Functionality-Clustered Code Search Within Relevant Software Packages
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing semantic and neural code search techniques struggle with identifying relevant code blocks within the correct software package, often requiring precise queries and facing scalability issues due to large code block databases, leading to inaccurate and inefficient searches.
Innovation Solution
Code blocks are clustered by functionality using embeddings, generating package, functionality, and code block embeddings, which are then used to accurately identify relevant code blocks within the correct software package, improving scalability and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing semantic and neural code search techniques are used to search through large databases of code blocks, then the search coverage increases, but the search accuracy decreases and the search efficiency deteriorates
Solution Approach 1:
The patent segments the code block database into multiple clusters based on functionality and software package context. Each cluster represents a subset of code blocks with similar characteristics, allowing the search system to navigate through organized groups rather than examining all code blocks individually. This segmentation maintains high search accuracy while enabling efficient searching across large databases.
Solution Approach 2:
The patent performs preliminary clustering and organization of code blocks into functionality-based groups before the actual search operation. By pre-processing the database to create structured clusters with metadata about software packages and functional categories, the system prepares the data in advance to enable fast and accurate retrieval without examining every code block during the search phase.
2Quantity of substance
If existing semantic and neural code search techniques are used to search through large databases of code blocks, then the search coverage increases, but the search efficiency decreases
Solution Approach 1:
The code block database is divided into multiple functionality-based clusters, each representing a specific domain or purpose. This segmentation allows the search system to quickly eliminate irrelevant clusters and focus only on those that match the query, dramatically improving search efficiency while maintaining the ability to search through large databases.
Solution Approach 2:
The system performs preliminary clustering and indexing of code blocks by functionality and software package context before searching. This pre-organization creates a structured framework that enables rapid navigation through the database, allowing efficient retrieval even when searching through large numbers of code blocks across multiple packages.
3Speed
If code blocks are searched without considering software package context, then the search speed increases, but the relevance of results decreases
Solution Approach 1:
The patent adds a new dimension to the search space by incorporating software package context as a filtering criterion alongside functionality-based clustering. This dimensional extension allows the system to maintain fast search speeds through organized clusters while simultaneously ensuring result relevance by considering the software package context in which code blocks reside.
Data Source
AI summary
A database stores, for each of a number of software packages, a software package embedding representing the software package. The database stores, for each software package, code block embeddings respectively representing code blocks of the software package. The database stores, for each software package, functionality embeddings respectively representing functionality clusters into which the code block embeddings representing the code blocks of the software package have been clustered. A query embedding representing a query is generated, and used to query the database to identify a relevant code block within a relevant software package for the query.