14 results about "Memory profiling" patented technology

The invention provides a communication driver and interface construction automation solution providing method, device and system for machinery equipment. The system may comprise a memory for storing instructions and a processor. Instructions, when executed by a processor, provide a universal driver, the system can communicate with PLCs of a plurality of manufacturers, receive address mapping data in the form of Excel files and automatically analyze the data through a memory analyzer, generate PLC I / O mapping according to the analyzed data, automatically generate corresponding source codes, compile generated source codes, and send the generated source codes to the processor. And automatically linking the compiled program with the PLC I / O, and automatically generating and storing a log generated in the system operation process. The system automatically analyzes stored log files to assess system performance and errors, visualizes equipment states and test consistency line by line according to analysis results, and controls and provides the results to a user terminal.

The invention discloses a memory data analysis method and device, electronic equipment and a storage medium, and relates to the technical field of computers.The method comprises the steps that original memory data is sorted, and target memory data based on a reference relation is obtained; wherein the original memory data comprises a memory use condition and object reference relation data; and performing visual analysis on the target memory data. According to the method, the target memory data based on the reference relationship is organized and generated, so that the actual reference chain between the objects can be revealed, a developer is helped to accurately grasp the object life cycle and the memory occupation condition, and the memory analysis accuracy is improved; the target memory data is visualized, and the hierarchical structure and association between the objects can be displayed, so that optimization of performance analysis is facilitated.

Aspects of the present disclosure relate to retrospective memory analysis. In examples, a historical archive of memory images for an execution environment is maintained. A historical memory image of the historical archive may be evaluated according to a current set of known issues, rather than issues that were known at the time of the memory capture. Accordingly, it may be possible to determine when the execution environment was last in a good environment condition. As another example, it may be possible to determine whether a now-known issue has since been resolved (e.g., such that the issue would not be identified in the current execution environment). Thus, as compared to contemporaneous issue identification techniques, aspects of the present disclosure may be applied to any number of execution environments to enable retrospective identification of now-known issues that were, at least at the time of a memory capture, not known.

The embodiment of the invention provides a vehicle-mounted application memory occupation detection method and device, computer equipment and a storage medium. The method comprises the steps that a to-be-detected vehicle-mounted application is split into a plurality of assemblies; for each component, recording a test script of the current component by using a preset script recording tool; based on a preset memory analysis tool and a memory index script, performing pressure test on the current component according to the test script of the current component; and based on a preset memory occupation sample and a memory occupation standard, determining whether the memory occupation of the to-be-detected vehicle-mounted application is abnormal according to the memory snapshot file and the memory index obtained by the pressure test, and detecting whether the memory occupation of the to-be-detected vehicle-mounted application meets the standard of the vehicle-mounted equipment in the high-frequency and high-strength long-time use process of the vehicle-mounted application. Whether abnormal conditions of memory leak and memory jitter exist or not is judged, and it is ensured that the vehicle-mounted application is kept in a running state in a complex environment or is paused and recovered at a proper time so as to meet user requirements.

Methods and apparatus consistent with the present disclosure may use instrumentation code that remains transparent to an application program that the instrumentation code has been injected into. In certain instances, data sets that include executable code may be received via packetized communications or be received via other means, such as, receiving a file from a data store. The present technique allows a processor executing instrumentation code to monitor actions performed by the program code included in a received data set. Malware may be detected by scanning suspect program code with a malware scanner, malware may be detected by identifying suspicious actions performed by a set of program code, or malware may be detected by a combination of such techniques.

Methods and apparatus consistent with the present disclosure may use instrumentation code that remains transparent to an application program that the instrumentation code has been injected into. In certain instances, data sets that include executable code may be received via packetized communications or be received via other means, such as, receiving a file from a data store. The present technique allows a processor executing instrumentation code to monitor actions performed by the program code included in a received data set. Malware may be detected by scanning suspect program code with a malware scanner, malware may be detected by identifying suspicious actions performed by a set of program code, or malware may be detected by a combination of such techniques.

The invention provides a computer memory release system based on data analysis, and relates to the technical field of computer memory management. The system comprises a memory data acquisition module, a multi-dimensional memory analysis module, an intelligent release decision module, a hierarchical release execution module and a memory fragment optimization module. The memory data acquisition module acquires and preprocesses data by adopting kernel mode and user mode dual channels; the multi-dimensional memory analysis module realizes process memory consumption mode recognition and release potential calculation through feature matrix construction, improved LSTM network prediction and entropy weight method evaluation; the intelligent release decision-making module realizes dynamic decision-making based on an AHP model in combination with scene adaptation; the hierarchical release execution module adopts a three-stage mechanism of pre-cleaning, verification and release to guarantee safe release; and the memory fragment optimization module realizes free block integration and closed-loop feedback. The system solves the problems that a traditional memory is slow in release response, blind in release and poor in stability.

