63 results about "Memory leak" patented technology

The invention discloses a page assembly type development method and device based on Vue.js and a medium. The method comprises the steps that a page is split into a plurality of independent function components, and each component is packaged into a Vue single file component; defining a corresponding standardized configuration file, analyzing the standardized configuration file, and obtaining a declarative definition of the component; the standardized configuration file comprises a unique identifier, a component name, a component path and an initialization method of the Vue component; in response to the page routing request, calling a dynamic loading function to load a corresponding Vue component, and executing an initialization method of the Vue component; and establishing a mapping relationship between the routing path and the component instance, storing the operation parameters in a cache system, and rendering a page through a keep-alive component of the Vue in combination with the cache system. By means of the method, repeated coding work is reduced, the resource size is reduced, the memory leakage risk is avoided, and the page response speed is increased.

The invention discloses a method and a system for protecting privacy of source codes in memory error detection, belongs to the technical field of computer software security, and particularly relates to a technology for protecting confidentiality of the source codes in a third-party memory error analysis process of software. According to the method, a debugging information minimization processing system DIREDUCER is constructed, a selective deletion and type minimization technology is utilized, on the premise that complete source codes are not exposed, necessary debugging information used for memory error detection is effectively reserved, and dual guarantee of source code privacy and memory error detection effects is achieved. According to the method, the debugging information in the non-stripping binary file is compressed to be within 10% of the original volume, and the recognition capability of an analysis tool on the problems such as memory leak, buffer overflow and overhanging pointers is not remarkably reduced. Experimental results show that the method has good adaptability and expandability in actual deployment, is suitable for various debugging tools and binary analysis frameworks, and has wide application prospects and practical values.

The invention discloses an automatic AI memory leak intelligent positioning and root cause traceability analysis system, and relates to the technical field of memory leak intelligent positioning and root cause traceability analysis. The automatic AI memory leak intelligent positioning and root cause traceability analysis method includes the following steps: S1, data acquisition: performing index acquisition through a multi-dimensional data acquisition unit, and supporting physical memory and virtual memory utilization rate, heap and stack memory allocation and log release, object creation, track destruction and thread execution state index acquisition; according to the automatic AI memory leak intelligent positioning and root cause tracing analysis system, the leak position is positioned, the root cause can be analyzed from dimensions such as code defects, improper configuration and resource competition, the leak recurrence rate is reduced, normal memory fluctuation and a real leak mode are effectively distinguished through sliding window time sequence analysis, exception screening and feature engineering optimization, and the reliability of the system is improved. False alarms are reduced, and the accuracy of abnormal event identification is improved.

This invention discloses an automatic browser memory leak location system, method, and medium based on the MCP protocol, belonging to the field of software testing technology. The system includes an MCP communication module, an automated testing module, a heap snapshot acquisition module, an incremental analysis module, a reference chain analysis module, a SourceMap location module, an intelligent repair module, and an IDE visualization module. This invention establishes a standardized connection between the IDE and the browser debugging port through the MCP protocol, achieving fully automated control; it employs a multi-dimensional fingerprint algorithm based on constructed stack frames and attribute structures to solve the problem of cross-snapshot object matching; it utilizes the dominator tree algorithm to compress the reference chain and combines it with the SourceMap index to achieve source code-level location and AI repair suggestion generation. This invention significantly improves the efficiency and accuracy of memory leak location, solving the problems of fragmented debugging links and the inability to accurately map source code.

The invention discloses a data processing method, a data processing device, a computer readable storage medium, electronic equipment and a computer program product, and the method comprises the steps: obtaining memory usage data and event response data of a target application, and determining the correlation degree of an interaction event and memory leak according to the memory usage data and the event response data, and positioning an interaction event causing the memory leak. Thus, a developer can check the function point corresponding to the interaction event based on the positioned interaction event so as to check whether the function point can cause memory leakage, and compared with a mode that the developer checks all the function points one by one, assistance can be provided for the check work of the developer, so that the check efficiency is improved.

The invention discloses a data distribution method and device and a vehicle, and relates to the technical field of vehicle-mounted electronic system data communication, and the method comprises the steps: carrying out the statistics of application pages subscribing to CAN data, determining a data subscription dynamic list, and enabling the data subscription dynamic list to comprise a corresponding relation between a CAN message ID and the CAN data; monitoring the page state of the application page in real time, and determining a first CAN message ID required by the application page; determining first CAN data corresponding to the first CAN message ID in a data subscription dynamic list according to the corresponding relation; and distributing the first CAN data to the application page through the weak reference holding the application page, thereby avoiding resource waste and memory leakage, and improving the vehicle-mounted information machine fluency.

