SEIP - Software Engineering in PracticeAPSEC 2024
The purpose of SEIP (Software Engineering in Practice) track offers a unique opportunity for practitioners from industry and academia to share their valuable experiences, insights, pragmatic research issues and the best practices in the software engineering community. As part of the APSEC2024 conference, the SEIP Track aims to foster collaboration and mutual learning between these two vital sectors. We welcome submissions from industrial practitioners and academic researchers that align with the general topics outlined in the technical research track, as well as emerging technical topics such as AI, autonomous, safety, SoS (System of systems).
SEIP Invited Talks
1. Yinan Wang (Huawei)
Title: Evaluation Methods and Practices for Large Code Models
Abstract: Large code models are the core "brains" of AI developer tools like GitHub Copilot and Cursor. The strength of a model's coding capabilities directly relates to the product's ability and market competitiveness. Nowadays, there are more and more types of large code models being open sourced and trained within enterprises, with increasingly powerful capabilities, how to select a suitable and excellent model for AI developer tools and continuously iterate the model to enhance product capabilities has become one of the key issues that need to be addressed in intelligent code products. How to comprehensively, accurately, and quickly evaluate the code capabilities of each model, and through evaluation feedback, promote the next round of model iteration? This is a problem that various intelligent code product teams are exploring and practicing.
Bio: Tencent Technical Product Expert, Head of Intelligent Software Engineering Data and Evaluation Team. Formerly the Product Lead of Baidu's Engineering Efficiency Department and Product Director of OSChina. Bachelor's and Master's degree in Software Engineering from Beihang University. Committed to enhancing organizational research and development efficiency by designing software development efficiency tools and promoting the implementation of software engineering practices. He was the main author of company’s software engineering guidelines and led the planning, design, and system development of multiple enterprise-level R&D efficiency platforms.
2. Chao Peng (ByteDance)
Title: MarsCode Agent: Automated Program Repair based on Large Language Models
Abstract: In recent years, advancements in large language models (LLMs) have shown great potential in automating various software development tasks, including code completion, test generation, and bug fixing. However, due to the complexity and diversity of real-world software systems, the application of LLMs in automated bug fixing still faces many challenges. To address these issues, we propose MarsCode Agent, a new framework that leverages LLMs to automatically identify and fix errors in software code. MarsCode Agent combines the powerful capabilities of LLMs with advanced code analysis techniques to accurately locate faults and generate patches. Our approach follows a systematic process, including planning, bug reproduction, fault localization, candidate patch generation, and validation, to ensure high-quality bug fixes. Evaluations on SWE-bench and deployments in real-world enterprise code repositories demonstrate that MarsCode Agent achieves a high success rate in bug fixing compared to most existing automated methods.
Bio: Dr. Chao Peng is a Senior Researcher at ByteDance. He received his PhD degree from the University of Edinburgh under supervision of Prof. Ajitha Rajan. At ByteDance, he is in the Software Engineering Lab, MarsCode IDE Team. His research interest lies in the area of software testing, program repair and optimisations, and the synergy with machine learning and compiler techniques. He is also responsible for academic development and university collaboration. He has published research and industry papers on conferences such as ICSE, FSE, ASE and ICSME and serve as the PC member of FSE.
3. Xing Hu (Zhejiang University)
Title: LLM for Code: Generation, Testing, and Evaluation
Abstract: Recently, Large Language Models (LLMs) such as ChatGPT has attracted great attention from both academia and industry. They have shown substantial gains in solving a variety of problems ranging from Q&A to text summarization. Existing studies also found that some LLMs can be applied to the source code, such as code generation or debugging. However, their performance on various software engineering tasks has not been systematically investigated, and the understanding of LLMs is arguably fairly limited. Also, it is unclear how we can build software engineering capability based on LLM. In this talk, I will discuss the performance of LLMs on software development and maintenance, including code generation and test generation. I will also present some software engineering applications based on LLM (e.g., vulnerability management, code search, and code idioms mining).
