68 results about "Memory leak detection" patented technology

The invention discloses a method for positioning memory leak, which relates to the field of computer science and technology, and comprises the following steps of: initializing a memory use monitoring module, setting an initial memory use rate threshold, and defining a threshold adjustment parameter; the CPU utilization rate and the memory use condition are monitored in real time, historical data are recorded, and a memory use trend model is established. When the CPU utilization rate exceeds the set threshold value, reducing the first preset threshold value, adjusting the second preset threshold value according to the memory use trend, and comprehensively adjusting the memory utilization rate threshold value. And when the memory utilization rate exceeds a first preset threshold value, starting memory leak detection, recording memory allocation and release information by using a hash table, and searching the unreleased memory. And analyzing logs and behavior records of the system before and after memory leak, constructing a causal relationship model, adjusting a memory utilization rate threshold value, and generating a report containing memory leak position and reason analysis thereof. According to the method, the predictability and the accuracy of memory management are better improved, and the self-adaptive capability of the system is enhanced.

The present application belongs to the technical field of terminal devices. Disclosed are a memory leak detection method and apparatus, an electronic device and a readable storage medium. The method comprises: acquiring actual physical memory data of at least one second process periodically reported by a first process, the first process being a process having a ROOT permission, and the at least one second process being a process currently run by an electronic device; and, when it is determined, on the basis of the actual physical memory data of a second process acquired multiple times in succession, that a memory growth trend of the second process meets a preset condition, determining that the second process has memory leak, the second process being any process of the at least one first process.

The invention relates to a component memory leak detection method and device, computer equipment and a storage medium. The method comprises the following steps: when a component creation event of a to-be-detected component is detected, generating a first heap snapshot corresponding to the component creation event of the to-be-detected component, and when a component destruction event of the to-be-detected component is detected, generating a second heap snapshot corresponding to the component destruction event of the to-be-detected component; analyzing the first heap snapshot and the second heap snapshot, and determining target structured data; component instance nodes are determined, and an information mapping table between node unique identifiers and node information of the component instance nodes is constructed; determining candidate memory leak components according to the information mapping table; and determining a target memory leak component from the candidate memory leak components according to the component-created document object model and the component-destroyed document object model of the candidate memory leak components. And the identification precision of the component memory leak scene is improved.

The invention discloses a memory leak detection method and device, equipment and a storage medium, and the method comprises the steps: regularly reading the total memory usage amount at the current moment according to a preset detection frequency, and calculating the memory usage proportion at the current moment according to the total memory usage amount; if the memory use proportion is greater than a proportion threshold value, shooting a heap snapshot at the current moment; obtaining a historical heap snapshot; comparing the heap snapshots at the current moment with historical heap snapshots to identify one or more suspected leakage points; and analyzing the reference relationship of each leakage suspected point to determine each leakage node. According to the method, the macroscopic memory use proportion and the specific microcosmic structure of the heap snapshots are effectively associated, suspected abnormally increased or unreleased objects in the time dimension are accurately captured through comparison information of the heap snapshots, then code roots causing leakage are traced through the reference relation, the leaked nodes are accurately determined, and the leakage efficiency of the heap snapshots is improved. Compared with a manual operation mode in the prior art, efficiency and accuracy are greatly improved.

The Android system memory management optimization method is characterized by comprising the following steps: (1) memory fragment arrangement: (1-1) fragment detection and classification; (1-2) fragment merging; (1-3) rearranging memory blocks; (2) memory leak detection: (2-1) reference chain analysis; (2-2) garbage collection monitoring; (2-3) memory leak repair suggestion; (3) memory allocation optimization: (3-1) memory pool management; (3-2) dynamically adjusting the size of a memory block; (3-3) multiplexing the memory blocks; (4) a memory allocation strategy under multi-task processing: (4-1) task priority evaluation; (4-2) memory sharing; and (4-3) a memory recovery strategy. According to the method, the memory utilization rate of the Android system is improved, memory leakage is reduced, the memory allocation efficiency is improved, and memory allocation under multi-task processing is optimized.

