namely a demand entity, a code entity, a test entity and a deployment entity is realized by constructing a dynamic knowledge graph center, and an end-to-end closed-loop control system is formed; a full-link traceable network is dynamically established through explicit binding, implicit capturing and cross-layer traceability mechanisms, demand omission marks are automatically repaired, and accurate attribution of environmental problems is achieved; manual operation blind areas are eliminated through automatic means such as developing and submitting forced association, automatically freezing branches when test fails and deploying environment consistency verification; based on a risk thermodynamic diagram of full-link topology penetration and fusion defect density and change frequency, active early warning of a high-risk module is realized, and controllability and quality assurance capability of a software development process are remarkably improved.

The invention discloses a test failure root cause diagnosis method, which relates to the technical field of electric digital data processing, and is characterized in that after a test failure signal is captured, comprehensive analysis is carried out in combination with multi-source log information of a test case and test environment configuration data, so that the influence of environment configuration on a test is fully considered, and information in a log is fully mined; according to the method, a more accurate diagnosis result is obtained, and a corresponding solution is matched according to a test failure root cause to solve the problem of test failure, so that the problems of low efficiency and high misjudgment probability of manual analysis, neglect of the influence of a test environment on the test failure, difficulty in identifying implicit connection between texts in a log and difficulty in testing failure in the prior art can be solved. Therefore, the technical problem that the obtained analysis result is difficult to be used for accurate root cause diagnosis is solved, the diagnosis efficiency of test failure root causes is improved, the diagnosis precision is improved, and the overall test period is shortened.

The invention provides sampling equipment for roadbed and pavement compactness detection. The sampling equipment for roadbed and pavement compactness detection comprises a chassis, four wheels are fixedly mounted at the bottom of the chassis, a bearing plate is fixedly mounted at the top of the chassis through a frame box, two handles are fixedly mounted on one side of the frame box, and the sampling equipment further comprises a lifting mechanism fixedly mounted at the top of the bearing plate. According to the sampling equipment for roadbed and pavement compactness detection, the lifting motor drives the sampling mechanism to ascend and descend, the sampling motor rotates to drive the drill bit to rotate for sampling, the three trays rotate to subpackage three layers of different samples, and the three different layers of samples are detected respectively; detection failure caused by errors generated by compaction degree detection of the mixed samples is avoided, the air cylinder is arranged to drive the push disc to push out the samples, the samples are pushed out completely, detection errors caused by residues are avoided, and workers can take out the samples conveniently through the sampling opening.

The invention discloses a high-speed signal time sequence bias method and device applied to a reliability test. The method comprises the following steps: finding out an effective capture time interval of each bit DQ signal during read-write operation; calculating the midpoint time of each bit DQ signal, and aligning the midpoint time with the DQS to serve as an optimal capture time point; starting from the optimal capturing time point, deviating leftwards or rightwards by a set step length, and performing time deviation of different degrees; performing read-write left pulling deviation or right pulling deviation operation tests under different temperature conditions, and recording test results; according to a test result, finding out a limit boundary causing a test failure; and judging whether the current design margin is enough or not according to the limit boundary, and if not, adjusting the currently set driving parameters. According to the method, the product limit boundary is found out through batch sample data, whether the margin is enough to cover the design parameter deviation or not is evaluated, the normal read-write service of the memory can be ensured even in an extreme scene, error code failure is avoided, and the robustness of the product is improved.

The invention relates to the technical field of micro-fluidic chip testing, and provides a micro-fluidic chip testing cabin which comprises a cabin body and a cabin cover, the side wall of the cabin body is of a hollow interlayer structure, the hollow interlayer structure is filled with protective gas, and the protective gas in the hollow interlayer structure can enter the cabin body. According to the test cabin, the test environment of the to-be-tested micro-fluidic chip in the cabin body is an oxygen-free environment, test failure caused by air interference when the to-be-tested micro-fluidic chip is tested in the cabin body is avoided, meanwhile, the cabin cover is arranged at the top of the cabin body, the sealing performance of the test cabin is further guaranteed, the test passing rate is further increased, and the test efficiency is improved. The problem that an existing testing device fails in testing due to air interference is solved.

