Developers heavily rely on Application Programming Interfaces (APIs) from libraries to build their software. As software evolves, developers may need to replace the used libraries with alternate libraries, a process known as library migration. Doing this manually can be tedious, time-consuming, and prone to errors. Automated migration techniques can help alleviate some of this burden. However, designing effective automated migration techniques requires understanding the types of code changes required to transform client code that used the old library to the new library. This paper contributes an empirical study that provides a holistic view of Python library migrations, both in terms of the code changes required in a migration and the typical development effort involved. We manually label 1,902 migration-related code changes in 335 Python library migrations from 311 client repositories spanning 141 library pairs from 35 domains. Based on our labeled data, we derive a taxonomy for describing migration-related code changes, PyMigTax. Leveraging PyMigTax and our labeled data, we investigate various characteristics of Python library migrations, such as the types of program elements and properties of API mappings, the combinations of types of migration-related code changes in a migration, and the typical development effort required for a migration. Our findings highlight various potential shortcomings of current library migration tools. For example, we find that 40% of library pairs have API mappings that involve non-function program elements, while most library migration techniques typically assume that function calls from the source library will map into (one or more) function calls from the target library. As an approximation for the development effort involved, we find that, on average, a developer needs to learn about 4 APIs and 2 API mappings to perform a migration, and change 8 lines of code. However, we also found cases of migrations that involve up to 43 unique APIs, 22 API mappings, and 758 lines of code, making them harder to manually implement. Overall, our contributions provide the necessary knowledge and foundations for developing automated Python library migration techniques.
| poster - Characterizing Python Library Migrations (poster - Characterizing Python Library Migrations.pdf) | 306KiB |
Thu 18 JulDisplayed time zone: Brasilia, Distrito Federal, Brazil change
15:30 - 16:00 | |||
15:30 30mPoster | Can GPT-4 Replicate Empirical Software Engineering Research? Posters Jenny T. Liang Carnegie Mellon University, Carmen Badea Microsoft Research, Christian Bird Microsoft Research, Robert DeLine Microsoft Research, Denae Ford Microsoft Research, Nicole Forsgren Microsoft Research, Thomas Zimmermann Microsoft Research | ||
15:30 30mPoster | Evaluating Directed Fuzzers: Are We Heading in the Right Direction? Posters Tae Eun Kim KAIST, Jaeseung Choi Sogang University, Seongjae Im KAIST, Kihong Heo KAIST, Sang Kil Cha KAIST Link to publication Media Attached File Attached | ||
15:30 30mPoster | Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detection Posters Yuxi Li Huazhong University of Science and Technology, Yi Liu Nanyang Technological University, Gelei Deng Nanyang Technological University, Ying Zhang Virginia Tech, Wenjia Song Virginia Tech, Ling Shi Nanyang Technological University, Kailong Wang Huazhong University of Science and Technology, Yuekang Li The University of New South Wales, Yang Liu Nanyang Technological University, Haoyu Wang Huazhong University of Science and Technology | ||
15:30 30mPoster | Do Words Have Power? Understanding and Fostering Civility in Code Review Discussion Posters Md Shamimur Rahman University of Saskatchewan, Canada, Zadia Codabux University of Saskatchewan, Chanchal K. Roy University of Saskatchewan, Canada | ||
15:30 30mPoster | CodePlan: Repository-level Coding using LLMs and Planning Posters Ramakrishna Bairi Microsoft Research, India, Atharv Sonwane Microsoft Research, India, Aditya Kanade Microsoft Research, India, Vageesh D C Microsoft Research, India, Arun Iyer Microsoft Research, India, Suresh Parthasarathy Microsoft Research, India, Sriram Rajamani Microsoft Research Indua, B. Ashok Microsoft Research. India, Shashank Shet Microsoft Research. India | ||
15:30 30mPoster | Understanding and Detecting Annotation-induced Faults of Static Analyzers Posters Huaien Zhang The Hong Kong Polytechnic University, Southern University of Science and Technology, Yu Pei The Hong Kong Polytechnic University, Shuyun Liang Southern University of Science and Technology, Shin Hwei Tan Concordia University | ||
15:30 30mPoster | Partial Solution Based Constraint Solving Cache in Symbolic Execution Posters Ziqi Shuai School of Computer, National University of Defense Technology, China, Zhenbang Chen College of Computer, National University of Defense Technology, Kelin Ma School of Computer, National University of Defense Technology, China, Kunlin Liu School of Computer, National University of Defense Technology, China, Yufeng Zhang Hunan University, Jun Sun School of Information Systems, Singapore Management University, Singapore, Ji Wang School of Computer, National University of Defense Technology, China | ||
15:30 30mPoster | Characterizing Python Library Migrations Posters Mohayeminul Islam University of Alberta, Ajay Jha North Dakota State University, Ildar Akhmetov Northeastern University, Sarah Nadi New York University Abu Dhabi, University of Alberta File Attached | ||
15:30 30mPoster | DeSQL: Interactive Debugging of SQL in Data-Intensive Scalable Computing Posters | ||
15:30 30mPoster | BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection Posters | ||
15:30 30mPoster | Less Cybersickness, Please: Demystifying and Detecting Stereoscopic Visual Inconsistencies in Virtual Reality Applications Posters Shuqing Li The Chinese University of Hong Kong, Cuiyun Gao Harbin Institute of Technology, Jianping Zhang The Chinese University of Hong Kong, Yujia Zhang Harbin Institute of Technology, Yepang Liu Southern University of Science and Technology, Jiazhen Gu The Chinese University of Hong Kong, Yun Peng The Chinese University of Hong Kong, Michael Lyu The Chinese University of Hong Kong | ||
15:30 30mPoster | CORE: Resolving Code Quality Issues Using LLMs Posters Nalin Wadhwa Microsoft Research, India, Jui Pradhan Microsoft Research, India, Atharv Sonwane Microsoft Research, India, Surya Prakash Sahu Microsoft Research, India, Nagarajan Natarajan Microsoft Research India, Aditya Kanade Microsoft Research, India, Suresh Parthasarathy Microsoft Research, India, Sriram Rajamani Microsoft Research Indua | ||
15:30 30mPoster | Abstraction-Aware Inference of Metamorphic Relations Posters Agustin Nolasco University of Rio Cuarto, Facundo Molina IMDEA Software Institute, Renzo Degiovanni Luxembourg Institute of Science and Technology, Alessandra Gorla IMDEA Software Institute, Diego Garbervetsky Departamento de Computación, FCEyN, UBA, Mike Papadakis University of Luxembourg, Sebastian Uchitel Imperial College and University of Buenos Aires, Nazareno Aguirre University of Rio Cuarto and CONICET, Marcelo F. Frias Dept. of Software Engineering Instituto Tecnológico de Buenos Aires | ||
15:30 30mPoster | State Reconciliation Defects in Infrastructure as Code Posters Md Mahadi Hassan Auburn University, John Salvador Auburn University, Shubhra Kanti Karmaker Santu Auburn University, Akond Rahman Auburn University | ||
This room is conjoined with the Foyer to provide additional space for the coffee break, and hold poster presentations throughout the event.