The invention discloses a memory leak detection method and device based on a Vue framework and a medium, belongs to the technical field of memory leak detection, and is used for solving the technical problems that an existing memory leak solution cannot accurately identify and position a source of memory leak, cannot provide an effective optimization strategy and is poor in stability and performance of a Vue.js application. The method comprises the following steps: regularly obtaining memory usage data of a Vue application, and carrying out memory usage monitoring on the Vue application based on the memory usage data; when the memory occupancy exceeds a first preset threshold value, performing memory recovery on the memory of the Vue application; performing memory leak detection on the Vue application through a memory analyzer; and when memory leak occurs, recovering the isolated object in the Vue application so as to automatically repair the memory.

The invention discloses a memory leak detection method and device based on KNN and a medium, belongs to the technical field of intelligent operation and maintenance, and is used for solving the technical problems that an existing memory anomaly detection algorithm is mainly oriented to universal memory faults such as resource bottleneck and insufficient capacity and is not accurate enough in memory leak fault recognition and lagged in fault recognition. The method comprises the following steps: acquiring a memory monitoring index data set of a target system in a preset time period; determining whether any data point is an abnormal point or not based on the distance between any data point in the memory monitoring index data set and other data points; and if the number of the abnormal points in the memory monitoring index data set exceeds a preset number threshold, determining that the target system has a memory leak fault. By means of the method, targeted fault detection on specific fault scenes such as memory leakage is achieved, and when the target system has the memory leakage fault, the fault of memory leakage of the target system can be accurately and timely detected.

The invention discloses a memory leak detection method and device, electronic equipment and a storage medium, and relates to the technical field of big data or other related fields, and the method comprises the steps that in the execution process of a target process, a memory event of the target process is monitored, and a monitoring result is obtained, the memory event is used for indicating the change conditions of the virtual memory and the physical memory; establishing a virtual memory allocation table and a physical memory allocation table based on a monitoring result; based on a preset detection rule, the virtual memory allocation table and the physical memory allocation table are compared to obtain a comparison result, and the comparison result is used for recording R stack identifiers; and taking R call stacks corresponding to the R stack identifiers as suspected leak memories, and generating a memory leak detection result. According to the method and the device, the technical problem that the memory leak cannot be effectively detected when the Java program runs due to the fact that the monitoring and analysis capability on the Java memory object is insufficient in the related technology is solved.

The embodiment of the invention provides a memory leak detection method and device, equipment and a storage medium, and relates to the technical field of operating systems and performance tuning. The method comprises the following steps: monitoring memory allocation and release operation of a process by adopting a probe program; collecting memory use information of a stack of the process on memory allocation and release operation; through a collaborative caching mechanism of a kernel mode and a user mode, sharing memory use information to the user mode, and analyzing the memory use information in the user mode to obtain a comprehensive hotspot score representing a memory occupation growth trend of a stack; and determining whether the stack has memory leak according to the comprehensive hotspot score. Based on the method, whether the memory leaks or not can be accurately detected under the condition of low performance overhead.

The invention provides a detection method, device and system applied to periodic memory leak, the method is applied to first electronic equipment, a full pointer list is generated by counting memory applications, and the full pointer list comprises a first feature and a second feature. And dividing the records with the same second feature into sub pointer lists, and further determining a target pointer list set of which the timestamps are regularly increased. And transmitting the target pointer list and the memory data through a communication protocol with the second electronic equipment so as to identify a memory leak pointer value. According to the method, the first electronic equipment can effectively screen and transmit the target pointer list and the memory data to the second electronic equipment, the pointer list with the timestamps increasing regularly is analyzed in a centralized mode, the timestamps increasing regularly are obvious marks of memory leakage in a period, the accuracy and efficiency of detection are improved, and the detection efficiency is improved. And the specific analysis part is performed at the second electronic equipment end, so that the operation pressure of the first electronic equipment is reduced, and the operation efficiency of the first electronic equipment is guaranteed.

