# WebAPIRec: Recommending Web APIs to Software Projects via Personalized   Ranking

**Authors:** Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian

arXiv: 1705.00561 · 2018-03-02

## TL;DR

WebAPIRec is an automated, personalized ranking system that recommends relevant web APIs for software projects, significantly improving over existing search and recommendation methods by leveraging historical usage data.

## Contribution

It introduces a novel personalized ranking model for API recommendation that learns from historical usage data to improve accuracy in suggesting relevant APIs.

## Key findings

- Achieves 84% success rate in top-5 API recommendations
- Outperforms ProgrammableWeb's native search and other baseline methods
- Demonstrates effectiveness on a large dataset of APIs and projects

## Abstract

Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as many functionalities can be reused to achieve faster development. However, the massive number of APIs would often hinder the developers' ability to quickly find the right APIs. In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of {web} APIs that can be used to implement the project. At its heart, WebAPIRec employs a personalized ranking model that ranks web APIs specific (personalized) to a project. Based on the historical data of {web} API usages, WebAPIRec learns a model that minimizes the incorrect ordering of web APIs, i.e., when a used {web} API is ranked lower than an unused (or a not-yet-used) web API. We have evaluated our approach on a dataset comprising 9,883 web APIs and 4,315 web application projects from ProgrammableWeb with promising results. For 84.0% of the projects, WebAPIRec is able to successfully return correct APIs that are used to implement the projects in the top-5 positions. This is substantially better than the recommendations provided by ProgrammableWeb's native search functionality. WebAPIRec also outperforms McMillan et al.'s application search engine and popularity-based recommendation.

## Full text

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## Figures

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## References

42 references — full list in the complete paper: https://tomesphere.com/paper/1705.00561/full.md

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Source: https://tomesphere.com/paper/1705.00561