Automated Technology Recommendation System for Software Development
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Solution Overview
Problem
Developing software applications for web and mobile devices is time-consuming and economically wasteful due to the vast number of technological choices available, requiring developers to consult colleagues and search online resources.
Innovation Solution
An interactive system comprising a client device and a server with a knowledge base that receives user input through a query tree or GUI, analyzes requirements, and automatically recommends suitable software technologies such as frameworks, languages, and platforms for efficient development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If developers manually research and consult resources to select software technologies, then technology selection accuracy is improved, but development time and costs increase
Solution Approach 1:
The system enables automated technology recommendation by having the server autonomously analyze software environment requirements and generate recommendations without requiring manual developer intervention for research and consultation, thus reducing development time while maintaining selection accuracy
Solution Approach 2:
The patent replaces the manual mechanical process of developer research and consultation with an automated computational system that analyzes requirements and generates technology recommendations algorithmically, eliminating time-consuming human activities while preserving decision quality
2Measurement precision
If developers manually research and consult resources to select software technologies, then technology selection accuracy is improved, but economic costs increase
Solution Approach 1:
The automated recommendation system performs the research and analysis functions that would otherwise require human developer time and external consulting resources, converting these economic costs into automated computational processes that are more cost-effective
Solution Approach 2:
The system substitutes expensive manual research activities with automated server-based analysis, replacing human expertise consultation with algorithmic recommendation generation, thereby reducing economic costs while maintaining technology selection accuracy
3Measurement precision
If comprehensive technology research is conducted, then recommendation quality is improved, but system complexity increases
Solution Approach 1:
The system segments the complex technology recommendation process into distinct modular components: requirement reception module, knowledge base module, analysis module, and recommendation generation module, making the system more manageable and maintainable while comprehensively analyzing software environment requirements
Solution Approach 2:
The patent introduces a structured query tree as an intermediary data structure that organizes software environment requirements into standardized categories, simplifying the analysis process and enabling systematic recommendation generation without overwhelming system complexity
Data Source
AI summary
A method includes receiving, by a computer, input from a client device. The input is indicative of a software environment for software to be developed by a user. The method further includes analyzing, by the computer, the received input against a knowledge base to generate a technology recommendation for the user to use to develop the software. The method also includes providing, by the computer, the technology recommendation to the client device.