The invention discloses a memory allocation system with a memory monitoring and early warning system, and relates to the technical field of memory management. Comprising a memory pool management module, a memory pool debugging module, a memory monitoring and early warning module, a memory leak detection module, a dual release detection module, a memory usage amount statistics module and a wild pointer positioning module. By integrating the memory pool management module, the debugging module and the monitoring and early warning module, memory management in the embedded system is optimized, the system can dynamically allocate memories, record operation, monitor abnormal use of the memories in real time and position the problems of memory leakage, wild pointers and the like, the safety and efficiency of memory use are improved, the positioning and solving of the problems are accelerated, and the system is suitable for large-scale popularization and application. And the system stability is enhanced.

The application provides a detection method, device and system applied to periodic memory leakage, the method is applied to a first electronic device, a full pointer list is generated by counting memory application, containing a first feature and a second feature. Records with the same second feature are divided into sub-pointer lists, and then a target pointer list set with regularly increasing time stamps is determined. Through a communication protocol with a second electronic device, the target pointer list and memory data are transmitted to identify memory leakage pointer values. The first electronic device can effectively screen and transmit the target pointer list and memory data to the second electronic device, the method concentrates on analyzing the pointer list with regularly increasing time stamps, the regularly increasing time stamps are obvious signs of periodic memory leakage, the accuracy and efficiency of detection are improved, and specific analysis is performed on the second electronic device side, thereby reducing the operation pressure of the first electronic device and ensuring the operation efficiency of the first electronic device.

This application relates to the field of data destruction and provides a method, apparatus, device, storage medium, and program product for detecting memory leaks. The method includes: creating destruction tasks for multiple volumes to be destroyed and assigning these tasks to multiple nodes; obtaining the number of destruction tasks being executed by each node under different operating states and the load balancing conditions; and determining whether the destruction tasks are in a load-balanced state based on the number of destruction tasks being executed by each node under different operating states and the load balancing conditions. By assigning multiple destruction tasks to nodes and determining whether the destruction tasks are load-balanced based on whether the number of destruction tasks being executed by each node meets the load balancing conditions, the time-consuming and laborious problem of manually checking whether the destruction tasks are load-balanced is avoided, achieving efficient and rapid verification of whether the storage system is load-balanced during the data destruction process.

Automatic memory leak detection is presented herein. An example method comprises, receiving, into a data slot of a defined data structure, a flow of memory usage data sent by a resource monitoring process operational on the system, in response to determining a time value exceeding a defined threshold time value, closing the data slot, based on the memory usage data included in the data slot, executing a trend analysis process using the memory usage data as an input to the trend analysis process, and in response to the trend analysis process determining a trend associated with the memory usage data, transmitting notification data representing the trend and recommendation data representing a suggestion to reverse the trend to a user equipment.

The embodiment of the invention provides a memory leak detection method, electronic equipment and a storage medium, and relates to the technical field of memory management, the method comprises the following steps: obtaining a to-be-detected source code; traversing the to-be-detected source code, and determining a target message processing class in the to-be-detected source code; for each target message processing class, determining a target message processing object corresponding to the target message processing class; determining the reference count of each target message processing object based on the calling relationship of each target message processing object; the reference count of one target message processing object represents the number of times that the target message processing object is referenced; based on the reference count of each target message processing object, generating a memory leak detection result; the detection result comprises the message processing object with the memory leak, and the accuracy of memory leak detection can be improved.

The present application discloses a memory leak detection method, an electronic device and a storage medium, which relate to the field of memory management technology and are used to provide a memory leak detection solution to ensure the stability and security of memory management. The method comprises: in response to the memory of a Java heap being greater than a first memory threshold, based on a target subprocess in an application process, obtaining a Java object reference relationship of the Java heap; based on the Java object reference relationship, determining at least one Java object in the Java heap whose memory is in a running state; and in the at least one Java object, determining that a Java object that meets a memory exception condition is a Java object with a memory leak.

The invention provides a method, device and equipment for intelligently detecting gateway memory leak and a medium, and the method comprises the steps: deploying a lightweight AI prediction model at a main gateway, and carrying out the online learning of a memory leak mode and real-time reasoning; the slave gateway collects memory data, preprocesses the memory data, generates a memory change trend vector by adopting a dynamic sliding window, and transmits the memory change trend vector to the master gateway; the main gateway analyzes the memory change trend vector transmitted by the slave device in real time through an AI prediction model, identifies a potential leakage mode of the memory change trend vector, and performs graded early warning on an identification result; constructing a lightweight graph neural network to analyze a memory dependency relationship, evaluating a repair measure influence range, and dynamically selecting an optimal repair strategy for equipment needing to be repaired according to a historical repair effect in combination with a reinforcement learning model; and regularly carrying out data statistics and generating a whole-network visual predictive report. According to the invention, memory leak detection, classified statistics and intelligent alarm of the master / slave gateway can be realized, and the network stability is improved.

