A Large-Scale Empirical Study on Software Reuse in Mobile Apps

被引：82

作者：

Mojica, Israel J. ^{[1
]}

Adams, Bram ^{[2
]}

Nagappan, Meiyappan ^{[3
]}

Dienst, Steffen ^{[4
]}

Berger, Thorsten ^{[5
]}

Hassan, Ahmed E. ^{[6
]}

机构：

[1] McAfee, Santa Clara, CA USA

[2] Ecole Polytech Montreal, MCIS Maintenance Construct & Intelligence Softwar, Montreal, PQ, Canada

[3] Queens Univ, SAIL, Kingston, ON K7L 3N6, Canada

[4] Univ Leipzig, Chair Business Informat Syst, D-04109 Leipzig, Germany

[5] Univ Waterloo, Generat Software Dev Lab, Waterloo, ON N2L 3G1, Canada

[6] Queens Univ, Sch Comp, Kingston, ON K7L 3N6, Canada

来源：

IEEE SOFTWARE | 2014年 / 31卷 / 02期

关键词：

Android; mobile apps; software reuse;

D O I：

10.1109/MS.2013.142

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In less than five years, the number of mobile apps has grown exponentially, with more than 1 million available in the largest mobile app stores. One explanation for this growth could be the adoption of well-proven software engineering practices-in particular, software reuse despite the often conjectured lack of training among mobile app developers. A study of hundreds of thousands of Android apps across 30 different categories found substantial software reuse, indicating that while these apps benefit from increased productivity, they're also more dependent on the quality of the apps and libraries that they reuse. © 1984-2012 IEEE.

引用

页码：78 / 86

页数：9

共 50 条

[1] Testing of Mobile Applications in the Wild: A Large-Scale Empirical Study on Android Apps
Pecorelli, Fabiano
Catolino, Gemma
Ferrucci, Filomena
De Lucia, Andrea
Palomba, Fabio
2020 IEEE/ACM 28TH INTERNATIONAL CONFERENCE ON PROGRAM COMPREHENSION, ICPC, 2020, : 296 - 307
[2] A Large-Scale Empirical Study on Industrial Fake Apps
Tang, Chongbin
Chen, Sen
Fan, Lingling
Xu, Lihua
Liu, Yang
Tang, Zhushou
Dou, Liang
2019 IEEE/ACM 41ST INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN PRACTICE (ICSE-SEIP 2019), 2019, : 183 - 192
[3] Quantifying reuse in OSS: A large-scale empirical study
Constantinou, Eleni
Ampatzoglou, Apostolos
Stamelos, Ioannis
International Journal of Open Source Software and Processes, 2014, 5 (03) : 1 - 19
[4] Software Protection on the Go: A Large-Scale Empirical Study on Mobile App Obfuscation
Wang, Pei
Bao, Qinkun
Wang, Li
Wang, Shuai
Chen, Zhaofeng
Wei, Tao
Wu, Dinghao
PROCEEDINGS 2018 IEEE/ACM 40TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE), 2018, : 26 - 36
[5] DEVELOPING SOFTWARE FOR LARGE-SCALE REUSE
SEIDEWITZ, E
BALFOUR, B
ADAMS, SS
WADE, DM
COX, B
SIGPLAN NOTICES, 1993, 28 (10): : 137 - 143
[6] A Large-scale Investigation into Geodifferences in Mobile Apps
Kumar, Renuka
Virkud, Apurva
Raman, Ram Sundara
Prakash, Atul
Ensafi, Roya
PROCEEDINGS OF THE 31ST USENIX SECURITY SYMPOSIUM, 2022, : 1203 - 1220
[7] A LARGE-SCALE EMPIRICAL STUDY ON THE COGNITIVE COMPLEXITY OF SOFTWARE
Chiew, Vincent
Wang, Yingxu
2010 23RD CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE), 2010,
[8] Is It a Trap? A Large-scale Empirical Study And Comprehensive Assessment of Online Automated Privacy Policy Generators for Mobile Apps
Pan, Shidong
Zhang, Dawen
Staples, Mark
Xing, Zhenchang
Chen, Jieshan
Xu, Xiwei
Thong Hoang
PROCEEDINGS OF THE 33RD USENIX SECURITY SYMPOSIUM, SECURITY 2024, 2024, : 5681 - 5698
[9] MobileRec: A Large-Scale Dataset for Mobile Apps Recommendation
Maqbool, M. H.
Farooq, Umar
Mosharrof, Adib
Siddique, A. B.
Foroosh, Hassan
PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023, 2023, : 3007 - 3016
[10] Software testing and Android applications: a large-scale empirical study
Pecorelli, Fabiano
Catolino, Gemma
Ferrucci, Filomena
De Lucia, Andrea
Palomba, Fabio
EMPIRICAL SOFTWARE ENGINEERING, 2022, 27 (02)

← 1 2 3 4 5 →