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Estimate method calls in Android apps

Published: 14 May 2016 Publication History

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.

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G. Bavota, M. L. Vásquez, C. E. Bernal-Cárdenas, M. Di Penta, R. Oliveto, and D. Poshyvanyk. The Impact of API Change- and Fault-Proneness on the User Ratings of Android Apps. IEEE Trans. on Softw. Eng., 41(4):384--407, 2015.
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B. Bruegge and A. H. Dutoit. Object-Oriented Software Engineering: Using UML, Patterns and Java. Prentice-Hall, 2nd edition, 2003.
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R. Francese, C. Gravino, M. Risi, G. Scanniello, and G. Tortora. Using Project-Based-Learning in a Mobile Application Development Course: An Experience Report. J. of Vis. Lang. and Comp., 31:196--205, 2015.
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M. L. Vásquez, G. Bavota, C. Bernal-Cárdenas, R. Oliveto, M. D. Penta, and D. Poshyvanyk. Mining Energy-Greedy API Usage Patterns in Android Apps: An Empirical Study. In Proc. of Working Conf. on Mining Soft. Repositories, pages 2--11. ACM Press, 2014.

Cited By

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  • (2018)Effort Estimation across Mobile App Platforms using Agile Processes: A Systematic Literature ReviewJournal of Software10.17706/jsw.13.4.242-25913:4(242-259)Online publication date: Apr-2018

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cover image ACM Conferences
MOBILESoft '16: Proceedings of the International Conference on Mobile Software Engineering and Systems
May 2016
326 pages
ISBN:9781450341783
DOI:10.1145/2897073
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 May 2016

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Author Tags

  1. Android platform
  2. empirical study
  3. estimation models

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Cited By

View all
  • (2018)Effort Estimation across Mobile App Platforms using Agile Processes: A Systematic Literature ReviewJournal of Software10.17706/jsw.13.4.242-25913:4(242-259)Online publication date: Apr-2018

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