The present invention discloses a method for locating memory leaks, which relates to the field of computer science and technology. The method includes initializing a memory usage monitoring module, setting an initial memory usage rate threshold, and defining a threshold adjustment parameter. It monitors the CPU utilization rate and memory usage in real time, records historical data, and establishes a memory usage trend model. When the CPU utilization rate exceeds the set threshold, it reduces the first preset threshold and adjusts the second preset threshold according to the memory usage trend, comprehensively adjusting the memory usage rate threshold. When the memory usage rate exceeds the first preset threshold, it starts memory leak detection, uses a hash table to record memory allocation and release information, and searches for unreleased memory. It analyzes the system logs and behavior records before and after the memory leak, constructs a causal relationship model, adjusts the memory usage rate threshold, and generates a report containing the location of the memory leak and its cause analysis. The present invention better improves the predictability and accuracy of memory management and enhances the adaptive ability of the system.

Automatic memory leak detection is presented herein. An example method comprises, receiving, into a data slot of a defined data structure, a flow of memory usage data sent by a resource monitoring process operational on the system, in response to determining a time value exceeding a defined threshold time value, closing the data slot, based on the memory usage data included in the data slot, executing a trend analysis process using the memory usage data as an input to the trend analysis process, and in response to the trend analysis process determining a trend associated with the memory usage data, transmitting notification data representing the trend and recommendation data representing a suggestion to reverse the trend to a user equipment.

The invention provides a memory leak detection method, device and equipment, a medium and a computer program product, and relates to the technical field of computers, in particular to the field of cloud computing. According to the specific implementation scheme, at least one second memory page which is not counted by an operating system is obtained from distributed first memory pages, and the second memory page is a memory page applied by a process for calling a drive program; memory allocation information corresponding to any second memory page is obtained, wherein the memory allocation information is used for indicating a calling path of the driving program; determining the memory occupation amount of any calling path based on the memory allocation information; and performing memory leak detection on the operating system based on the memory occupancy of any calling path.

The present invention discloses a memory leak detection method and device, relating to the field of computer technology. A specific implementation of the method includes: upon entering a page to be detected in an application, initializing a view controller and at least one view of the page to be detected, and storing characteristic information of the view controller and the view in a pre-established weak reference set; after exiting the page to be detected, determining whether a memory leak has occurred in the page to be detected based on the information currently stored in the weak reference set. This implementation can quickly determine whether a memory leak has occurred in the page to be detected in an application.

The invention provides a memory leak detection and analysis method, system and device and a medium, and belongs to the technical field of memory detection. Memory use data based on an application program is obtained and stored; based on a memory analysis module, analyzing the memory use data, and identifying a memory leak position and memory leak data; key information of the memory leak data is extracted, and a memory leak data report is generated; and displaying the memory usage amount and the leakage mode through a graphical interface. According to the method, the existing memory leak detection technology is highly fused, and the advanced visual analysis technology is adopted, so that the detection accuracy and efficiency are improved, the security of the system is enhanced, and an efficient, convenient and reliable memory leak solution is provided for a user.

Embodiments of the present application disclose a memory leakage processing method and device, a storage medium and an electronic device. The method comprises: collecting all objects held by a view controller when the view controller disappears, determining target objects with memory leakage from all the objects, and sending a target message indicating that the target objects have memory leakage to a server based on the target objects. The scheme expands the detection range of memory leakage and improves the detection coverage, can more comprehensively detect objects with memory leakage, and uploads the collected memory leakage information to the server and distributes it to relevant personnel for processing, avoiding the impact of memory leakage detection in the testing stage.

