Automated Software Change Management via Risk-Based Test Scheduling
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Solution Overview
Problem
The management of software changes is heavily reliant on human operators, leading to errors and delays due to oversights, and existing methods lack automation for efficient testing and approval processes.
Innovation Solution
A computer-implemented method for automating software change management, which includes receiving change requests, assessing risk levels, scheduling tests, initiating testing operations, determining test failures, and generating communication bridges between stakeholders, with features like administrator approval requests and machine learning-based test case corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review and testing of software modifications is performed by human operators, then proper functioning and throughput can be ensured, but software testing errors and development delays occur due to operator oversights
Solution Approach 1:
The system performs self-assessment of risk levels and self-scheduling of testing operations through automated algorithms. The processor automatically evaluates change request data objects, determines risk levels without human intervention, and schedules testing operations based on the assessed risk, enabling the system to serve itself rather than relying on human operators for these tasks.
Solution Approach 2:
The patent replaces the mechanical system of manual human review and testing scheduling with an automated computational system. The processor executes algorithms that automatically assess risk levels, generate test scheduling data objects, and initiate testing operations, substituting human cognitive and manual processes with automated mechanical-computational processes.
2Productivity
If automated risk assessment and test scheduling is implemented, then testing throughput and efficiency are improved, but system complexity increases
Solution Approach 1:
The automated system is segmented into distinct functional modules: a risk assessment module that evaluates change request data objects and determines risk levels, a test scheduling module that generates test scheduling data objects based on risk levels, and a testing execution module that initiates and monitors testing operations. This segmentation allows each module to perform its specific function independently, managing complexity through functional decomposition.
Solution Approach 2:
The system performs preliminary risk assessment before scheduling testing operations. By evaluating the change request data object and determining the risk level in advance, the system can proactively schedule appropriate testing operations without waiting for manual review, thereby improving throughput while keeping the automation logic straightforward and predictable.
3Reliability
If comprehensive testing operations are initiated for all software modifications, then testing coverage is improved, but time consumption and resource usage increase
Solution Approach 1:
The system applies different testing strategies based on local characteristics of each software modification. By assessing the risk level of individual change request data objects and tailoring the testing operations to the specific risk profile of each modification, the system ensures comprehensive testing coverage for high-risk changes while reducing testing time for low-risk changes, optimizing both reliability and time efficiency.
Solution Approach 2:
The system dynamically changes the parameters of testing operations based on the assessed risk level. For high-risk modifications, more extensive testing parameters are applied, while for low-risk modifications, reduced testing parameters are used. This parameter adaptation allows the system to maintain testing coverage where needed while minimizing time consumption overall.
Data Source
AI summary
Embodiments of the disclosure provide for improved automation of software change management. Such embodiments enable automatically managing and testing software modifications. Some embodiments receive a change request data object indicative of a software modification, generate a risk level of the software modification based on the change request data object, and generate a test scheduling data object based on the change request data object and the risk level, where the test scheduling data object is indicative of a testing operation for the software modification. Some embodiments initiate performance of the testing operation at a testing environment and receive, from the testing environment, test performance data. Some embodiments determine a test failure based on the test performance data and, in response to determining the test failure, generate a communication bridge between a subset of a plurality of computing devices based on the test failure and a development flow data object.