Implementations are described herein for network testing using machine learning. In some implementations, a testing system receives an indication of a test failure associated with a test of a wireless communication system. The testing system stores one or more packet capture files associated with the test failure. A machine learning model associated with the testing system performs a root cause analysis of the test failure using the one or more packet capture files. The testing system determines a configuration update for the wireless communication system based on a result of the root cause analysis. The testing system generates an output that indicates the configuration update.

The invention relates to the technical field of photovoltaic inverters, in particular to an aging test manipulator motion control method and system. The method comprises the steps of capturing the state of the manipulator in real time; a safety controller and an emergency stop mechanism are added in a control system of the aging test manipulator; designing a manipulator control function block; real-time data exchange between the manipulator control system and other production equipment is realized by utilizing a preset modern industrial communication protocol; an intelligent fault diagnosis system is arranged, and controllable movement conveying is carried out on the jig through z-axis mutual coordinated movement; and performing function block packaging on each function on line, wherein a function block is used for performing real-time detection on online X-axis and Z-axis movement. According to the scheme, by setting the aging control method of the manipulator, the accuracy and stability of the manipulator in the carrying and positioning process are ensured, and the risk of product damage or test failure caused by inaccurate movement of the manipulator is remarkably reduced.

The invention discloses a log analysis method and device, equipment, a medium and a program product, and relates to the technical field of software testing, and the method comprises the steps: obtaining failure log data of a failure test case, and success log data of a success test case corresponding to the failure test case; extracting target content related to the test failure in the failure log data through a preset large language model; performing semantic comparison on log data corresponding to the test steps in the failure log data and the success log data through a preset large language model to obtain difference information; analyzing the failure log data based on a target cue word through a preset large language model to obtain a failure reason of the failed test case, the target cue word being obtained by combining a first cue word and a second cue word, and generating the first cue word by embedding a target content into a first cue word template; and embedding the difference information into a second cue word template to generate a second cue word. The log analysis efficiency is improved.

The invention relates to the technical field of data storage, and discloses a method for testing the signal quality of an IO interface of a memory module, and the method comprises the steps: verifying the signal integrity of the I / O interface in the memory module based on an eye diagram analysis method; after the signal is verified to be complete, the morphological characteristics of the input eye pattern and the output eye pattern are quantitatively compared, whether morphological characteristic changes occur in the signal transmission process or not is judged, and the morphological characteristic changes at least comprise logic level flipping errors, time sequence recognition errors and signal quality degradation; if the morphological characteristics of the input eye pattern are consistent with the morphological characteristics of the output eye pattern, the test is successful; and if the morphological characteristics of the input eye pattern are inconsistent with the morphological characteristics of the output eye pattern, determining that the test fails. Visual and quantitative verification of signal integrity is realized through eye pattern analysis, multi-dimensional indexes such as voltage, time sequence and noise are covered, and the signal transmission quality is reflected more comprehensively compared with a single parameter test.

The invention discloses an environment deployment method and system of a cloud native electric power auxiliary service market system, and belongs to the technical field of electric power system informatization. The method comprises the following steps: acquiring test environment configuration information and a system running state; constructing an infrastructure and deploying a system service component according to the test environment configuration information, and generating a test environment consistent with the production environment; testing the test case in the test environment to obtain a test result; verifying the system operation state and the test result according to a preset verification rule to obtain a test report; the test report comprises a test success report and a test failure report; when the test success report exists and the test coverage is in accordance with the preset range, allowing the system to be deployed to the production environment; and when the test report does not exist, the test failure report exists or the test coverage does not meet the preset requirement, the system is prohibited from being deployed to the production environment. The problems that the test environment generation efficiency is low and deployment verification is not strict can be solved.

The invention provides a multichannel platinum thermal resistor program control simulation card and method, the multichannel platinum thermal resistor program control simulation card comprises a resistor gating array, a relay driving array, a microcontroller module, a communication interface module and a power supply module, and the method comprises the following steps: inputting a temperature value in an upper computer; the upper computer carries out temperature-resistance value conversion; the upper computer sets resistance precision; the upper computer packages the resistance value data into a data packet according to a communication protocol, and the data packet is sent to a microcontroller of the lower computer after CRC verification; the microcontroller receives the data packet, analyzes the data packet according to a communication protocol after performing CRC (Cyclic Redundancy Check), and obtains resistance value data; the microcontroller performs'resistance value-I / O state 'conversion; the microcontroller sets an I / O state. The method has the beneficial effects that the integration and automation levels of test equipment are remarkably improved, and the test failure risk caused by the problems of instrument consistency and the like is reduced.