The application discloses a Linux-based dynamic USB device optimization method, aiming to solve the dimming failure and recognition problem of USB devices during use. Through the hot plug callback mechanism of libusb, the method monitors the insertion and removal events of USB devices in real time, ensuring efficient management of the devices. First, the system records USB device information during initialization and registers the callback function of the hot plug event. When the device is inserted, the program attempts to open the device and declare the interface. If a dimming failure is found, the device is automatically reset to restore normal function. When the device is removed, resources are released to prevent memory leakage. The method is suitable for various USB devices, especially display devices, significantly improving the efficiency of device management and user experience. Through the application, users can more conveniently manage USB devices while ensuring the stability and reliability of display dimming functions.

The embodiment of the invention provides an application monitoring method and device, equipment, a storage medium and a program product, and relates to the field of big data. The method comprises the following steps: in response to a captured memory exception event when a to-be-monitored application runs, acquiring memory stack information corresponding to the memory exception event; wherein the memory exception event comprises at least one of a memory leak event, a memory depletion event and an exceptional memory allocation event; the memory stack information, the crash event data and the operation behavior data are subjected to association analysis, an association analysis result is obtained, and the association analysis result comprises associated transaction identifiers and corresponding memory stack information within a preset duration before the crash triggering time; and according to the correlation analysis result, identifying an abnormal reason of the to-be-monitored application. According to the method, the abnormal problem identification accuracy of the application can be effectively improved.

The invention discloses an inter-thread communication method and device, electronic equipment and a program product, and relates to the technical field of computer software. The method comprises the following steps: receiving a subscription request of a message subscriber; receiving a message of a message sender, wherein the message comprises a synchronous message and an asynchronous message; determining a message subscriber matched with the message according to the identification information in the message; wherein for the asynchronous message, the intelligent pointer pointing to the memory of the asynchronous message is distributed to the message queue corresponding to the matched message subscriber; and for the synchronous message, directly calling a message processing function of the matched message subscriber. According to the method, a message sender does not need to specify a receiver, and the coupling problem of traditional thread communication is effectively solved; unnecessary thread blocking can be avoided through differential processing of the synchronous and asynchronous messages, the memory of the asynchronous messages is managed in combination with the intelligent pointer, the risks of memory leakage and system abnormity are solved, cross-language communication is supported, and the flexibility, reliability and efficiency of communication between the threads are remarkably improved.

The invention belongs to the field of kernel vulnerability analysis of operating systems, and particularly relates to a kernel memory vulnerability cause diagnosis method based on causal chain analysis. The method comprises the steps of restoring a data dependency graph and a function call tree in a vulnerability triggering process from instruction-level tracking data in the vulnerability triggering process, and restoring a kernel execution state and kernel behavior semantics in combination with function modeling; analyzing the kernel execution state, and identifying an abnormal execution behavior in the kernel memory vulnerability in combination with the abnormal model of the kernel memory vulnerability; based on causal chain analysis of dynamic programming, causes of vulnerabilities are analyzed and obtained in a series of kernel execution abnormal behaviors. According to the method, the kernel execution state and behavior semantics are restored, the kernel abnormal behavior state is identified, and the causal chain of the abnormal behavior is analyzed, so that the cause of the kernel memory vulnerability can be effectively diagnosed, and the subsequent vulnerability repair work is promoted.

Embodiments of the present application disclose a memory leakage detection method, related device and equipment, which are used for improving the detection accuracy. The method of the embodiments of the present application comprises: obtaining an object mapping list for a target business module, the target business module indicating a target business type of an application to be detected, the object mapping list being stored in a database and comprising a mapping relationship between an interface identifier and a number of operable objects, the interface identifier being used for uniquely identifying an interface of the target business module. In response to an exit operation for the application to be detected, first operable object data actually corresponding to M interfaces is obtained, the M interfaces comprising interfaces in a running state in the target business module before the application to be detected exits, and M being a positive integer. According to the object mapping list, second operable object data preset for the M interfaces is obtained. In a case where the first operable object data is greater than the second operable object data, it is determined that the target business module has a memory leakage.

The application discloses a message transmission method and device, equipment and a computer readable storage medium. The method comprises the following steps: receiving a first encrypted broadcast message sent by a first message publisher to a first message channel; determining at least one message subscriber corresponding to the first message publisher; monitoring the state of the at least one message subscriber; in the case that the state of a target message subscriber is an active state, sending a first notification message to the target message subscriber to instruct the target message subscriber to acquire and decrypt the first encrypted broadcast message from the first message channel to obtain a first broadcast message; and in the case that all the message subscribers in the active state among the at least one message subscriber have acquired the first broadcast message, deleting the first encrypted broadcast message. According to the embodiment of the application, resource waste and memory leakage can be avoided, and the efficiency, stability and security of information transmission are improved.

