Transaction Log Analysis for IoT Testing Completeness
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Solution Overview
Problem
Current methods for quality assurance of IoT applications are inefficient and resource-intensive, as they often neglect secondary actions and require extensive storage for database image comparisons, leading to increased costs and limited testing precision.
Innovation Solution
A computer-implemented method for analyzing transaction logs by filtering records based on criteria such as timestamps and database users, allowing for the efficient retrieval and analysis of both primary and secondary actions, and determining a test verdict to ensure comprehensive testing without neglecting secondary actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If database image comparison method is used to verify actions, then testing completeness is improved, but storage space requirement increases significantly
Solution Approach 1:
The patent extracts only the necessary verification information (transaction logs containing action records and criterion records) from the database, rather than comparing entire database images. This extraction approach maintains testing completeness by preserving all action-criterion pairs while dramatically reducing storage requirements.
Solution Approach 2:
Instead of copying and storing entire database images for comparison, the patent creates lightweight copies of only the essential elements (transaction logs with action and criterion records). This selective copying maintains the ability to verify all actions while minimizing storage space consumption.
2Ease of manufacture
If simulators and emulators are used for testing, then testing cost is reduced, but testing precision and device coverage are limited
Solution Approach 1:
The patent introduces transaction logs as an intermediary layer between the simulator and the verification process. The transaction logs capture detailed action and criterion records that provide precise verification data, bridging the gap between cost-effective simulation and high-precision testing requirements.
Solution Approach 2:
The patent replaces the need for complex physical device simulations with a streamlined system using transaction logs and filtering. This substitution maintains testing precision by focusing on the essential action-criterion verification while reducing reliance on resource-intensive simulator infrastructure.
3Device complexity
If only primary actions are monitored, then analysis complexity is reduced, but testing completeness deteriorates due to neglected secondary actions
Solution Approach 1:
The patent creates a universal filtering mechanism that can handle both primary and secondary actions uniformly. The filter criterion system is designed to work with any action type, making the analysis process multi-functional while maintaining manageable complexity through standardized processing of all action categories.
Solution Approach 2:
The patent performs preliminary classification of actions into primary and secondary categories during the transaction logging phase. This preliminary organization allows the system to comprehensively monitor all actions without increasing analysis complexity, as the differentiation is already established before the verification process begins.
Data Source
AI summary
Provided is a computer-implemented method for analyzing a transaction log, stored in a computer readable storage medium, wherein the transaction log comprises records of transactions in the range of zero to a plurality of records, wherein each record of transaction comprises at least one action executed during a test and at least one associated recorded criterion, comprising the steps: a. Providing the transaction log and at least one filter criterion; b. Determining records of transactions from the transaction log to be filtered in accordance with the at least one filter criterion; wherein the at least one filter criterion matches the respective associated recorded criterion of the action at least one action of the respective filtered records of transactions of transaction; c. Determining a test verdict based on the filtered records of transactions of transaction; and d. Providing the filtered records of transactions, the test verdict and/or related data as output.