推荐带有隐马尔可夫模型的移动应用的API用法

2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2015-11-09 DOI:10.1109/ASE.2015.109

Tam The Nguyen, H. Pham, P. Vu, T. Nguyen

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引用次数: 50

摘要

移动应用通常严重依赖于标准的API框架和库。然而，由于API框架的快速变化以及文档和代码示例的不足，学习使用这些API通常是具有挑战性的。本文介绍了Android移动应用API使用推荐工具DroidAssist。DroidAssist的核心是HAPI，一个基于隐马尔可夫模型的API使用统计生成模型。通过从现有移动应用程序中训练的hapi, DroidAssist可以为方法调用执行代码补全。它还可以检查现有的调用序列，以检测和修复可疑的(即不受欢迎的)API使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Recommending API Usages for Mobile Apps with Hidden Markov Model

Mobile apps often rely heavily on standard API frameworks and libraries. However, learning to use those APIs is often challenging due to the fast-changing nature of API frameworks and the insufficiency of documentation and code examples. This paper introduces DroidAssist, a recommendation tool for API usages of Android mobile apps. The core of DroidAssist is HAPI, a statistical, generative model of API usages based on Hidden Markov Model. With HAPIs trained from existing mobile apps, DroidAssist could perform code completion for method calls. It can also check existing call sequences to detect and repair suspicious (i.e. unpopular) API usages.

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2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)

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