The invention relates to the technical field of computer programming, in particular to a priority-based pop-up window management method and system, electronic equipment and a medium. The method comprises the following steps: importing related classes; constructing a suspended function as a corresponding popup task for the popup, and instantiating the asynchronous result container as a decision result container corresponding to the popup task; acquiring the priority of the pop-up window task, and adding the pop-up window task into a pop-up window task queue based on the priority of the pop-up window task through a queuing method of a pop-up window queue manager; starting a coroutine in the coroutine action range, executing the pop-up window tasks in the pop-up window task queue according to the sequence, executing the pop-up window tasks, and obtaining a result value in a corresponding decision result container; if the result value is the preset value, executing the next pop-up window task in the pop-up window task queue in sequence; and if the result value is not the preset value, stopping executing all follow-up window popup tasks. According to the method, interface conflicts and memory leakage risks can be avoided, and the maintainability and reusability of codes are improved.

Embodiments of the invention provide a memory leak detection method and apparatus, and a computing device. The method comprises the steps of obtaining a to-be-tested code; taking the to-be-tested code as the input of the first neural network model, and generating a parameterized test script of the to-be-tested code by using the first neural network model; operating the parameterized test script; in the process of executing the parameterized test script, monitoring runtime data of the to-be-tested code; under the condition that the memory leaks, determining the position of a code causing the memory to leak in the to-be-tested code according to the runtime data; generating a leakage detection report; the leak detection report includes a code location and a test execution path. By adopting the method, the leak behavior of the to-be-tested code is verified by dynamically executing the parameterized test script, and the memory leak point is specifically positioned, so that the accuracy and comprehensiveness of detection can be effectively improved.

The invention provides a video page rendering method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a viewport position and a current action of a user in a process that the user browses a page, and dynamically requesting image resources according to an acquisition result; according to the action of the user on the video content, three-level cache processing is carried out, and the cache used by the browser is reasonably distributed; furthermore, the hardware and software configuration of the equipment is detected, for the equipment with lower configuration, the image to be rendered is split into a plurality of smaller image blocks and then is distributed to a plurality of WebGL contexts for asynchronous rendering in the background, and the main thread is not blocked while the rendering performance is greatly optimized. In addition, the WebGL textures are managed by adopting a strong reference mechanism and a weak reference mechanism, so that a large number of unused WebGL textures can be effectively prevented from being accumulated in the background, thereby avoiding memory leakage and excessive memory occupation, and ensuring stability and high efficiency when the user browses the video page for a long time.

The application relates to an artificial intelligence-based full-stack application systematic optimization method, which comprises the following steps: realizing full-link data collection through an intelligent probe; data preprocessing; inputting the preprocessed data into a professional model system, identifying memory leakage risks, correlatively analyzing hardware indexes and application performance indexes, and locating root cause problems; generating a dynamic optimization strategy, generating optimization parameters, and injecting the target system; establishing a standardized feedback data collection mechanism, collecting key performance indexes every predetermined time, and evaluating the optimization result by comparing the key performance index fluctuation before and after optimization. The application can realize intelligentization, dynamicization and cross-level collaborative optimization of system performance.

This invention discloses an autonomous evolutionary AGI system and method based on dual-model decoupling and human feedback, belonging to the field of artificial intelligence technology. The system includes modules for online inference (Model A), offline training (Model B), human feedback rewards, persistent storage, training scheduling, model hot replacement, distributed communication, and a secure sandbox. This invention decouples inference and training to ensure service continuity; anchors value direction with human ratings to avoid drift; employs dual-condition triggering training to improve resource efficiency; achieves seamless updates through hot replacement; avoids memory leaks through database persistence; enables multi-machine expansion through distributed architecture; and ensures execution security through a sandbox. This invention enables 24 / 7 online, controllable, and secure autonomous evolution of AGI, suitable for code generation, intelligent agents, automated R&D, and general artificial intelligence scenarios.

A technique dynamically configures a memory bank in a slumber state that maintains power to an array of bit cells but powers down periphery logic of the memory bank to reduce power consumption by an integrated circuit system in an active mode of operation. The memory bank includes periphery logic and an array of storage elements that are configured to receive power from different power domains and powers down the periphery circuits when the access frequency for the memory bank is below a predetermined access frequency. Slumber control logic determines whether the memory bank has been accessed in a previous interval defined by a predetermined number of clock cycles. If the memory bank has not been accessed in the previous interval, then the slumber control logic configures the memory bank in the slumber state.

