skip to main content
10.1145/2897073.2897113acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
poster

Estimate method calls in Android apps

Published:14 May 2016Publication 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.

References

  1. V. R. Basili, L. C. Briand, and W. L. Melo. A Validation of Object-Oriented Design Metrics as Quality Indicators. IEEE Trans. on Soft. Eng., 22(10):751--761, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. 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.Google ScholarGoogle ScholarCross RefCross Ref
  3. B. Bruegge and A. H. Dutoit. Object-Oriented Software Engineering: Using UML, Patterns and Java. Prentice-Hall, 2nd edition, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. 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. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. 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. Google ScholarGoogle ScholarDigital LibraryDigital Library

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    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

    Copyright © 2016 Owner/Author

    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.

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 14 May 2016

    Check for updates

    Qualifiers

    • poster

    Upcoming Conference

    ICSE 2025

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader