The Sustainability Face of Automated Program Repair Tools
Automated program repair (APR) aims to automatize the process of repairing software bugs in order to reduce the cost of maintaining software programs. While APR accuracy has significantly improved in recent years, its energy impact remains unstudied. The field of green software research aims to measure the energy consumption required to develop, maintain, and use software products. Our main goal is to define the foundation for measuring the energy consumption of the APR activity. We state that an environmentally \emph{sustainable (or green) APR tool} achieves a good balance between the ability to correctly repair bugs and the amount of energy consumed during such process. We measure the energy consumption of ten traditional APR tools for Java and eleven fine-tuned Large-Language Models (LLM) trying to repair real bugs from Defects4J. The results of this study show the existing trade-off between energy consumption and repairability. In particular, APR tools such as TBar and RepairLlama repair more bugs than other approaches at the expense of a higher energy consumption. Other tools, such as SimFix and the LLM CodeT5-Large, provide a good trade-off between energy consumption and repairability. We also present guidelines consisting of a set of recommendations for developing greener APR.
Fri 17 AprDisplayed time zone: Brasilia, Distrito Federal, Brazil change
11:00 - 12:30 | Testing and Analysis 17Demonstrations / Journal-first Papers / New Ideas and Emerging Results (NIER) at Oceania I Chair(s): Rangeet Pan IBM Research | ||
11:00 15mTalk | PySTAAR: An End-to-End, Extensible Framework for Automated Python Type Error Repair Demonstrations Wonseok Oh Korea University, Hyobin Park Kyungpook National University, Miryeong Kang Korea University, Seungbin Choi Kyungpook National University, Yunja Choi Kyungpook National University, Hakjoo Oh Korea University | ||
11:15 15mTalk | FlakeSync: A Tool for Automatically Repairing Async Flaky Tests Demonstrations Nandita Jayanthi The University of Texas at Austin, Shanto Rahman The University of Texas at Austin, August Shi The University of Texas at Austin | ||
11:30 15mTalk | The Sustainability Face of Automated Program Repair Tools Journal-first Papers Matias Martinez Universitat Politècnica de Catalunya (UPC), Silverio Martínez-Fernández UPC-BarcelonaTech, Xavier Franch Universitat Politècnica de Catalunya | ||
11:45 15mTalk | Towards Understanding the Challenges of Bug Localization in Deep Learning Systems Journal-first Papers Sigma Jahan Dalhousie University, Mehil Shah Dalhousie University, Masud Rahman Dalhousie University Pre-print File Attached | ||
12:00 15mTalk | Hypothesize-Then-Verify: Speculative Root Cause Analysis for Microservices with Pathwise Parallelism New Ideas and Emerging Results (NIER) Lingzhe Zhang Peking University, China, Tong Jia Institute for Artificial Intelligence, Peking University, Beijing, China, Yunpeng Zhai Alibaba Group, Leyi Pan Tsinghua University, Chiming Duan Peking University, Minghua He Peking University, Pei Xiao Peking University, Ying Li School of Software and Microelectronics, Peking University, Beijing, China | ||
12:15 15mTalk | Abductive Reasoning for Neurosymbolic Fault Localization New Ideas and Emerging Results (NIER) Minh Tam Le University of Sydney, Australia, Xi Zheng Macquarie University, Hong Jin Kang University of Sydney | ||