Understanding Developers' Discussions and Perceptions on Non-Functional Requirements: The Case of the Spring Ecosystem
Non-Functional Requirements (NFR) should be defined in the early stages of the software development process, driving developers to make important design decisions. Neglecting NFRs may lead developers to create systems that are difficult to maintain and do not meet user expectations. Despite its importance, the discussion of NFRs is often ad-hoc and scattered through multiple sources, limiting developers’ awareness of NFRs. In that scenario, Pull Request (PR) discussions can be used, thus providing a centralized platform for comprehensive NFR discussions. However, existing studies do not explore this important source of information in open-source software development, which developers widely use to discuss software requirements. In this study, we report an investigation of NFR discussions available in PR of repositories of the Spring ecosystem. We collected, manually curated, and analyzed PR discussions addressing four categories of NFR: maintainability, security, performance, and robustness. We found that more than 77% of the discussions related to NFRs are triggered in the PR title and/or description, indicating that developers are often provided with sufficient information straightway. We observed that discussions surrounding these PRs tend to address the introduction of a code change or explain some anomaly regarding a particular NFR. To gain more knowledge of NFR discussions, we investigated developers involved in discussions and fixing NFR issues. For that, we performed an in-depth analysis of \devsAnalyzed developers that stood out in collaborating with the mapped PRs. We discovered that the developers who discuss NFRs often open and review most PRs related to NFRs. To complement this analysis, we applied a survey with \devsSurvey to gather their perceptions on NFR discussions. By observing how developers approach NFRs and participate in discussions, we documented the best practices and strategies newcomers can use to address NFRs effectively. Through the characterization of NFR discussions, we aim to pave the way for developing automated tools to identify NFRs better. Finally, we provide a curated dataset of 1,533 PR discussions classified with NFR presence.
Thu 18 JulDisplayed time zone: Brasilia, Distrito Federal, Brazil change
10:30 - 11:00 | |||
10:30 30mPoster | DyPyBench: A Benchmark of Executable Python Software Posters Islem BOUZENIA University of Stuttgart, Bajaj Piyush Krishan University of Stuttgart, Michael Pradel University of Stuttgart | ||
10:30 30mPoster | Shadows in the Interface: A Comprehensive Study on Dark Patterns Posters Liming Nie Nanyang Technological University, Yangyang Zhao Zhejiang Sci-Tech University, Chenglin Li Zhejiang Sci-Tech University, Xuqiong Luo Changsha University of Science and Technology, Yang Liu Nanyang Technological University | ||
10:30 30mPoster | Do Large Language Models Recognize Python Identifier Swaps in their Generated Code? Posters DOI Pre-print Media Attached File Attached | ||
10:30 30mPoster | Understanding Developers' Discussions and Perceptions on Non-Functional Requirements: The Case of the Spring Ecosystem Posters Anderson Oliveira Pontifical Catholic University of Rio de Janeiro (PUC-Rio), João Lucas Correia Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Wesley Assunção North Carolina State University, Juliana Alves Pereira Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rafael de Mello Federal University of Rio de Janeiro (UFRJ), Daniel Coutinho Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Caio Barbosa Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Paulo Vítor C. F. Libório Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Alessandro Garcia Pontifical Catholic University of Rio de Janeiro (PUC-Rio) | ||
10:30 30mPoster | ProveNFix: Temporal Property guided Program Repair Posters Yahui Song National University of Singapore, Xiang Gao Beihang University, Wenhua Li National University of Singapore, Wei-Ngan Chin National University of Singapore, Abhik Roychoudhury National University of Singapore | ||
10:30 30mPoster | PBE-based Selective Abstraction and Refinement for Efficient Property Falsification of Embedded Software Posters | ||
10:30 30mPoster | A Transferability Study of Interpolation-Based Hardware Model Checking to Software Verification Posters DOI Media Attached | ||
10:30 30mPoster | Evaluating and Improving ChatGPT for Unit Test Generation Posters Zhiqiang Yuan Fudan University, Mingwei Liu Fudan University, Shiji Ding Fudan University, Kaixin Wang Fudan University, Yixuan Chen Yale University, Xin Peng Fudan University, Yiling Lou Fudan University | ||
10:30 30mPoster | Testing AI Systems Leveraging Graph Perturbation Posters Zhaorui Yang University of California, Riverside, Haichao Zhu Tencent America, Qian Zhang University of California, Riverside | ||
10:30 30mPoster | Predictive Program Slicing via Execution Knowledge-Guided Dynamic Dependence Learning Posters Aashish Yadavally University of Texas at Dallas, Yi Li University of Texas at Dallas, Tien N. Nguyen University of Texas at Dallas | ||
10:30 30mPoster | Unprecedented Code Change Automation: The Fusion of LLMs and Transformation by Example Posters Malinda Dilhara University of Colorado Boulder, Abhiram Bellur University of Colorado Boulder, Timofey Bryksin JetBrains Research, Danny Dig University of Colorado Boulder, JetBrains Research | ||
10:30 30mPoster | A Deep Dive into Large Language Models for Bug Fixing Posters Soneya Binta Hossain University of Virginia, Nan Jiang Purdue University, Qiang Zhou Amazon Web Services, Xiaopeng LI Amazon Web Services, Wen-Hao Chiang Amazon Web Services, Yingjun Lyu Amazon Web Services, Hoan Nguyen Amazon Web Services, Omer Tripp Amazon Web Services | ||
10:30 30mPoster | A Quantitative and Qualitative Evaluation of LLM-based Explainable Fault Localization Posters Sungmin Kang Korea Advanced Institute of Science and Technology, Gabin An Korea Advanced Institute of Science and Technology, Shin Yoo Korea Advanced Institute of Science and Technology | ||
10:30 30mPoster | IRCoCo: Immediate Rewards-Guided Deep Reinforcement Learning for Code Completion Posters Bolun Li Shandong Normal University, Zhihong Sun Shandong Normal University, Tao Huang Shandong Normal University, Hongyu Zhang Chongqing University, Yao Wan Huazhong University of Science and Technology, Chen Lyu Shandong Normal University, Ge Li Peking University, Zhi Jin Peking University | ||
This room is conjoined with the Foyer to provide additional space for the coffee break, and hold poster presentations throughout the event.