Estimate Method Calls in Android Apps

R. Francese, C. Gravino, M. Risi, G. Tortora, G. Scanniello
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引用次数: 1

Abstract

In this paper, we focus on the definition of estimators to predict method calls in Android apps. Estimation models are based on information from requirements specification documents (e.g., number of actors, number of use cases, and number of classes in the conceptual model). We have used a dataset containing information on 23 Android apps. After performing data-cleaning, we applied linear regression to build estimation models on 21 data points. Results suggest that measures gathered from requirements specification documents can be considered good predictors to estimate the number of internal calls (i.e., methods invoking other methods present in the app) and external calls (i.e., invocations to API) as well as their sum.
Android应用中的估算方法调用
在本文中,我们重点研究了估计器的定义,以预测Android应用程序中的方法调用。评估模型基于需求规范文档中的信息(例如,角色的数量,用例的数量,以及概念模型中的类的数量)。我们使用了一个包含23个Android应用程序信息的数据集。在执行数据清理后,我们应用线性回归对21个数据点构建估计模型。结果表明,从需求规范文档中收集的度量可以被认为是估计内部调用(即调用应用程序中存在的其他方法的方法)和外部调用(即对API的调用)的数量及其总和的良好预测器。
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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