Method Parameter Tracing for Distributed Application Server Profiling
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Solution Overview
Problem
Distributed application server environments face performance and scalability issues due to concurrent user access, and existing profiling tools struggle to effectively trace and report method parameter values in software applications, leading to inefficiencies in resource consumption analysis.
Innovation Solution
A computer-implemented method and system that trace values of method parameters during application execution, generating entry and exit events with event data including timestamps and processing unit times, and reporting these events to user interfaces or storage devices, allowing for comprehensive profiling and debugging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive profiling of all method parameters is performed, then measurement precision is improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent segments the profiling process by dividing method parameters into different groups based on their characteristics and profiling requirements. The system selectively applies different profiling strategies to different parameter groups, rather than uniformly profiling all parameters. This segmentation reduces the overall complexity while maintaining measurement precision for critical parameters.
Solution Approach 2:
The patent implements local quality by applying different profiling depths and methods to different methods and parameters based on their specific characteristics. High-precision profiling is applied only to critical methods and parameters where measurement accuracy is most important, while less critical parameters receive simplified profiling treatment. This selective approach maintains measurement precision where needed while reducing system complexity overall.
2Difficulty of detecting and measuring
If detailed tracing of method parameter values is performed, then debugging capability is improved, but processing time and resource consumption increase
Solution Approach 1:
The patent applies partial action by selectively tracing only the most relevant method parameters based on profiling specifications and criteria, rather than tracing all parameters uniformly. The system determines which parameters require detailed tracing based on method importance, parameter sensitivity, and debugging priorities. This partial tracing approach maintains strong debugging capability for critical parameters while significantly reducing processing time and resource consumption.
Solution Approach 2:
The patent changes parameters dynamically by adjusting the level of tracing detail based on runtime conditions, method characteristics, and profiling priorities. The system can modify which parameters are traced and at what depth based on observed behavior patterns and performance metrics. This dynamic parameter adjustment enables effective debugging when needed while minimizing processing overhead during normal operation.
3Loss of information
If all method parameters are traced and reported, then information completeness is improved, but data volume and reporting overhead increase
Solution Approach 1:
The patent extracts and reports only the most significant method parameter values based on predefined criteria and profiling specifications. The system identifies and extracts critical parameters that provide the most valuable profiling information, while omitting or aggregating less important parameters. This extraction approach maintains information completeness for decision-making while significantly reducing the volume of data that needs to be stored, transmitted, and processed.
Solution Approach 2:
The patent inverts the traditional approach by not reporting all parameters by default, but rather reporting only those parameters that meet specific importance criteria. The system starts with an empty set of reported parameters and selectively adds only those that provide meaningful profiling information based on method significance, parameter sensitivity, and business logic. This inverted approach ensures information completeness for critical decisions while minimizing data volume.
Data Source
AI summary
Implementations of the present disclosure provide methods including receiving one or more specifications at a virtual machine that is executed using one or more processors, each specification indicating one or more methods and one or more parameters to be traced, the one or more parameters corresponding to the one or more methods, executing an application, the application calling a method of the one or more methods using the virtual machine, determining a subset of the one or more received specifications, the subset corresponding to specifications that are applicable to the method, generating an entry event corresponding to the method based on the subset, the entry event comprising event data including values of the one or more parameters, and reporting the entry event.