Parallel Software Instance Execution for Decision Path Optimization
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Solution Overview
Problem
Computer software applications often experience delays due to user indecision when presented with selection options, leading to costly inefficiencies.
Innovation Solution
The method involves duplicating a primary instance of a software application into multiple execution contexts and selecting different subsets of predefined elements for each duplicate instance, allowing execution to continue along various paths without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the application waits for user selection to proceed, then the user can make an informed decision, but the execution time increases and productivity decreases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and preparing multiple possible execution paths before the user makes a selection. Multiple instances of the application are executed in parallel, each following a different predefined path, so that when the user selects an option, the corresponding path is already ready to continue execution immediately, eliminating waiting time.
Solution Approach 2:
The system creates multiple copies (instances) of the application simultaneously, each copy pursuing a different execution path. This allows the application to explore multiple possibilities in parallel rather than sequentially, effectively preparing multiple futures at once so that the user's selection can immediately redirect to the desired path without delay.
2Productivity
If multiple execution paths are prepared in advance, then execution speed improves, but the system complexity increases
Solution Approach 1:
The system segments the execution paths into distinct, independent branches that can be managed separately. Each path is divided into manageable segments with clear decision points, allowing the system to control and coordinate multiple parallel executions without becoming overwhelming. This segmentation enables straightforward management of complexity through structured organization.
Solution Approach 2:
The system dynamically adjusts the execution strategy based on user input and system state. Rather than rigidly following predetermined paths, the system can adaptively select which paths to pursue based on real-time conditions, making the complexity management flexible and responsive. This dynamic approach allows the system to optimize performance while managing complexity through adaptability.
3Adaptability or versatility
If the application presents multiple options to the user, then the user can choose the best path, but the time required for selection increases
Solution Approach 1:
The system performs preliminary evaluation of multiple paths and prepares their execution states in advance. By pre-computing the implications and readiness status of each option, the system enables the user to make selections more quickly, as the necessary preparation work is already done before the user needs to decide.
Solution Approach 2:
The system provides feedback to the user about the status and implications of different paths, helping the user make more informed and faster decisions. By displaying information about which paths are ready, their estimated outcomes, and their current execution states, the system reduces the cognitive load and time required for the user to make a selection.
Data Source
AI summary
Managing the execution of a computer software application by duplicating a primary instance of a computer software application during its execution in a primary execution context to create multiple duplicate instances of the computer software application in corresponding duplicate execution contexts, and effecting a selection of a different candidate subset of predefined elements for each of the duplicate instances.