Bio: Xing Hu is an associate professor at school of software technology, Zhejiang University (ZJU). She got her Ph.D degree in July 2020 from School of Electronics Engineering and Computer Science (EECS), Peking University, China. Her research interests are intelligent software engineering (e.g., intelligent code generation and test case generation) and mining software repositories. In recent years, she has published more than 50 papers in TSE, TOSEM, ICSE, FSE, ASE and other conferences and journals. She is the associate editors of TOSEM and JSEP. She has also served as a program committee member for many top conferences such as FSE, ISSTA, and ASE.
4. Zhifeng Li (Huazhi Future)
Title: Artificial Intelligence Catalyzes a New Paradigm for Industrial Development
Abstract: The rapid development of artificial intelligence is driving a significant transformation in industrial IT development models. The application of artificial intelligence spans many fields, including industry, agriculture, healthcare, and culture. It not only serves as a tool but also represents a transformation in production methods, leading to profound changes in social production relations. This talk will discuss the impact and facilitative role of artificial intelligence on typical industries, as well as the changes and risks it brings to human society.
Bio: Dr Li is a chairman of Huazhi Future (Chongqing) Technology Co., Ltd. He received his Doctor of Physics from the University of Vienna. He mainly engages in research and industrial incubation in the fields of information technology, big data, and artificial intelligence. He published numerous papers in international journals, obtained more than ten national patents including invention patents, and undertook several provincial and national level research projects. He has extensive experience in the industrialization development of high and new technology and has given lectures to various government departments. He is a recipient of the National Outstanding Self-Financed Student Scholarship, and serves as a panel member for many entrepreneurship competitions such as Chongqing Postdoctoral Innovation and Entrepreneurship Competition.
Wed 4 DecDisplayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change
11:00 - 12:20 | |||
11:00 40mIndustry talk | SEIP Invited Talk - Evaluation Methods and Practices for Large Code Models SEIP - Software Engineering in Practice Yinan Wang Huawei | ||
11:40 40mIndustry talk | SEIP Invited Talk - MarsCode Agent: Automated Program Repair based on Large Language Models SEIP - Software Engineering in Practice Chao Peng ByteDance Link to publication |
16:00 - 17:20 | Session (6)EDU - Software Engineering Education / SEIP - Software Engineering in Practice at Room 3 (Xiangquan Ballroom) Chair(s): Lingfeng Bao Zhejiang University | ||
17:00 20mTalk | Unveiling Cognitive Biases in Software Testing: Insights from a Survey and Controlled Experiment SEIP - Software Engineering in Practice Eduard Paul Enoiu Mälardalen University, Alexandru Cusmaru Siemens Mobility GmbH, Jean Malm Malardalen University Pre-print File Attached |
Thu 5 DecDisplayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change
11:00 - 12:20 | |||
11:00 40mTalk | SEIP Invited Talk - LLM for Code: Generation, Testing, and Evaluation SEIP - Software Engineering in Practice Xing Hu Zhejiang University | ||
11:40 40mTalk | SEIP Invited Talk - Artificial Intelligence Catalyzes a New Paradigm for Industrial Development SEIP - Software Engineering in Practice Zhifeng Li Huazhi Future |
14:00 - 15:30 | Session (10)Technical Track / SEIP - Software Engineering in Practice at Room 3 (Xiangquan Ballroom) Chair(s): In-Young Ko Korea Advanced Institute of Science and Technology | ||
15:00 20mTalk | CoSTV: Accelerating Code Search with Two-Stage Paradigm and Vector Retrieval SEIP - Software Engineering in Practice Dewu Zheng Sun yat-sen University, Yanlin Wang Sun Yat-sen University, Wenqing Chen Sun Yat-sen University, Jiachi Chen Sun Yat-sen University, Zibin Zheng Sun Yat-sen University |
Fri 6 DecDisplayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change
11:00 - 12:20 | Session (17)SEIP - Software Engineering in Practice / ERA - Early Research Achievements at Room 1 (Zunhui Room) Chair(s): Meng Yan School of Big Data & Software Engineering, Chongqing University | ||
