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40 results about "Stack trace" patented technology
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In computing, a stack trace (also called stack backtrace or stack traceback) is a report of the active stack frames at a certain point in time during the execution of a program. When a program is run, memory is often dynamically allocated in two places; the stack and the heap. Memory is continuously allocated on a stack but not on a heap, thus reflective of their names. Stack also refers to a programming construct, thus to differentiate it, this stack is referred to as the program's runtime stack. Technically, once a block of memory has been allocated on the stack, it cannot be easily removed as there can be other blocks of memory that were allocated before it. Each time a function is called in a program, a block of memory is allocated on top of the runtime stack called the activation record (or stack pointer.) At a high level, an activation record allocates memory for the function's parameters and local variables declared in the function.
Automatic application data collection for potentially insightful business values
In one embodiment, a method for automatic application data collection is disclosed. The method illustratively comprises determining a stack trace associated with one or more business transactions, wherein at least one application is configured to perform at least part of the one or more business transactions; identifying, based on the stack trace, one or more methods of the at least one application that were invoked during performance of the one or more business transactions; selecting, from the identified one or more methods, a set of the one or more methods by applying at least one scoring heuristic to the identified one or methods; and configuring one or more monitoring agents executing on the at least one application to instrument the selected set of the one or methods at one or more instrumentation points, wherein application performance data is generated by instrumentation of the one or more instrumentation points.
Owner:CISCO TECHNOLOGY INC
Software crash error repair scheme recommendation method based on position and knowledge similarity
The invention discloses a position and knowledge similarity-based software crash error repair scheme recommendation method, which outputs a repair method for error codes according to generated crash stack tracking information and corresponding codes when software crashes, and can help developers to quickly and efficiently solve the problem of software crash. When the method works, firstly, a context knowledge base is constructed, problem posts containing crash stacks on Stack Overflow are preprocessed, a knowledge base and an abnormal dictionary are constructed, and a language model is trained; thirdly, a related question set is preliminarily obtained through stack tracking, the comprehensive similarity of the question and an input stack is calculated through the position related similarity and the additional knowledge similarity, and the most related question and answer set is returned; and finally, performing relevancy calculation on the answer paragraphs based on multiple features, selecting paragraphs related to the crash reason by applying an MMR algorithm, and outputting root cause analysis and repair code snippets related to the crash error.
Owner:ZHEJIANG UNIV CITY COLLEGE
Systems and methods for generating an enhanced error message
Systems and methods for generating an enhanced error message are provided. An example method includes: receiving one or more raw error messages. The one or more raw error messages include one or more stack traces. The method further includes matching at least one raw error message of the one or more raw error messages to one or more error rules from a plurality of error rules. The one or more error rules include regular expression patterns. The method further includes parsing the at least one raw error message, based on the one or more matched error rules from the plurality of error rules; and generating one or more enhanced error messages, based on the at least one parsed raw error messages. The one or more enhanced error messages include one or more natural language sentences. The method further includes embedding the one or more enhanced error messages into a website.
Owner:PALANTIR TECHNOLOGIES INC
Crash bug component prediction system to identify components as potential bug sources
Methods, systems, and computer-readable storage media for receiving a crash report provided as a computer-readable file, providing a stack trace from the crash report, adding component information to the stack trace, for each component identified in the stack trace, determining a set of features, processing sets of features through a ML model to provide a prediction identifying a component as a bug component, and assigning the bug component for resolution through a crash management system.
Owner:SAP SE
Parallel partitioning method and device for RDD structure post-stack data
PendingCN120123418ADatabase distribution/replicationSpecial data processing applicationsComputational scienceParallel computing
Owner:CHINA PETROLEUM & CHEMICAL CORP +1
Cyber threat information processing apparatus, cyber threat information processing method, and storage medium storing cyber threat information processing program
A cyber threat information processing method including generating stack trace information of a reader program of an operating system executing a non-executable file at a hooking point of a system call of the operating system when the reader program performs the system call, obtaining a calling function for calling the system call and a variable corresponding to the calling function from the generated stack trace information, and providing description information about the obtained calling function and the variable corresponding to the calling function.
Owner:SANDS LAB INC
Data acquisition method and device, electronic equipment and storage medium
PendingCN120973440AExecution paradigmsCreation/generation of source codeCall stackSoftware engineering
The invention discloses a data acquisition method and device, electronic equipment and a storage medium. The data acquisition method comprises the following steps: injecting a data acquisition code into a runtime environment of a target application program; determining data acquisition demand information in a runtime environment of the target application program; calling the data acquisition code according to the data acquisition demand information; when the data collection code is called, stack tracking data are obtained from original calling stack data of the target application program according to the data collection requirement information, and the stack tracking data are output. By adopting the method, the performance loss of call stack acquisition can be reduced.
