Machine-Mediated Requirement Management in Software Trials
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Solution Overview
Problem
Current solutions lack effective methods for managing and tracking software requirements in pre-sales processes, leading to inefficiencies, miscommunications, and increased costs due to poorly defined requirements, which can result in scope creep, delays, and unhappy customers.
Innovation Solution
A computer-implemented system for machine-mediated requirement management in a software trial management system, utilizing a distributed computer platform that enables centralized storage and management of requirements, allowing for two-party commit operations, visual progress tracking, and accountability through digital workspaces and electronic historical records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If requirements are manually managed through multiple reviewers and chains of approval, then accountability and review thoroughness are improved, but process time and operational complexity increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically notifying all reviewers of new requirements and prompting them to review before the requirement can be approved. This automated preliminary notification system ensures thorough review while reducing the time lost in manual coordination of reviewers.
2Measurement precision
If extensive datasets are collected around requirements to track progress and ensure alignment, then measurement precision and accountability are improved, but data management complexity and processing requirements increase
Solution Approach 1:
The requirement object serves multiple functions simultaneously: it stores the requirement definition, tracks review status, records approvals, maintains version history, and provides notification routing. This multi-functionality consolidates what would otherwise require separate complex data management systems into a single unified object.
Solution Approach 2:
The system implements nested data structures where reviewers are nested within requirement objects, approval statuses are nested within reviewer records, and version histories are nested within requirement objects. This hierarchical nesting organizes extensive datasets in a manageable, scalable manner.
3Adaptability or versatility
If multiple users and accounts are granted access to view and review requirements, then collaboration and alignment are improved, but system complexity and permission management increase
Solution Approach 1:
The system implements self-service mechanisms where reviewers automatically receive notifications and can independently access requirements for review without manual intervention. The requirement objects self-manage their reviewer lists and approval states, reducing the complexity of permission management.
4Loss of information
If visual progress tracking and real-time updates are implemented for requirement status, then transparency and alignment are improved, but computational resources and system complexity increase
Solution Approach 1:
The system implements feedback mechanisms where requirement objects automatically update their status and notify relevant users when changes occur. This automated feedback loop provides real-time transparency without requiring continuous polling or complex monitoring systems, as the system only computes when state changes occur.
Data Source
AI summary
In one embodiment, the disclosure provides a computer-implemented method comprising: generating a unique identifier associated with a digital electronic workspace, a project, a first account, and a second account; receiving, from the first account, input granting permissions to a second account; generating initial requirements data; receiving, a second input indicating a first set of one or more of the digital requirement objects to associate with the unique identifier; receiving, from the second account, a third input to generate and digitally store an additional digital requirement object and associating that object with the unique identifier; receiving input indicating consensus that the project should possess all the features described in natural language text summaries represented by the digital requirement objects; and changing a state value of a variable associated with the unique identifier to a new state and displaying an indication of the new state.