The invention provides a memory leak detection method and device, a storage medium and an electronic device.The method comprises the steps that index data of a process used memory in a target network element is collected locally according to a first preset period, and the index data is used for representing the memory occupancy amount of the corresponding process; the index data is stored in a time sequence database of the target network element, and the time sequence database is used for storing index time sequence data of all processes in the target network element in a plurality of time sequence periods; querying index time sequence data in the time sequence database according to a second preset period; and adopting a pre-trained deep learning model to perform memory leak detection on the target network element through the index time sequence data. Through the embodiment of the invention, the technical problems of large resource consumption and large time delay of memory leak detection in related technologies are solved, the memory leak of a specific module can be detected besides the process memory leak, and a leak root cause can be conveniently positioned in time.

The invention discloses an Android MTK platform memory leak detection method combined with Python data analysis, and relates to the technical field of Android MTK platform memory leak analysis and troubleshooting, and the method comprises the following steps: S1, system log classification; s2, sorting memory occupation information; s3, outputting a memory occupation broken line graph of each application process; and S4, memory leak judgment. According to the Android MTK platform memory leak detection method combined with Python data analysis, the memory problem of a system process is analyzed very visually, the limitation that only developers can analyze memory leak is broken through, testers execute according to steps, application processes with system memory leak can also be distinguished, the method can be used for system stability testing, and the test efficiency is improved. Data analysis is carried out from the overall dimension of the system, and the limitation that a previous scheme can only aim at a single application process is broken through.

The embodiment of the application provides a memory leakage detection method and electronic equipment, relates to the terminal technical field, and can accurately detect the memory leakage problem of the application in the electronic equipment. The electronic equipment comprises a first process and a second process, and the method comprises the following steps: acquiring first memory information corresponding to the first process and second memory information corresponding to the second process; determining that the first process meets a preset condition and the second process does not meet the preset condition according to the first memory information corresponding to the first process and the second memory information corresponding to the second process; acquiring third memory information corresponding to the first process; and judging whether the first process has memory leakage or not according to the third memory information corresponding to the first process.

The invention discloses a method for analyzing a pointer of a swan Mongolia ArkTS cache component based on static analysis, which comprises the following steps of: screening AppStorage-related APIs (Application Program Interface) through three-address code semantic modeling, constructing a bidirectional synchronous strong connected component by adopting a reverse backflow edge, and blocking unidirectional synchronous reverse propagation based on freezing constraint, so as to achieve the purpose of analyzing the pointer of the swan Mongolia ArkTS cache component. And realizing cross-component data stream accurate tracking by combining a dynamic pointer assignment graph and an accessibility algorithm. According to the method, the false alarm rate of pointer analysis is reduced from 20% to 5%, the accuracy rate of memory leak detection reaches 98%, the analysis efficiency is improved by 40%-60%, the method is compatible with an OpenHarmony tool chain, and the problems of memory security and optimization under an ArkTS response type synchronization mechanism are solved.

The embodiment of the invention provides a memory leak detection method and device, and relates to the technical field of computers.The method comprises the steps that memory data of a plurality of target functions in a target application program are obtained through a pre-injected memory probe, the memory probe is injected into the target function in a compiling stage or a linking stage of the target application program; determining memory leak data of the target function based on the memory data; and under the condition that the memory leak data meets a preset leak condition, executing a preset alarm operation. According to the technical scheme provided by the embodiment of the invention, function-level memory leak monitoring can be realized, and memory leak detection is effectively realized.

The embodiment of the invention discloses a data processing task scheduling method and device, electronic equipment and a medium. A specific embodiment of the method comprises the steps of obtaining a memory capacity set required by task operation and memory capacity of an application server; generating the current required memory capacity; determining a task execution mode; performing memory scheduling on the current data processing task and the target data processing task set to obtain task scheduling information; executing the current data processing task and the target data processing task set to obtain task execution information; in response to determining that the task execution information represents execution abnormity, performing memory leak detection on the task execution information to obtain a task memory detection result; and according to a task memory detection result, performing memory resource recovery on required memories corresponding to the current data processing task and the target data processing task set. According to the embodiment, smooth execution of the data processing task can be improved, waste of memory resources is reduced, and the stability of a system for executing the data processing task is improved.