research-article

On the Variations and Evolutions of API Usage Patterns: Case Study on Android Applications

Authors:

Koki Ogasawara,

Tetsuya Kanda, and

Katsuro InoueAuthors Info & Claims

ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops

June 2020

Pages 746 - 753

https://doi.org/10.1145/3387940.3392203

Published: 25 September 2020 Publication History

Abstract

Software developers can reduce the implementation cost by calling already provided functions through accessing library Application Programming Interface (API). APIs are often used in combination but how to combine them are not well-documented. Existing researches focused on how to extract API usage patterns or how to detect API misuse from existing software. This kind of research might be affected by dataset to analyze, so to improve mining results and to understand how the difference of API usage patterns affect the software health are important tasks. We conducted an analysis on variations of API usage pattern among software projects and their version history with Android SDK APIs and Android applications. Based on our analysis results, we made some suggestions for further API analysis. For example, there are many project-specific API usage patterns and long-life uncommon API usage patterns so that they might affect the mining result or checking software health status.

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Cited By

Huang ZChen JJiang JLiang YYou HLi F(2024)Mapping APIs in Dynamic-typed Programs by Leveraging Transfer LearningACM Transactions on Software Engineering and Methodology10.1145/3641848Online publication date: 22-Jan-2024
https://doi.org/10.1145/3641848
Almahmoud MAlzu’bi DYaseen Q(2021)ReDroidDet: Android Malware Detection Based on Recurrent Neural NetworkProcedia Computer Science10.1016/j.procs.2021.03.105184(841-846)Online publication date: 2021
https://doi.org/10.1016/j.procs.2021.03.105
Liu LLi XLiu YLiu H(2021)Application programming interface recommendation according to the knowledge indexed by app feature mined from app storesJournal of Software: Evolution and Process10.1002/smr.238033:11Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1002/smr.2380
Show More Cited By

Index Terms

On the Variations and Evolutions of API Usage Patterns: Case Study on Android Applications
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Maintaining software
      2. Software evolution

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cover image ACM Conferences

ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops

June 2020

831 pages

ISBN:9781450379632

DOI:10.1145/3387940

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSOFT: ACM Special Interest Group on Software Engineering
KIISE: Korean Institute of Information Scientists and Engineers
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New York, NY, United States

Publication History

Published: 25 September 2020

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Japan Society for the Promotion of Science

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ICSE '20

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SIGSOFT
KIISE

ICSE '20: 42nd International Conference on Software Engineering

June 27 - July 19, 2020

Seoul, Republic of Korea

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ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

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Cited By

Huang ZChen JJiang JLiang YYou HLi F(2024)Mapping APIs in Dynamic-typed Programs by Leveraging Transfer LearningACM Transactions on Software Engineering and Methodology10.1145/3641848Online publication date: 22-Jan-2024
https://doi.org/10.1145/3641848
Almahmoud MAlzu’bi DYaseen Q(2021)ReDroidDet: Android Malware Detection Based on Recurrent Neural NetworkProcedia Computer Science10.1016/j.procs.2021.03.105184(841-846)Online publication date: 2021
https://doi.org/10.1016/j.procs.2021.03.105
Liu LLi XLiu YLiu H(2021)Application programming interface recommendation according to the knowledge indexed by app feature mined from app storesJournal of Software: Evolution and Process10.1002/smr.238033:11Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1002/smr.2380
Kim MKim N(2020)Mining Hidden and Fragmented API Usages in Android ApplicationsApplied Sciences10.3390/app1024904810:24(9048)Online publication date: 17-Dec-2020
https://doi.org/10.3390/app10249048

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