Cloud-Based Dynamic Analysis Error Classification
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Solution Overview
Problem
Dynamic analysis tools struggle to distinguish between system library-related errors caused by inherent problems and those resulting from developer misuse, leading to developers having to sift through numerous reported errors to identify relevant issues for improving applications.
Innovation Solution
A cloud-based approach where a dynamic analysis tool monitors and evaluates errors across multiple clients, using error data to flag errors as either user-related or system library-related based on frequency and resolution thresholds, allowing for filtering of irrelevant errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a dynamic analysis tool reports all system library-related errors, then the tool provides comprehensive error detection, but the developer must sift through numerous errors to identify relevant issues
Solution Approach 1:
The patent segments errors into two distinct categories: system library errors and application errors. This segmentation is achieved by analyzing error locations and determining whether they originate from system library code or application code. By dividing the error set into meaningful segments, the tool enables developers to focus on application errors while understanding that system library errors are not their responsibility, thus reducing time spent sifting through irrelevant errors while maintaining complete error detection capability
Solution Approach 2:
The patent introduces an intermediary mechanism (error classification system) that acts as a mediator between the dynamic analysis tool and the developer. This intermediary automatically evaluates errors, determines their origin, and presents them in a classified manner. The intermediary filters out system library errors from the developer's immediate attention while maintaining a record of all errors, thus reducing developer workload without compromising detection completeness
2Measurement precision
If a dynamic analysis tool tracks errors at multiple locations in system libraries, then the tool can pinpoint relevant areas for investigation, but the tool cannot distinguish between inherent system library problems and developer misuse
Solution Approach 1:
The patent applies dynamics by making the error reporting system adaptive and context-aware. Instead of statically reporting all errors uniformly, the system dynamically evaluates each error's origin by analyzing call stacks, instruction pointers, and code locations. The system adapts its reporting behavior based on whether an error originates from system library code or application code, providing different levels of detail and classification accordingly. This dynamic approach preserves precise location information while adding contextual information about error causes
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors error patterns and uses this information to improve classification accuracy. The system evaluates errors relative to observed error data and provides feedback to developers about whether errors are caused by system library issues or application misuse. This feedback loop ensures that precise location information is maintained while also providing actionable insights about error causes, transforming raw location data into meaningful diagnostic information
Data Source
AI summary
Techniques are disclosed for classifying system library errors detected by a dynamic analysis tool executing in a first client of a plurality of clients. The dynamic analysis tool monitors an execution of an application. The dynamic analysis tool identifies one or more errors that are related to at least one of a plurality of system libraries called by the application during the execution. For each identified error, the dynamic analysis tool evaluates the error relative to error data observed in a dynamic analysis tool executing in the other clients, and flagging the error as an error that is not caused by a user based on the evaluation.