Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

API recommendation result evaluation method based on functional similarity

A similarity and function technology, applied in the field of API recommendation result evaluation based on function similarity, to achieve the effect of improving evaluation accuracy

Pending Publication Date: 2019-10-08
SOUTHEAST UNIV
View PDF4 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is a problem with this judgment method: the recommendation that is inconsistent with the correct result of the reference is not necessarily wrong, on the contrary, the recommendation result may still contribute to the programmer's programming

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • API recommendation result evaluation method based on functional similarity
  • API recommendation result evaluation method based on functional similarity
  • API recommendation result evaluation method based on functional similarity

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] Embodiment 1: see figure 1 , figure 2 , the present invention proposes a method for evaluating the correctness of recommended results based on the similarity of API functions, aiming at the non-0 or 1 method in the traditional API recommendation result correctness evaluation method. The similarity between two APIs is calculated from three dimensions, so as to obtain a contribution (between 0 and 1) of a recommended API. And on this basis, a calculation method is given on the calculation of the correctness of the results of the entire recommendation API set.

[0032] Architecture: figure 1 The design architecture of the API recommendation result evaluation technology based on functional similarity is given, as follows

[0033] A detailed description of the two main parts is given below.

[0034] 1. Calculation of the functional similarity Sim of two APIs (API1, API2);

[0035] The function of this module is to calculate the functional similarity Sim of two APIs by ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an API (Application Programming Interface) recommendation result evaluation method based on functional similarity. For the API recommendation result evaluation method, for cases where the recommendation result is a set of APIs, the function similarity between the recommended API and the correct API is measured through three dimensions of name similarity, API annotation relevance and API call graph similarity; and according to the similarity, the contribution value of the recommendation result set of the API recommendation system is evaluated, and the contribution valueis used for replacing 0 or 1 in a traditional evaluation method, and the correctness of the recommendation result is calculated, so that correctness evaluation is more accurate and is close to a manual evaluation result.

Description

technical field [0001] The invention relates to an evaluation method, in particular to an API recommendation result evaluation method based on functional similarity, and belongs to the technical field of API recommendation result evaluation. Background technique [0002] API (Application Programming Interface, application programming interface) recommendation is an important part of the code recommendation field. Its situation is to recommend the API that the developer wants based on a description or context. For a recommendation, the recommendation result of some systems is A collection of APIs. When evaluating recommendation results, correctness is often the performance that users care most about. The indicators for calculating correctness include precision, recall, etc., but in the calculation of these indicators, the traditional method is to compare the recommended results with the correct results. If they are exactly the same, it will be recorded as 1, otherwise it wil...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F11/34
CPCG06F11/3452Y02D10/00
Inventor 李必信韩伟娜孔祥龙
Owner SOUTHEAST UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products