11:00 20mTalk | Large Language Models Empowered Online Log Anomaly Detection in AIOps SEIP - Software Engineering in Practice | ||
11:20 20mTalk | Leveraging Generative AI for Accelarating Enterprise Application Development: Insights from ChatGPT SEIP - Software Engineering in Practice Asha Rajbhoj TCS Research, Tanay Sant Tata Consultancy Services, Akanksha Somase Tata Consultancy Services, Vinay Kulkarni Tata Consultancy Services Research |
14:00 - 15:20 | Session (18)SEIP - Software Engineering in Practice / ERA - Early Research Achievements at Room 1 (Zunhui Room) Chair(s): Chao Liu Chongqing University | ||
15:00 20mTalk | ENeRgy sustaInability COding (ENRICO): A PRACTICAL USE CASE SEIP - Software Engineering in Practice Benoit Lange Inria File Attached |
Accepted Papers
Call for Papers: Software Engineering in Practice Track
The purpose of SEIP (Software Engineering in Practice) track offers a unique opportunity for practitioners from industry and academia to share their valuable experiences, insights, pragmatic research issues and the best practices in the software engineering community. As part of the APSEC 2024 conference, the SEIP Track aims to foster collaboration and mutual learning between these two vital sectors. We welcome submissions from industrial practitioners and academic researchers that align with the general topics outlined in the technical research track, as well as emerging technical topics such as AI, autonomous, safety, SoS (System of systems).
Topics of Interest
The major topics of SEIP 2024 include the following, but not limited to:
- Verification and validation of machine learning systems
- Software safety engineering in autonomous systems such as autonomous vehicles
- Software safety in functional safety, STPA/STAMP and other safety disciplines
- Software engineering on connected world including SoS
- Generative AI and software engineering
- Emerging methodology in software engineering
- Difficulties, issues, and challenges from SE in practice
- Introducing of new standards in SE
- Best practices in traditional software engineering
Evaluation Criteria
Each submission will be meticulously reviewed by a minimum of three members of the SEIP Program Committee. The evaluation process will consider industry relevance, originality, soundness, empirical and/or practical validation, as well as the quality and coherence of the presentation. Please note that, unlike the technical research track, the SEIP track does NOT necessitate double-anonymous reviews.
Submission Guideline
Submitted papers must have been neither previously accepted for publication nor concurrently submitted for review in another journal, book, conference, or workshop.
All submissions must be in English and must come in A4 paper size PDF format and conform, at the time of submission, to the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt font, LaTeX users must use \documentclass[10pt,conference]{IEEEtran}
without including the compsoc
or compsocconf
option). Also, papers must comply with the IEEE Policy on Authorship. Submissions must be submitted electronically in PDF before the due date via EasyChair.
An SEIP paper must not exceed 10 pages for the main text, including appendices, figures, tables, and references(short papers around 5 pages are also welcomed). The Chairs reserve the right to reject submissions (without reviews) that are not in compliance or out of scope for the conference.
Important Dates
- Submission Deadline:
9 Aug 202416 Aug 2024 - Author Notification: 25 Sep 2024
- Camera Ready Deadline: 20 Oct 2024
Submission Link
Papers must be submitted through EasyChair: https://easychair.org/conferences/?conf=apsec2024
Accepted Papers and Attendance Expectation
All accepted papers will be submitted to the CS Digital Library as the APSEC 2024 conference proceedings. If a submission is accepted, at least one author of the paper is required to register for and attend the conference to present the paper. The presentation is expected to be delivered in person, unless this is impossible due to travel restrictions (related to, e.g., health, visa, etc.). “If an accepted paper is not presented, the paper is removed from the proceedings.
Contacts
For more information, please contact the APSEC SEIP 2024 Co-Chairs:
- Cuiyun Gao, Harbin Institute of Technology, gaocuiyun@hit.edu.cn
- Xin Xia, Huawei, xin.xia@acm.org