This invention discloses a vulnerability exploitation agent system, method, and apparatus based on the driving engineering framework, relating to the field of artificial intelligence, to address the vulnerability problem in the autonomous execution of long-chain tasks by vulnerability exploitation agents. It constructs a vulnerability exploitation agent system comprising an environment perception and object representation layer, an execution layer, an orchestration layer, a memory layer, a semantic management layer, and a security layer. Based on the logic of global constraint pre-positioning – progressive information disclosure – full-link behavior control – autonomous closed-loop execution – standardized output of results, it leverages the core mechanisms of the driving engineering framework, such as event-driven interception and verification bus, dynamic loading of prompts, memory compression, autonomous task execution loop, and tool permission gating, to form a fully traceable vulnerability exploitation scheme. This application can solve the problems of difficult binary semantic analysis and memory analysis in long-chain vulnerability exploitation tasks, improving task execution efficiency and accuracy.

The present invention discloses a memory leak detection method, device, and medium based on the Vue framework. These methods belong to the field of memory leak detection technology and are used to address the technical issues of existing memory leak solutions, which are unable to accurately identify and locate the source of memory leaks, fail to provide effective optimization strategies, and suffer from poor stability and performance of Vue.js applications. The method comprises: regularly acquiring memory usage data of a Vue application and monitoring the memory occupancy of the Vue application based on the memory usage data; reclaiming the memory of the Vue application when the memory occupancy exceeds a first preset threshold; performing memory leak detection on the Vue application using a memory analyzer; and, when a memory leak occurs, reclaiming orphaned objects in the Vue application to automatically repair the memory.

The present invention provides an industrial data monitoring system based on a streaming computing engine, including a status monitoring module that uses Prometheus, which is natively supported by the streaming computing engine, to collect and store real-time indicators, periodically captures all sub-node indicators through a meta node for aggregation, provides a unified data source to Grafana for visualization, and configures alarms through a dashboard; a resource allocation module that analyzes real-time tasks, provides sufficient memory for the job, and processes task messages in real time. It combines relevant indicators obtained from the real-time task memory analysis and the rationality of the real-time task concurrency to derive a preset value for real-time task resources, adjusts real-time task resources, and achieves real-time task resource configuration; an abnormal status module that uses SideOutput to collect data on errors in each link of the streaming job, aggregates them into a unified error stream, and issues real-time alarms by discovering patterns that meet set characteristics in the streaming data. The present invention combines complex event processing with a streaming computing engine to enhance the real-time nature and applicability of alarms.

This invention relates to the field of electronic digital data processing technology and discloses a software component verification method based on runtime memory analysis. The method includes: reading a virtual reference address and the instruction stream to be verified when the target memory page attribute switches from non-executable to executable; dividing the instruction stream to be verified into continuous memory blocks according to the hardware cache line alignment length; counting the number of instruction start boundaries within each memory block and serializing them in ascending address order to generate a feature vector representing load density; matching the feature vector with a reference library and sending an interception signal to the kernel scheduler when the distance metric exceeds a threshold. This invention utilizes the physical boundaries of the hardware cache lines to capture load structure distortions caused by code obfuscation, avoiding complex semantic parsing logic, effectively reducing system latency caused by verification, and synergistically improving the verification confidence for dynamically mutated components.

The invention discloses a memory address adjustment method and device for an operating system, equipment, a storage medium and a program product. The method comprises the following steps: acquiring running data of the operating system; inputting the operation data into a preset neural network model, and obtaining an adjustment strategy output by the neural network model; wherein the neural network model comprises an input layer, a data processing layer and an output layer, the input layer is used for receiving the operation data, the data processing layer is used for performing memory analysis and attack recognition on the operation data to obtain a feature analysis result, and the output layer generates an adjustment strategy according with a memory optimization target according to the feature analysis result; and adjusting the memory address of the operating system according to the adjustment strategy. By adopting the embodiment of the invention, the memory address space layout of the operating system can be adjusted in real time, the randomness and unpredictability of the address space layout are improved, and different operating environments and attack modes are effectively coped with, so that the protection capability of the system is enhanced.

Systems and methods including: generating results of an algorithm based on a command; saving the results onto a dataserver; serializing the results; and storing the serialized results onto a cache stored on a disk.

The present invention discloses a method and system, equipment, and storage medium for reconstructing the dense modal response of a condensed structure. The method uses model condensation to generate a super-element model with fewer degrees of freedom based on a finite element model, which can effectively improve reconstruction efficiency. The method also divides the structural mode into dense modes and residual modes, and then reconstructs the residual modal response and dense modal response of the test point respectively. Finally, the test response is obtained by modal superposition. Compared with the existing EMD decomposition method that extracts single-frequency modal responses through a bandpass filter, the method can effectively separate dense modes and accurately reconstruct dense modal responses, which can be better applied to the response reconstruction of dense modal structures. In addition, the method can realize the reconstruction of the response of any degree of freedom of the structure based on the known structural response, improves engineering practicality, ensures accuracy, greatly improves reconstruction efficiency, saves computer memory, and has a fast analysis speed.