Techniques and solutions are described for automatically updating test code based on changes, including additions or deletions, to production code. Requests to analyze production code and a modification to production code are received. The modification is applied to the production code to provide modified production code. Test code specific for the production code is executed on the modified production code. It is determined that a test specified in the test code was failed by the modified production code. A condition responsible for test failure is identified, where the condition specifies at least one expected value or at least one expected result. A modification to update the test code is determined, where the modification includes an actual value or an actual result obtained during execution of the failed test. The modification to the test code is applied to provide modified test code.

The invention discloses an automatic test failure repairing method and device, and relates to the technical field of computer error diagnosis, and the method comprises the steps: obtaining failure test data when an automatic test task fails; preprocessing the failed test data to extract at least one test feature; and inputting the at least one test feature into a pre-trained structural causal model to output a reasoning result of the automatic test task, and repairing a test process of the automatic test task based on the reasoning result to carry out automatic test, thereby solving the problems of complex root cause of positioning test failure caused by changes of a software system and a test case and high test efficiency. The technical problems of time and labor consumption, increase of diagnosis cost, false alarm and missing alarm and lack of dynamic sensing capability are solved, and the purposes of quickly and accurately positioning the root cause of the test failure, automatically generating a repair scheme, reducing manual intervention, shortening the test period, improving the test efficiency, reducing the risk of false alarm and missing alarm and improving the test efficiency are achieved. And the technical effect of test optimization in a complex scene is supported.

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 embodiment of the invention discloses a development data detection method and equipment based on a low-code platform and a medium, belongs to the technical field of software development, and solves the problem that the repair efficiency is reduced by manual coding when a software code is changed and a test fails. Based on the development data change amount, matching a test suite containing the corresponding number of test cases in a preset test suite set, and testing the change data through the test suite; under the condition that the test fails, performing frequent item set query in a historical database through an association rule mining algorithm, and constructing an item set association relationship corresponding to the modified data according to the frequent item set; inputting the change data and the item set association relationship corresponding to the change data into a preset failure data analysis model group, and outputting a test failure reason and a repair suggestion through the preset failure data analysis model group; and based on the test failure reason and the repair suggestion, filling the preset code update meta-language, and repairing the modified data through the filled update meta-language.

The invention relates to the technical field of chemiluminescence immunoassay, and provides a reaction cup transfer control method which comprises the following steps: marking a station where a transfer disc is connected with a slideway as a slideway position, and marking a station where a cup grabbing mechanism grabs a reaction cup on the transfer disc as a cup grabbing position; a first reaction cup sensor is arranged on the transfer disc, and the first reaction cup sensor is used for detecting whether a reaction cup exists at a station on the transfer disc or not; and obtaining the station number without the reaction cup on the transfer disc, and controlling the transfer disc to rotate according to the station number without the reaction cup on the transfer disc. According to the reaction cup transfer control method provided by the invention, empty grabbing caused by insufficient reaction cups in the transfer disc can be prevented, and failure shutdown of an instrument and test failure caused by empty grabbing after supply interruption of the reaction cups are effectively avoided.

The invention discloses a test sequence optimization method and device, equipment and a storage medium. Comprising the steps of obtaining function point related data, and generating a function point test sequence based on an upper confidence bound algorithm; defining a global resource occupancy matrix, and according to the function point test sequence, sequentially importing the function points, traversing and querying the global resource occupancy matrix, and generating a parallel scheduling task; and executing the parallel scheduling task, and monitoring resource conflict conditions and test failure information in real time. By comprehensively considering related data of the function points, intelligent sorting of the function points is achieved, and the problems that in a traditional sorting method, exploration and utilization are difficult to balance and global dynamic optimization is lacked are solved. By reasonably distributing parallel tasks, resource conflicts are avoided, the utilization rate of limited test resources is improved, and efficiency reduction caused by unreasonable resource planning is reduced. Resource conflicts are found and processed in time through real-time monitoring, the conflicts are prevented from influencing the test process, test failures can be quickly responded, and the test efficiency is improved.