Application Test Tool Selection Based on Function Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing testing methods for applications often waste resources by testing non-existent functions and fail to exhaustively test all functions, leading to inefficiencies and potential security vulnerabilities.
Innovation Solution
An analyzer, potentially using AI, determines the functions of an application under test and selects appropriate testing tools to ensure thorough testing without redundant or irrelevant tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all available testing tools are applied to an application, then the completeness of testing is improved, but resource waste increases due to testing non-existent functions
Solution Approach 1:
The patent applies preliminary action by analyzing the application's source code, manifest files, and configuration data before executing tests to identify which functions actually exist in the application. This preliminary analysis creates a function inventory that guides subsequent test selection, ensuring that only relevant testing tools are applied rather than all available tools, thus preventing resource waste on non-existent functions while maintaining testing completeness.
2Reliability
If testing is performed exhaustively with every possible combination of inputs and operations, then testing thoroughness is improved, but testing time and resource consumption increase
Solution Approach 1:
The patent applies partial action by selectively executing only those tests that correspond to functions actually present in the application, rather than performing exhaustive testing with every possible test combination. The system analyzes application metadata and code structure to determine which functions exist, then applies testing tools only to those identified functions, achieving sufficient thoroughness without the excessive time and resource consumption of complete exhaustive testing.
3Productivity
If testing tools are selected without analyzing application functions, then testing speed is improved, but testing accuracy decreases due to irrelevant tests
Solution Approach 1:
The patent applies preliminary action by performing a rapid analysis of application source code, manifest files, and configuration data before test execution to identify existing functions. This preliminary function identification enables accurate matching of testing tools to actual application features, ensuring testing accuracy is maintained while the process remains efficient through automated static analysis rather than manual function identification.
4Measurement precision
If the analyzer examines all code and configuration data to identify functions, then function detection accuracy is improved, but analysis time increases
Solution Approach 1:
The patent applies segmentation by dividing the application analysis into distinct components: parsing manifest files for declared functions, analyzing source code for actual implementations, and examining configuration data for additional function indicators. By segmenting the analysis process and using multiple independent analysis streams, the system achieves comprehensive function detection accuracy while maintaining efficiency through parallel processing and early termination when sufficient information is gathered.
Data Source
AI summary
Systems and methods are disclosed for automatically analyzing an application under test (AUT) and, as a result of the analysis, determining a function of the AUT. The function may comprise a permission and/or a framework. An automated test is then selected, from a pool of tests, to test the function of the AUT. The test is then performed on the AUT. Results from the test may be provided back to the analysis process, which may be an artificial intelligence, such as a neural network, as feedback.