Software Instrumentation Model for User Action Diagnostics

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Solution Overview

Problem

Existing software application diagnostics lack intelligibility and context, making it difficult for data analysts to understand user actions and diagnose issues, as they rely on incomplete health instrumentation data that lacks semantic meaning and time correlation, leading to inefficient problem-solving and high data retention costs.

Innovation Solution

A robust instrumentation model and data schema are introduced, separating user instrumentation data from code instrumentation data, providing a semantic model for user actions and correlating them with code execution, while implementing privacy controls and flexible sampling policies to store and analyze user and code data effectively.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If comprehensive user action tracking is implemented, then diagnostic capability and user behavior understanding are improved, but data retention costs and system complexity increase

Engineering Contradiction:

Improveuser action context informationVSAvoiddata retention costs

Core Design Contradiction:

Loss of informationVSLoss of energy

Solution Approach 1:

The patent extracts and separates user instrumentation data from code instrumentation data into distinct data streams and storage structures. User actions are captured as high-level semantic events (e.g., 'user clicked button') separate from low-level code execution metrics, allowing selective retention and analysis of only the most valuable diagnostic information while reducing overall data volume and storage costs.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The instrumentation system segments data collection into multiple layers: user actions, code executions, and system events. Each layer is independently instrumented, stored, and analyzed. This segmentation allows the system to retain detailed user action sequences for diagnostic purposes while using sampling policies for other data types, thereby reducing total data retention requirements while maintaining diagnostic capability.

Inventive Principle:

Principle #1Segmentation

2Reliability

If detailed user action data is collected and stored, then problem diagnosis capability is improved, but data privacy risks and storage requirements increase

Engineering Contradiction:

Improveproblem diagnosis accuracyVSAvoiduser privacy exposure

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent introduces an intermediary instrumentation layer that captures user actions at the application level rather than at the operating system or hardware level. This intermediary layer processes and anonymizes data before storage, acting as a buffer that protects user privacy while maintaining diagnostic utility. The instrumentation code runs within the application sandbox, limiting access to sensitive user data while still capturing behavioral patterns needed for diagnosis.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Loss of information

If extensive instrumentation code is added to track user actions, then diagnostic capability is improved, but application complexity and development overhead increase

Engineering Contradiction:

Improveexecution context dataVSAvoidinstrumentation code complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent implements a universal instrumentation framework that can be applied across different applications and platforms with minimal customization. The core instrumentation library provides standardized functions for capturing user actions, code executions, and system events that work across diverse application types. This multi-functionality reduces the need for application-specific instrumentation code, lowering development overhead while maintaining comprehensive tracking capability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If all user actions are tracked without sampling, then complete behavior analysis is achieved, but data storage costs and processing overhead increase

Engineering Contradiction:

Improveuser behavior analysis completenessVSAvoiddata processing efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent implements dynamic sampling policies that adjust the level of data collection based on contextual factors such as action frequency, user segment, and diagnostic priority. High-value actions (e.g., error-triggering sequences) are captured at 100% rate, while common routine actions use lower sampling rates. This dynamic approach maintains measurement precision for critical behaviors while reducing overall data volume for processing and storage.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS10977159B2Instrumentation of user actions in software applications

Publication Date: 2021.04.13 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

A method may include receiving user instrumentation data and code instrumentation data from at least one user computing device such that the user and code instrumentation data is associated with performance of a user action of an application. The user instrumentation data may include a name identification of the user action and an input type identification of the initiation of the user action. The method may include storing the user and code instrumentation data in a database. The method may include receiving a search query associated with a past user action made in the application. The method may include retrieving, from the database, a set of one or more user actions based on the search query. The method may include presenting a user interface that includes an abstracted representation of the retrieved set of user actions.