The invention relates to a method, a system and equipment for checking memory leakage of a big data cluster in a smart park and a medium. The positioning method comprises the following steps: screening abnormal nodes; performing cross validation on the memory occupation condition of the abnormal node through a host monitoring tool and an operating system command to judge whether the abnormal node is a system-level memory anomaly or an application-level memory anomaly; reversely searching a corresponding application identifier according to a process identifier with high memory occupancy on an abnormal node with an abnormal application-level memory; and performing space-time correlation analysis on the application corresponding to the searched application identifier. According to the smart park big data cluster memory leak checking method, system and device and the medium, through multi-source data cross validation and hierarchical progressive analysis, accurate positioning and efficient handling of the memory leak problem are achieved.

A method, apparatus, device, and computer-readable storage medium for locating leaks in buffer objects are disclosed. The method involves identifying first buffer objects in a used state from a memory pool and obtaining lifecycle data for each first buffer object, wherein the lifecycle data includes the allocation time and current stage of the first buffer object, as well as the latest update time of the lifecycle data. Based on a first mapping relationship, the allocation time and current stage of each first buffer object, second buffer objects that have timed out are selected from all first buffer objects. Based on a second mapping relationship, the current stage and latest update time of each second buffer object, leaked buffer objects that have timed out are selected from all second buffer objects. This application improves detection accuracy and efficiency, reduces the probability of false positives for memory leaks, and is adaptable to different business stages, thus improving versatility.

The application provides a memory management method and device in an electric energy meter, and relates to the technical field of electric energy meters.A memory application record table is constructed as a unique management hub, a record set to be released is accurately determined by executing a program to query the record table, the integrity of the release target is ensured, and memory omission release is avoided.According to the memory data model type in the record, a preset release program is associated, the release logic is strictly matched with the data structure, and logical errors introduced by manual writing are eliminated.The release program is used to automatically release the memory from the inside to the outside according to the nesting level, the order problem of the memory release of complex nested objects is solved, memory leakage or access exceptions are prevented, and finally, the corresponding entries of the record table are deleted after the release, the consistency between the record table and the physical memory state is maintained in real time, the problem that the memory of the electric energy meter is prone to leakage is solved, the effective release of the memory of the electric energy meter is realized, and the reliability of the electric energy meter operation is improved.

The invention discloses a memory management method and device, equipment, a storage medium and a program product, for a communication module with a dual-core processor, when the communication module is started, memory parameters are updated, so that the memory space of the dual-core processor is loaded by utilizing the updated memory parameters, the dynamic adjustment of the memory space can be realized, and the memory management efficiency is improved. And the utilization efficiency of memory space is improved. Besides, dynamic memories in small spaces are distributed and managed in a virtual heap mode, memory fragments in shared memory spaces and independent dynamic memory spaces are reduced, and the utilization efficiency of the memory spaces is further improved. Moreover, the dynamic memory application management method based on the linked list can effectively avoid memory leakage.

The invention discloses a display interface management method of embedded equipment and related equipment thereof, and the method comprises the following steps of: decoupling interface logic and display data by adopting a layered interface architecture and an event-driven mechanism and separating a basic canvas layer, an interface layer and a dynamic data layer; user input, a sensor state and a storage signal are monitored by using an independent event thread, and local updating or interface switching is performed based on message content, so that resource waste and response delay caused by a traditional polling mode are effectively avoided; the local refreshing mechanism only updates affected components, so that the CPU load and the memory occupation are remarkably reduced; and during interface switching, old resources are thoroughly destroyed, and a new interface layer is reconstructed, so that memory leakage and interface residue are prevented. According to the method, a matched event monitoring and response mechanism is set for display interface management of the embedded equipment, so that the resource management stability during interface switching is ensured, and the interface response speed and the display fluency are improved.

The invention provides a process control method and device, equipment and a storage medium, and the process control method in the application comprises the following steps: in response to a process control request, obtaining process memory data of a background running process and reference memory data of the background running process; determining memory deviation data of the background running process according to the process memory data and the reference memory data; if the memory deviation data is greater than a preset memory deviation threshold, determining memory evaluation data of the background running process based on the process memory data and historical memory data; and performing memory control processing on the background running process by utilizing the memory evaluation data to obtain a memory control result. According to the technical scheme, effective memory control can be intelligently carried out on the background running process with memory occupation abnormity or memory leakage, so that the memory pressure of the terminal is reduced, and the running fluency of the foreground application is improved.

