Software Transport Compliance Checking in Upgrade Context
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Solution Overview
Problem
Upgrading individual software components within complex software landscapes is challenging due to subtle interconnections, leading to wide-ranging ramifications that are not readily apparent, making it difficult to assess and ensure compliance before full impact analysis, which can result in last-minute compliance problems and potential system downtime.
Innovation Solution
Implementing early assessment of upgrade compliance checking on production data before execution, using discrete compliance checks in a pre-transport phase and bundled checks in a transport phase, with results reported to developers and higher-level users, and condensing data to bi-value states to reduce storage volume and enhance security, allowing for early indication of compliance violations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full impact analysis is performed to ensure upgrade compliance, then compliance reliability is improved, but system downtime increases and productivity decreases
Solution Approach 1:
The patent performs upgrade compliance checks in advance during development and transport phases, condensing production data to bi-value states and executing discrete compliance checks before full impact analysis. This preliminary action identifies potential compliance issues early, allowing them to be resolved before production deployment, thereby ensuring compliance reliability while minimizing system downtime and maintaining productivity.
2Measurement precision
If production data is stored in full detail for compliance checking, then measurement precision is improved, but data storage volume increases
Solution Approach 1:
The patent transforms production data from its original detailed state to a condensed bi-value state (e.g., present/absent, true/false) that retains sufficient information for compliance checking while dramatically reducing storage requirements. This parameter change maintains measurement precision for compliance determination while minimizing the quantity of stored data.
3Quantity of substance
If production data is condensed to bi-value states, then data storage volume is reduced and security is enhanced, but information detail is lost
Solution Approach 1:
The patent extracts only the essential information needed for compliance checking from the full production data, condensing it to bi-value states that capture critical compliance-relevant details while discarding redundant information. This extraction process reduces storage volume and enhances security by limiting exposed data while retaining sufficient detail for accurate compliance assessment.
4Loss of time
If discrete compliance checks are performed in pre-transport phase, then compliance issues are detected early, but development complexity increases
Solution Approach 1:
The patent segments the compliance checking process into distinct phases: discrete checks during development, additional checks during transport, and full impact analysis before production. Each segment handles specific compliance aspects with appropriate data condensation levels, reducing overall complexity while enabling early detection of compliance issues and minimizing rework.
Data Source
AI summary
Embodiments offer early assessment of upgrade compliance checking upon software landscape production data, prior to actually executing a full impact analysis. In a pre-transport phase, discrete upgrade compliance checks are run and corresponding reports returned to individual developers. In a transport phase, batches of combined compliance checks (bundled into released transports) are run and corresponding reports returned to higher level users. According to certain embodiments, pre-transport and/or transport compliance checking is performed upon landscape production data condensed to a bi-value states. Such condensing can desirably reduce stored data volumes and impart security. According to some embodiments, pre-transport and/or transport compliance checking is performed upon production data merged across multiple landscapes. This avoids storing redundant upgrade check data. Early indication of compliance checking violations, can reduce the incidence of last-minute compliance problems arising during subsequent full impact analysis (which is fraught with potential consequences for system down-time).