Customer Workload Profiling for Software Test Resource Allocation
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Solution Overview
Problem
Software testing often fails to identify all issues before software release, leading to problems in customer software due to inadequate understanding of client environments and workload profiling.
Innovation Solution
A method and system that identify workload characteristics by customer geography, country, and culture, creating a test workload execution model to determine peak customer test coverage and reduce test resources allocation accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional software testing methods are used without customer environment profiling, then testing can be performed with standard resources, but software problems remain unidentified and test coverage is insufficient
Solution Approach 1:
The patent performs customer environment and workload profiling in advance before software release, creating baseline data about actual customer usage patterns, hardware configurations, and software environments. This preliminary characterization enables more accurate and targeted testing to be performed subsequently, improving both reliability and measurement precision.
2Reliability
If comprehensive software testing is performed to identify all problems, then software quality improves, but testing costs and time increase significantly
Solution Approach 1:
The patent applies different testing strategies to different customer segments based on their specific environment profiles, workload characteristics, and risk levels. High-risk customers with complex environments receive more comprehensive testing, while lower-risk customers receive streamlined testing, optimizing the balance between quality and efficiency.
Solution Approach 2:
The system dynamically adjusts testing parameters such as test depth, resource allocation, and test case selection based on customer-specific profiles including environment complexity, workload characteristics, and historical data, enabling efficient resource utilization while maintaining quality.
3Measurement precision
If test resources are allocated uniformly to all customers, then resource management is simplified, but test coverage does not match actual customer needs and peak coverage requirements are not met
Solution Approach 1:
The system pre-characterizes customer environments and workloads to identify peak coverage requirements before resource allocation decisions are made. This advance profiling enables data-driven resource allocation that matches actual customer needs rather than using uniform distribution.
Solution Approach 2:
The patent implements continuous monitoring and comparison of actual customer environments against test coverage results, using this feedback to dynamically adjust resource allocation. This closed-loop system ensures resources are directed to areas with peak coverage needs while maintaining overall system manageability.
Data Source
AI summary
Aspects of the present invention include a method, system and computer program product. The method includes a processor identifying a plurality of workload characteristics by customer geography, country and/or culture; identifying one or more workload characteristics within a customer geography, country and/or culture; creating a test workload execution model; determining that a peak customer test coverage is beneficial to at least one customer in other customer geographies, countries and/or cultures; and reducing, by the processor, a number of test resources allocated to at least one customer in other customer geographies, countries and/or cultures.