Owner:ALIBABA (CHINA) CO LTD
Verified Stack Trace Generation And Accelerated Stack-Based Analysis With Shadow Stacks
A verified stack trace can be generated by utilizing information contained in a shadow stack, such as a hardware protected duplicate stack implemented for malware prevention and computer security. The shadow stack contains return addresses which are obtainable without requiring an unwinding of the traditional call stack. As such, triaging based on return address information can be performed more quickly and more efficiently, and with a reduced utilization of processing resources. Additionally, the generation of a verified stack trace can be performed, with such a verified stack trace containing return addresses that are known to be correct and not corrupted. The return addresses can either be read from the traditional call stack, or derived therefrom, and then verified by comparison to corresponding return addresses from the shadow stack, or they can be read directly from the shadow stack.
Owner:MICROSOFT TECHNOLOGY LICENSING LLC
Stack trace using shadow stack
ActiveCN114144764BError detection/correctionPlatform integrity maintainanceCall stackTelecommunications
A program is executed using a call stack and a shadow stack. The call stack includes frames with respective return addresses. The frames can also store variables and / or parameters. The shadow stack stores copies of the return addresses in the call stack. The call stack and the shadow stack are maintained by (i) adding a respective stack frame to the call stack and a respective return address to the shadow stack each time a function is called, and (ii) removing a respective frame from the call stack and a respective return address from the shadow stack each time a function is exited. A backtrace of the current call chain of the program is generated by accessing the return addresses in the shadow stack. The output backtrace includes return addresses from the shadow stack and / or information about traced functions derived from the return addresses of the shadow stack.
Owner:MICROSOFT TECHNOLOGY LICENSING LLC
Computer-implemented method for checking the execution of at least one control device function on a simulator and corresponding simulator
Described and illustrated is a computer-implemented method (1) for verifying the execution of at least one control unit function (f1, f2, f3) of a control unit by means of at least one computing unit (5) of a simulation environment (4) on a simulator (2), wherein the control unit function (f1, f2, f3) is executed under zero-time assumption of a discretely progressing simulation time (tsim) between successive simulation steps in an event-oriented discrete simulation on the simulator (2).The cause of blockage situations in the simulation can be efficiently determined by an observation service (6) operated on the simulator (2) comparing the progress of the discrete simulation time (tsim) with the progress of a simulator real-time (treal) and, if the progress of the simulator real-time (treal) exceeds the progress of the discrete simulation time (tsim) by a predefined limit (td), at least indirectly creating a plurality of stack traces (7) of the at least one computing unit (5) (8) and in an evaluation step (9) by evaluating the stack traces (7) at least the most frequent control unit function (fmax) that the at least one computing unit (5) executed most frequently at the time of creation (8) of the respective stack trace (7) is determined and the determined most frequent control unit function (fmax) is displayed and / or further processed.
Owner:DSPACE SE & CO KG
Prestack AVO inversion optimization method based on DTW matching technology
The present invention provides a pre-stack AVO inversion optimization algorithm based on DTW matching technology. Seismic traces with minimal error are selected as reference traces, a Euclidean distance matrix is established, and the cumulative Euclidean distance matrix is calculated to characterize the global similarity between the sequence reference trace and the trace to be corrected. The cumulative error matrix is calculated to determine the optimal path for correcting the trace. This path stores the amount of stretching and compression at each point, representing the optimal time-domain stretching and compression scheme for the trace to be corrected. By traversing all traces to be corrected, an optimized pre-stack trace gather is obtained. Using this optimized trace gather for pre-stack AVO inversion improves inversion accuracy. The present invention only performs local stretching and compression on the time axis, ensuring the accuracy of subsequent AVO analysis and inversion. Furthermore, the stretching and compression amount of each trace to be corrected can be automatically calculated as the correction amount. In situations where the effective reflection signal is weak and background noise interference is strong, a control layer can be added to make the matching results more reliable.
Owner:HAINAN BRANCH OF CHINA NATIONAL OFFSHORE OIL (CHINA) CO LTD +1
An Application Code-Level Performance Analysis Method, Device, Equipment and Medium
ActiveCN116303078BError detection/correctionProgram loading/initiatingApplication procedureAnalysis method
The present invention relates to the field of code performance analysis, and in particular, to a method, device, equipment and medium for application program code-level performance analysis. The method includes: creating a detection task to configure the application name of the application to be detected, the function name to be detected, and the monitoring duration; starting the application to be detected based on the application name; using an eBPF sampler to obtain the detection task, and injecting sampling code into the started application to be detected based on the function name to be detected and the monitoring duration; generating access traffic to run the application to be detected after injecting the sampling code; using an analyzer to obtain the kernel stack trace and process symbol table from the eBPF Map and perform aggregation analysis to obtain the thread stack and call count corresponding to each kernel stack trace that is called. The solution of the present invention saves manpower and time costs, facilitates developers to quickly analyze online and accurately locate the root cause of program time consumption, and has high application value.
