A Large-scale Investigation of Semantically Incompatible APIs behind Compatibility Issues in Android Apps

Language models are few-shot learners

Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901

Earlier work this paper cites.

Determining sample size

Glenn D Israel et al · 1992

Earlier work this paper cites.

Semantic topic models for source code analysis

Anas Mahmoud and Gary Bradshaw. 2017 · 2000

Earlier work this paper cites.

Answering the call for a standard reliability measure for coding data

Andrew F Hayes and Klaus Krippendorff. 2007 · 2007

Earlier work this paper cites.

Semantic clustering: Identifying topics in source code

Adrian Kuhn, Stéphane Ducasse, and Tudor Gîrba. 2007 · 2007

Earlier work this paper cites.

Mobile application compatibility test system design for android fragmentation. In International Conference on Advanced Software Engineering and Its Applications . Springer, 314–320

Hyung Kil Ham and Young Bom Park. 2011 · 2011

Earlier work this paper cites.

Compatibility testing service for mobile applications. In 2015 IEEE Symposium on Service-Oriented System Engineering . IEEE, 179–186

Tao Zhang, Jerry Gao, Jing Cheng, and Tadahiro Uehara. 2015 · 2015

Earlier work this paper cites.

Target fragmentation in Android apps. In 2016 IEEE Security and Privacy Workshops (SPW) . IEEE, 204–213

Patrick Mutchler, Yeganeh Safaei, Adam Doupé, and John Mitchell. 2016 · 2016

Earlier work this paper cites.

Taming Android fragmentation: Characterizing and detecting compatibility issues for Android apps. In Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering . 226–237

Lili Wei, Yepang Liu, and Shing-Chi Cheung. 2016 · 2016

Earlier work this paper cites.

Attention is all you need

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017

Earlier work this paper cites.

An explorative study of the mobile app ecosystem from app developers’ perspective. In Proceedings of the 26th international conference on World Wide Web . 163–172

Haoyu Wang, Zhe Liu, Yao Guo, Xiangqun Chen, Miao Zhang, Guoai Xu, and Jason Hong. 2017 · 2017

Earlier work this paper cites.

Understanding and detecting callback compatibility issues for android applications. In Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering . 532–542

Huaxun Huang, Lili Wei, Yepang Liu, and Shing-Chi Cheung. 2018 · 2018

Earlier work this paper cites.

Cid: Automating the detection of api-related compatibility issues in android apps. In Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis . 153–163

Li Li, Tegawendé F Bissyandé, Haoyu Wang, and Jacques Klein. 2018 · 2018

Earlier work this paper cites.

A Survey on Android Malware Detection Techniques Using Machine Learning Algorithms. In 2019 Sixth International Conference on Software Defined Systems (SDS) . 110–117

Ebtesam J. Alqahtani, Rachid Zagrouba, and Abdullah Almuhaideb. 2019 · 2019

Earlier work this paper cites.

Pivot: learning API-device correlations to facilitate Android compatibility issue detection. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) . IEEE, 878–888

Lili Wei, Yepang Liu, and Shing-Chi Cheung. 2019 · 2019

Earlier work this paper cites.

Androzooopen: Collecting large-scale open source android apps for the research community. In Proceedings of the 17th International Conference on Mining Software Repositories . 548–552

Pei Liu, Li Li, Yanjie Zhao, Xiaoyu Sun, and John Grundy. 2020 · 2020

Earlier work this paper cites.

Short Text Topic Modeling Techniques, Applications, and Performance: A Survey

Jipeng Qiang, Zhenyu Qian, Yun Li, Yunhao Yuan, and Xindong Wu. 2022 · 2020

Earlier work this paper cites.

A survey of android malware detection with deep neural models

Junyang Qiu, Jun Zhang, Wei Luo, Lei Pan, Surya Nepal, and Yang Xiang. 2020 · 2020

Earlier work this paper cites.

Cosqa: 20,000+ web queries for code search and question answering

Original

Junjie Huang, Duyu Tang, Linjun Shou, Ming Gong, Ke Xu, Daxin Jiang, Ming Zhou, and Nan Duan. 2021 · 2021

Earlier work this paper cites.

Identifying and characterizing silently-evolved methods in the android API. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP 2021) . IEEE, 308–317

Pei Liu, Li Li, Yichun Yan, Mattia Fazzini, and John Grundy. 2021 · 2021

Earlier work this paper cites.

Android Compatibility Issue Detection Using API Differences. In 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) . 480–490

Tarek Mahmud, Meiru Che, and Guowei Yang. 2021 · 2021

Earlier work this paper cites.

Manipulating and Measuring Model Interpretability. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21) . Association for Computing Machinery, New York, NY, USA, Article 237, 52 pages

Forough Poursabzi-Sangdeh, Daniel G Goldstein, Jake M Hofman, Jennifer Wortman Wortman Vaughan, and Hanna Wallach. 2021 · 2021

Earlier work this paper cites.

Topic modeling in software engineering research

Camila Costa Silva, Matthias Galster, and Fabian Gilson. 2021 · 2021

Earlier work this paper cites.

Taming reflection: An essential step toward whole-program analysis of android apps

Xiaoyu Sun, Li Li, Tegawendé F Bissyandé, Jacques Klein, Damien Octeau, and John Grundy. 2021 · 2021

Cited alongside, same era.

Calibrate before use: Improving few-shot performance of language models. In International conference on machine learning . PMLR, 12697–12706

Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021

Cited alongside, same era.

SE Factual Knowledge in Frozen Giant Code Model: A Study on FQN and its Retrieval

Original

Qing Huang, Dianshu Liao, Zhenchang Xing, Zhiqiang Yuan, Qinghua Lu, Xiwei Xu, and Jiaxing Lu. 2022 · 2022

Cited alongside, same era.

JuCify: a step towards Android code unification for enhanced static analysis. In 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) . IEEE, 1232–1244

Jordan Samhi, Jun Gao, Nadia Daoudi, Pierre Graux, Henri Hoyez, Xiaoyu Sun, Kevin Allix, Tegawendé F Bissyandé, and Jacques Klein. 2022 · 2022

Cited alongside, same era.

Android source code vulnerability detection: a systematic literature review

Janaka Senanayake, Harsha Kalutarage, Mhd Omar Al-Kadri, Andrei Petrovski, and Luca Piras. 2023 · 2023

Later among the works it cites.

Towards expert-level medical question answering with large language models

Original

Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, et al · 2023

Later among the works it cites.

Android app crashing java.lang.NoSuchMethodError

Stack OverFlow. 2023a · 2023

Later among the works it cites.

NoClassDefFoundError: Class not found using the boot loader class loader Android Studio

Stack OverFlow. 2023b · 2023

Later among the works it cites.

Automatic Code Summarization via ChatGPT: How Far Are We?

Original

Weisong Sun, Chunrong Fang, Yudu You, Yun Miao, Yi Liu, Yuekang Li, Gelei Deng, Shenghan Huang, Yuchen Chen, Quanjun Zhang, et al · 2023