Visible to the public Estimate Method Calls in Android Apps

TitleEstimate Method Calls in Android Apps
Publication TypeConference Paper
Year of Publication2016
AuthorsFrancese, Rita, Gravino, Carmine, Risi, Michele, Tortora, Genoveffa, Scanniello, Giuseppe
Conference NameProceedings of the International Conference on Mobile Software Engineering and Systems
Date PublishedMay 2016
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4178-3
KeywordsAndroid platform, empirical study, estimation models, pubcrawl170201

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.

Citation Keyfrancese_estimate_2016