Owner:JINAN INSPUR DATA TECH CO LTD
System and method for threat detection based on stack trace and kernel sensors
A method and system for threat detection and analysis is disclosed herein. The method includes monitoring at least one thread associated with at least one process on a computing system. The method further includes detecting specific system calls associated with at least one process at kernel level. The specific system calls are analyzed by applying a filter to the system calls sequence feature set associated with the specific system calls for detecting one or more events of interest. A full stack trace capture of at least one process is requested if the system calls sequence feature set is filtered and the one or more events of interest are detected. A first level monitoring is provided to the computing system, which includes processing and analyzing the captured full stack trace by a machine learning (ML) stack trace analyzer to generate a first verdict for threat detection and analysis.
Owner:ACRONIS INT
System and method for threat detection based on stack trace and user-mode sensors
Systems and methods for threat detection and analysis. A method includes monitoring at least one thread associated with at least one user process on a computing device. The method further includes detecting specific-system calls associated with at least one user process at user level. The specific-system calls are analyzed by applying a filter to system calls sequence feature sets associated with the specific-system calls for detecting one or more events of interest. A capture of a full stack trace of at least one user process is requested if the system calls sequence feature set is filtered and at least one event of interest is detected. A first level monitoring is provided to the computing device, which includes processing and analyzing the captured full stack trace by a machine learning (ML) stack trace analyzer to generate a first verdict for threat detection and analysis.
Owner:ACRONIS INT
Software application testing with flaky test case detection
Various examples are directed to systems and methods for debugging a software application. A computing system may access first stack trace data describing a plurality of function calls made by a software application during a failed execution of a first test case. The computing system may compare the first stack trace data and flaky test case data. The flaky test case data may describe at least one function call made by the software application during execution of at least one flaky test case. The at least one flaky test case may comprise a first flaky test case that the software application passed during one execution of the first flaky test case and failed during another execution of the first flaky test case. Based at least in part on the comparing, the computing system may determine that the first test case is a flaky test case.
Owner:SAP SE
Verified stack trace generation and accelerated stack-based analysis with shadow stacks
A verified stack trace can be generated by utilizing information contained in a shadow stack, such as a hardware protected duplicate stack implemented for malware prevention and computer security. The shadow stack contains return addresses which are obtainable without requiring an unwinding of the traditional call stack. As such, triaging based on return address information can be performed more quickly and more efficiently, and with a reduced utilization of processing resources. Additionally, the generation of a verified stack trace can be performed, with such a verified stack trace containing return addresses that are known to be correct and not corrupted. The return addresses can either be read from the traditional call stack, or derived therefrom, and then verified by comparison to corresponding return addresses from the shadow stack, or they can be read directly from the shadow stack.
Owner:MICROSOFT TECHNOLOGY LICENSING LLC
Tracing processes in distributed container systems
ActiveUS12524276B1Resource allocationSoftware simulation/interpretation/emulationResource utilizationDistributed computing
Techniques implemented by container services to provide users with utilization metrics indicating which processes running inside containers of distributed container systems are driving computing resource consumption. The container service may deploy agents in VMs alongside the containers that are supporting applications, and the agents may include profilers that inject eBPF programs into the kernels of each VM in which containers are running. The eBPF programs collect stack traces from the kernels that represent which processes were being executed when the stack traces were sampled. The profilers may use the stack traces to determine resource utilization for each process, and group the stack trace results based on the container in which the processes are executing. The utilization metrics may be converted into easily digestible visualizations and provided to a user to determine which processes are driving utilization in the containers, which in turn helps the users improve their application code.
Owner:AMAZON TECH INC
A software defect localization method based on contextual program reduction technology
The present invention discloses a software defect location method based on context program reduction technology. The method adopts a defect location system to work. The system includes a suspicious program extraction module, a code entity processing module, and a defect location module. The suspicious program extraction module is used to generate a stack trace from the stack frame of the program activity and extract suspicious program entities therefrom. The code entity processing module is used to parse the suspicious program entities and rank the defect probabilities of potential defective code entities. The defect location module is used to locate the defective code entities. The suspicious program extraction module includes a stack frame generation module and a stack trace analysis module. The stack frame generation module is electrically connected to the stack trace analysis module; the stack trace analysis module is used to extract suspicious program entities from the stack frame. The present invention has the characteristics of statement-level defect location.
