Workload Report Scores for Software Testing Profiling
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Solution Overview
Problem
Current software testing methods often fail to identify all issues in a software program before its release, leading to unforeseen problems in customer environments due to inadequate characterization of client environments and workloads.
Innovation Solution
A method and system that cache historical and active workload data, calculate statistical measures, and generate workload report scores to provide proactive insights for improving software testing by comparing client and test environments, enabling timely and effective workload adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional software testing methods are used, then testing can be completed with standard procedures, but problems in the software program remain unidentified and testing accuracy is insufficient
Solution Approach 1:
The system performs preliminary actions by caching historical workload data and customer environment characteristics before the actual testing process. Statistical measures are pre-calculated and stored, allowing the testing system to quickly retrieve and apply relevant benchmarks during testing, thereby improving accuracy without proportionally increasing complexity
Solution Approach 2:
The invention creates copies of customer environment data and workload characteristics by caching historical data that replicates actual usage patterns. These cached copies serve as reference models for comparison during testing, enabling more accurate identification of software problems without requiring direct access to the customer's actual environment during testing operations
2Reliability
If detailed customer environment and workload profiling is performed, then testing improvements are achieved, but data processing time and system resources increase
Solution Approach 1:
The system performs workload profiling and environment characterization in advance, caching the results for future use. By pre-processing customer environment data and storing statistical measures, the system eliminates the need to re-analyze this data during each testing cycle, thereby maintaining high reliability while significantly reducing data processing time
Solution Approach 2:
The system dynamically adapts by selectively retrieving only the relevant cached data needed for specific testing scenarios. Rather than processing all available data, the system flexibly queries and uses only the portions of cached workload profiles and environment characteristics that are applicable to the current testing objectives, optimizing the balance between reliability and processing time
3Measurement precision
If workload data is cached and statistical measures are calculated, then workload assessment accuracy is improved, but system memory and processing resources are consumed
Solution Approach 1:
The system extracts only the essential statistical measures and key characteristics from the complete workload data sets. Rather than caching and processing entire data sets, the invention identifies and retains only the critical statistical parameters needed for accurate workload assessment, thereby improving measurement precision while minimizing system resource consumption
Solution Approach 2:
The system applies partial action by calculating and caching only the specific statistical measures that are most valuable for workload assessment comparisons. By focusing on a subset of the most relevant statistical parameters rather than computing all possible measures, the system achieves sufficient assessment accuracy while consuming fewer computational resources
Data Source
AI summary
Aspects of the present invention include a method, system and computer program product for providing automated run time and historical test workload report scoring. The method includes caching, by a processor, historical data relating to a customer workload; and caching, by the processor, data relating to an active workload test. The method also includes determining, by the processor, one or more statistical measures between the historical data relating to a customer workload and the data relating to an active workload test; generating, by the processor, one or more workload report scores based on the statistical measures; and displaying, by the processor, the one or more workload report scores.