Towards Efficient Build Ordering for Incremental Builds with Multiple Configurations
Software products have many configurations to meet different environments and diverse needs. Building software with multiple software configurations typically incurs high costs in terms of build time and computing resources. Incremental builds could reuse intermediate artifacts if configuration settings affect only a portion of the build artifacts. The efficiency gains depend on the strategic ordering of the incremental builds as the order influences which build artifacts can be reused. Deriving an efficient order is challenging and an open problem, since it is infeasible to reliably determine the degree of re-use and time savings before an actual build. In this paper, we propose an approach, called BUDDI—BUild Declaration DIstance, for C-based and Make-based projects to derive an efficient order for incremental builds from the static information provided by the build scripts (i.e., Makefile). The core strategy of BUDDI is to measure the distance between the build declarations of configurations and predict the build size of a configuration from the build targets and build commands in each configuration. Since some artifacts could be reused in the subsequent builds if there is a close distance between the build scripts for different configurations. We implemented BUDDI as an automated tool called BuddiPlanner and evaluated it on 20 popular open-source projects, by comparing it to a baseline that randomly selects a build order. The experimental results show that the order created by BuddiPlanner outperforms 96.5% (193/200) of the random build orders in terms of build time and reduces the build time by an average of 305.94s (26%) compared to the random build orders, with a median saving of 64.88s (28%). BuddiPlanner demonstrates its potential to relieve practitioners of excessive build times and computational resource burdens caused by building multiple software configurations.
Wed 17 JulDisplayed time zone: Brasilia, Distrito Federal, Brazil change
11:00 - 12:30 | Software Maintenance and Comprehension 1Research Papers / Ideas, Visions and Reflections / Demonstrations at Acerola Chair(s): Wesley Assunção North Carolina State University | ||
11:00 18mTalk | Enhancing Function Name Prediction using Votes-Based Name Tokenization and Multi-Task Learning Research Papers Xiaoling Zhang Institute of Information Engineering, Chinese Academy of Sciences, School of Cyber Security, University of Chinese Academy of Sciences,, Zhengzi Xu Nanyang Technological University, shouguo yang Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China, Zhi Li Institute of Information Engineering, Chinese Academy of Sciences, China, zhiqiang shi Institute of Information Engineering, Chinese Academy of Sciences, School of Cyber Security, University of Chinese Academy of Sciences,, Limin Sun Institute of Information Engineering, Chinese Academy of Sciences, School of Cyber Security, University of Chinese Academy of Sciences, DOI Pre-print | ||
11:18 18mTalk | Only diff is Not Enough: Generating Commit Messages Leveraging Reasoning and Action of Large Language Model Research Papers Jiawei Li University of California, Irvine, David Faragó Innoopract GmbH & QPR Technologies, Christian Petrov Innoopract GmbH, Iftekhar Ahmed University of California, Irvine | ||
11:36 18mTalk | Towards Efficient Build Ordering for Incremental Builds with Multiple Configurations Research Papers Jun Lyu Nanjing University, Shanshan Li Software Institute, Nanjing University, He Zhang Nanjing University, Lanxin Yang Nanjing University, Bohan Liu Nanjing University, Manuel Rigger National University of Singapore | ||
11:54 18mTalk | Unprecedented Code Change Automation: The Fusion of LLMs and Transformation by Example Research Papers Malinda Dilhara University of Colorado Boulder, Abhiram Bellur University of Colorado Boulder, Timofey Bryksin JetBrains Research, Danny Dig University of Colorado Boulder, JetBrains Research Pre-print | ||
12:12 9mTalk | Variability-Aware Differencing with DiffDetectiveBest Demo Paper Demonstrations Paul Maximilian Bittner Paderborn University, Alexander Schultheiß Paderborn University, Benjamin Moosherr University of Ulm, Timo Kehrer University of Bern, Thomas Thüm Paderborn University Pre-print Media Attached | ||
12:21 9mTalk | From Models to Practice: Enhancing OSS Project Sustainability with Evidence-Based Advice Ideas, Visions and Reflections Nafiz Imtiaz Khan Department of Computer Science, University of California, Davis, Vladimir Filkov University of California at Davis, USA | ||