Owner:NANJING UNIV OF FINANCE & ECONOMICS
Stack trace analysis model
Systems and methods for detecting a malware injection interested processes. The method includes identifying one or more trusted processes, monitoring at least one thread associated with the trusted processes using at least one control point, detecting activity at the at least one thread based on the at least one control point and determining a timestamp of the detected activity, receiving from the trusted processes at least one execution stack corresponding to the timestamp and indicating the at least one control point used to monitor the at least one thread, applying a first malware detector to the at least one execution stack to generate a first verdict, collecting the first verdict and auxiliary information corresponding to the trusted processes at the given timestamp, and applying a second malware detector to the first verdict and the auxiliary information to generate a second verdict.
Owner:ACRONIS INT
Program call stack creation method and unwind stack method and apparatus
ActiveUS12650857B2Software testing/debuggingProgram loading/initiatingCall stackSoftware engineering
This application discloses a program call stack creation method and apparatus, and an unwind stack method and apparatus. The call stack creation method includes: obtaining a first program, where the first program includes a first function, in a process of calling a runtime library to run the first program, adding a second function and creating a call stack, where the call stack includes a first stack frame, a second stack frame, and a third stack frame that are respectively corresponding to the first function, the second function, and a third function. An unwind stack performance can be improved to a maximum extent without affecting a non-stack trace scenario.
Owner:HUAWEI TECH CO LTD
System and methods of generating previews for content migration
A computer-implemented method is disclosed. The method includes: obtaining a stack trace associated with an error detected in connection with execution of a computer program by a processor; determining a location of the error within source code of the computer program based on the stack trace, wherein the source code contains a template code section and a custom code section; generating an error message for the error, wherein the generating includes: in response to determining that the error is located in the custom code section, appending a first representation of the stack trace to the error message; and in response to determining that the error is located in the template code section, formatting the error message to indicate a generic template code error, and presenting the error message via a computing device.
Owner:SHOPIFY INC
Rendering a stack trace visualization display
ActiveUS12222836B2Hardware monitoringSoftware testing/debuggingComputer graphics (images)Processing element
A method and system for rendering a stack trace visualization display has been developed. A first stack trace associated with execution of an application during a time period is received from a central processing unit profiler. A first stack trace visualization display is rendered including a plurality of stack frames stacked in accordance with an order of ancestry based on the first stack trace. Rendering at least one stack frame involves rendering at a first location of the first stack trace visualization display, a stack frame rectangle for the at least one stack frame in accordance with the order of ancestry and rendering at a second location of the first stack trace visualization display, stack frame specific text for the at least one stack frame. The second location overlays the first location. Rendering of the stack frame rectangle is independent of the rendering of the stack frame specific text.
Owner:SALESFORCE INC
Methods, systems, and media for encoding stack trace information
Methods, systems, and media for encoding stack trace information are disclosed. Embodiments provide a thread categorization method that uses a categorization signature to represent a stack trace in a compact form. Some embodiments can receive a stack trace comprising a sequence of stack frames. Some embodiments can generate, based on the sequence of stack frames, a trace signature representing a set. Some embodiments can receive one or more subsequent stack traces. For each of the one or more subsequent stack traces, some embodiments can determine whether a subsequent trace signature representing a sequence of stack frames included within the subsequent stack trace has been generated. If not, some embodiments can generate, based on the trace signature and other subsequent trace signatures generated based on the trace signature, a subsequent trace signature representing the subsequent sequence of stack frames.
Owner:ORACLE INT CORP
Real-time shellcode detection and prevention
Methods, storage systems and computer program products implement embodiments of the present invention for protecting a computing device, which includes a processor and a memory and is coupled to a storage device storing a set of one or more files. In embodiments of the present invention, a call to a specified function for execution by the processor is detected, and a stack trace for the call to the specified function is generated in the memory. Upon detecting, in the stack trace, a stack frame including a return address referencing a shellcode region in the memory, wherein the shellcode region includes executable code that was not loaded from any given file on the storage device, then the referenced executable code is compared to a list of malicious shellcode. Finally, a preventive action is initiated upon detecting a match between the referenced executable code and one of malicious shellcodes in the list.