The invention discloses a memory leak processing method and a related device, and relates to the technical field of data processing, semantic analysis is performed on a reference chain of memory leak to obtain leak type diagnosis information, and the leak type diagnosis information is converted into a formatted diagnosis report; the formatted diagnosis report comprises a first report used for a large language model, the large language model is called based on a cue word to output repair information, the repair information is used for repairing a target code, and the cue word is obtained based on the diagnosis report and the target code. The reference chain of the memory leak is converted into the diagnosis report beneficial to understanding of the large language model, so that the repair information can be obtained based on the large language model, the degree of dependence of repair on manpower is reduced, and the processing mode of the memory leak is improved.

The invention provides a memory management method and system, electronic equipment and a storage medium. Java processes are called to initialize and load a TCMalloc library and a JNI interface, and the TCMalloc library is accessed through the JNI interface; the monitoring thread is started, the TCMalloc library is called through the monitoring thread to query the use condition of the out-of-heap memory, and distribution of the out-of-heap memory is carried out through the TCMalloc library; performing trend analysis according to the use condition of the out-of-heap memory, and performing leak detection on the out-of-heap memory according to a trend analysis result to obtain a first leak detection result of the out-of-heap memory; and if the first leak detection result indicates that the out-of-heap memory leaks, executing a corresponding memory release operation on the out-of-heap memory through the TCMalloc library.

The invention discloses a data auditing system for big data. Through cooperative operation of the flow processing component, the protocol analysis component and the rule matching component, full-link automatic monitoring and risk identification of database access behaviors are realized. The traffic processing component comprises a traffic preprocessing and recombining module; the traffic preprocessing component identifies database service traffic based on a quintuple, executes de-duplication, out-of-order message sorting and check cleaning, and outputs a preprocessed data packet; and the traffic recombination component restores the complete TCP session data according to the TCP serial number or the ACK number, and supports overtime cleaning to avoid memory leakage. And the protocol analysis component automatically identifies a database protocol type, unpacks and extracts terminal information, server information and operation information, and generates a structured analysis result. And the rule matching component is combined with predefined security rules or custom strategies to match key features, generate behavior logs and record risk details. According to the invention, the server can be automatically and comprehensively tested, and the inspection report is generated.

The invention discloses a memory leak analysis method and system based on an IVI log, electronic equipment and a storage medium, and relates to the field of in-vehicle machine memory data analysis, the method comprises the following steps: receiving an input parameter, determining an IVI log type, an analysis index and target application information, and obtaining analysis log data; according to the input parameters, loading a corresponding log file and carrying out text analysis; processing the analyzed log data, extracting effective data, and transferring the effective data into a database; performing fitting processing on the effective data by adopting a polynomial regression algorithm, and converting discrete data into a continuous curve; performing slope trend analysis on the fitted continuous curve, including deriving a fitting function corresponding to the continuous curve; calculating slope values of the curve at the plurality of data points based on the derivative function; analyzing the overall change trend of the slope value, and judging that the corresponding program has a memory leak risk; outputting a program name list with the memory leak risk; and displaying the effective data in a graphical mode.

The embodiment of the invention provides a method, a device and equipment for determining memory leak time. The method comprises the following steps: inputting a memory feature matrix corresponding to memory feature data into a target model to obtain a target probability; and under the condition that the target probability is greater than a preset target threshold value, determining the memory leakage time according to the growth rate of the value of the memory feature data in the preset time period and a preset memory alarm threshold value. The target probability of the memory feature data is calculated through the target model, and under the condition that the target probability is larger than the preset target threshold value, the memory leakage time is determined by calculating the growth rate of the value of the memory feature data in the preset time period and the preset memory alarm threshold value, so that early warning of memory leakage is realized, and the memory leakage time is shortened. Therefore, the risk of memory leakage is reduced, and the utilization rate of the memory is improved. And moreover, the utilization rate of the memory is improved, and the memory which is ineffectively occupied by the system within the memory leakage time is reduced, so that the probability of jamming of the system due to excessive memory occupation can be reduced.

The invention provides a throttling implementation method and system based on a Vue custom instruction, a medium and equipment, and the method comprises the steps: creating a throttling core function based on a Vue framework, returning a target function of throttling packaging according to the target function, and determining the Vue-based custom instruction; based on a throttling core function in the Vue custom instruction, a preset timestamp comparison algorithm is adopted to control the execution frequency of a target function; constructing an instruction definition object based on the Vue custom instruction; and controlling the execution frequency of the original event processing function by adopting a Vue-based custom instruction. Through the application, throttling control is realized based on the Vue custom instruction, code redundancy is reduced, complex configuration is reduced, development efficiency is improved, millisecond-level precision control and 100% context binding accuracy are realized, and the risk of memory leakage is reduced.