Owner:PALO ALTO NETWORKS INC
Stack tracking using shadow stacks
PendingCN121116438AError detection/correctionPlatform integrity maintainanceCall stackTelecommunications
A program is executed using a call stack and a shadow stack. The call stacks include frames having respective return addresses. These frames may also store variables and / or parameters. The shadow stack stores a copy of the return address in the call stack. The call stack and the shadow stack are maintained by (i) adding a corresponding stack frame to the call stack and adding a corresponding return address to the shadow stack whenever a function is called, and (ii) removing the corresponding frame from the call stack and the corresponding return address from the shadow stack whenever the function is exited. And backtracking of the current call chain of the program is generated by accessing the return address in the shadow stack. The backtracking of the output includes a return address from the shadow stack and / or information about a tracked function derived from the return address of the shadow stack.
Owner:MICROSOFT TECHNOLOGY LICENSING LLC
Identifying application and transport layers discrepancies
First data related to outbound transport layer requests from a software application to external systems are logged. Second data related to application services layer requests from the software application are logged to at least some of the external systems. A transport layer request of the outbound transport layer requests that does not correspond to an application services layer request of the application services layer requests is identified based on the first data and the second data. The first data can include stack traces associated with the outbound transport layer requests. Logging the first data can be performed by an agent injected into classes including java.net. Socket and java.net. DatagramSocket executable by the software application.
Owner:ZOOM COMMUNICATIONS INC
Stack hotspot profiling analysis function visual graphical user interface for electronic devices
1. The name of the design product: electronic device stack trace profiling analysis function visualization graphical user interface. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for collected profile data to support correlation trace / span, support jumping from a trace / span to related profiling. 6. The human-computer interaction mode of the graphical user interface: the front view is the initial interface; after clicking the "stacktraces" icon below the front view, interface change state diagram 1 is entered; after clicking interface change state diagram 1, entering "un" in the search bar below the flame diagram, interface change state diagram 2 is entered; after clicking interface change state diagram 2, sliding the mouse, interface change state diagram 3 is entered. 7. Other circumstances that need to be explained: the display screen panel is used for an electronic device.
Owner:BEIJING YOUTEJIE INFORMATION TECH
Log data analysis method and system based on AI
The invention belongs to the technical field of log data analysis, and provides an AI-based log data analysis method and system, and the method comprises the following steps: obtaining log content feature data, and judging whether to trigger stack tracking analysis or not based on error pattern recognition which comprises high-frequency error recognition and new error type recognition; if the stack tracking analysis is triggered, a corresponding error log entry is obtained, a theoretical starting mark and a theoretical ending mark of the stack tracking analysis are defined, an actual starting point and an actual ending point for executing the stack tracking analysis are obtained, consistency comparison is conducted on the theoretical ending mark and the actual ending point, and whether stack tracking is abnormal or not is judged; and if stack tracking is abnormal, identifying and screening out asynchronous log entries in an abnormal stack tracking adjacent area based on time deviation and asynchronous keywords, analyzing a correlation between stack tracking abnormity and the asynchronous log entries, and identifying a correlation degree.
Owner:SHANGHAI FENGSHEN NEW ENERGY TECHNOLOGY CO LTD
System and method for threat detection based on stack trace and user-mode sensors
Systems and methods for threat detection and analysis. A method includes monitoring at least one thread associated with at least one user process on a computing device. The method further includes detecting specific-system calls associated with at least one user process at user level. The specific-system calls are analyzed by applying a filter to system calls sequence feature sets associated with the specific-system calls for detecting one or more events of interest. A capture of a full stack trace of at least one user process is requested if the system calls sequence feature set is filtered and at least one event of interest is detected. A first level monitoring is provided to the computing device, which includes processing and analyzing the captured full stack trace by a machine learning (ML) stack trace analyzer to generate a first verdict for threat detection and analysis.
Owner:ACRONIS INT
An intelligent software compatibility problem detection method based on a pre-trained language model
This invention discloses an intelligent software compatibility problem detection method based on a pre-trained language model. It collects unlabeled and labeled Python stack trace data to construct a pre-training dataset and a fine-tuning dataset; parses the traceback data and standardizes its format; processes traceback data exceeding the model's maximum length limit; uses the unlabeled traceback data to perform unsupervised retraining on the BERT model to learn traceback semantic features; constructs an intelligent software compatibility problem detection model; divides the fine-tuning dataset, selects positive examples from the training set to construct a class-balanced fine-tuning training set, and uses a small amount of labeled data to fine-tune the classification model. This invention solves the problem that existing methods cannot automatically detect compatibility problems occurring during the operation of intelligent software, overcomes the limitations of existing models in understanding the semantic features of Python traceback context, and can fully capture the dependencies between stack frames and exception information, effectively improving the accuracy of intelligent software compatibility problem detection.
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS