As software demand proliferates and software size and complexity increase, traditional software development models face enormous challenges. As a result, new software development techniques are being explored to meet ...
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the objective of knowledge graph completion (KGC) is to enhance our understanding of known facts and infer missing relationships within the graph. Previous text-based methods have advanced the field by incorporating e...
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Context: Recent years have witnessed a noteworthy surge in the emphasis on research and practice in Empirical softwareengineering (ESE). However, teaching this discipline through traditional pedagogical methods prese...
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ISBN:
(纸本)9798400704987
Context: Recent years have witnessed a noteworthy surge in the emphasis on research and practice in Empirical softwareengineering (ESE). However, teaching this discipline through traditional pedagogical methods presents a challenge. Students typically acquire theories and concepts through lectures or expository classes but have limited opportunities to apply this knowledge. Goal: this report aims to share our experiences withthe instructional process, using the Active Learning approach within the context of ESE education. Method: We describe an ESE course that was taught using active methodology principles. At the end of the course, we conducted a personal opinion survey to gather students' feedback. Results: the findings indicated that Active Learning principles can offer several advantages in ESE education. these include improved comprehension of course material, better retention of knowledge gained during classes, and enhanced preparation for involvement in scientific research. Conclusion: this experience provides insights into incorporating active learning principles into an ESE course. We also discuss lessons learned and suggest areas for improvement in future ESE courses.
the importance of teaching software ethics to softwareengineering (SE) students is more critical now than ever before as software-related ethical issues continue to impact society at an alarming rate. Traditional cla...
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ISBN:
(纸本)9798400704987
the importance of teaching software ethics to softwareengineering (SE) students is more critical now than ever before as software-related ethical issues continue to impact society at an alarming rate. Traditional classroom methods, vignettes, role-play games, and quizzes have been employed over the years to teach SE students about software ethics. Recognising the significance of incorporating software ethics knowledge in SE education and the continued need for more efforts in the area of the teaching and learning of SE ethics, we developed an interactive, scenario-based software Ethics Quiz. Our goal was to teach SE students about ethics in a comprehensive, open, and engaging manner through a combined approach of an online lecture followed by an interactive workshop withthe quiz and a debriefing session. the anonymous quiz responses collected showed promising results regarding the engagement and efficacy of the lecture and quiz, with a slightly better rating for the interactive quiz. the voluntary student feedback collected suggested that a majority of the participants found the debrief discussion on the quiz scenarios to be very beneficial for learning about software ethics. In this experience report, we share our experiences, related educational resources including the quiz, and recommendations from lessons learned withthe wider education community to keep driving this critical topic forward.
In this paper, we propose an Embedding and Mapping Approach with Domain-Independent Latent (EMCDR-DiL) for cross-domain recommender. the proposed EMCDR-DiL framework is improved compared to EMCDR by using matrix tripl...
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Curricula recommendation for undergraduate softwareengineering courses underscore the importance of transcending from traditional lecture format to actively involving students in time-limited, iterative development p...
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ISBN:
(纸本)9798400704987
Curricula recommendation for undergraduate softwareengineering courses underscore the importance of transcending from traditional lecture format to actively involving students in time-limited, iterative development practices. this paper presents a teaching approach for a software testing course that integrates theory and practical experience through the utilization of both TBL and active contributions to OSS projects. the paper reports on our experience implementing the pedagogical approach over four consecutive semesters of a software Testing course within an undergraduate softwareengineering program. the experience encompassed both online and in-person classes, involving a substantial cohort of over 300 students spanning four semesters. Students' perceptions regarding the course are analyzed and compared with previous, related studies. Our results are positively aligned withthe existing literature of softwareengineering teaching, confirming the effectiveness of combining TBL with OSS contributions. Additionally, our survey has shed light on the challenges that students encounter during their first contribution to OSS projects, highlighting the need for targeted solutions. Overall, the experience demonstrates that the proposed pedagogical structure can effectively facilitate the transition from theoretical knowledge to real-world practice in the domain of software Testing.
the proceedings contain 66 papers. the topics discussed include: unsupervised and supervised co-learning for comment-based codebase refining and its application in code search;what do we know about hugging face? a sys...
ISBN:
(纸本)9798400710476
the proceedings contain 66 papers. the topics discussed include: unsupervised and supervised co-learning for comment-based codebase refining and its application in code search;what do we know about hugging face? a systematic literature review and quantitative validation of qualitative claims;ChatGPT application in systematic literature reviews in softwareengineering: an evaluation of its accuracy to support the selection activity;sustaining maintenance labor for healthy open source software projects through human infrastructure: a maintainer perspective;enhancing change impact prediction by integrating evolutionary coupling withsoftware change relationships;empirical evaluation of frequency based statistical models for estimating killable mutants;and optimizing the utilization of large language models via schedule optimization: an exploratory study.
Graph neural networks (GNNs) are powerful models for learning graph-structured data. In most graph neural networks, only the first-order neighbouring nodes, also known as positive samples, are utilized for message pas...
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the performance of repository-level code completion depends upon the effective leverage of both general and repository-specific knowledge. Despite the impressive capability of code LLMs in general code completion task...
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ISBN:
(数字)9798400712487
ISBN:
(纸本)9798400712487
the performance of repository-level code completion depends upon the effective leverage of both general and repository-specific knowledge. Despite the impressive capability of code LLMs in general code completion tasks, they often exhibit less satisfactory performance on repository-level completion due to the lack of repository-specific knowledge in these LLMs. To address this problem, we propose GraphCoder, a retrieval-augmented code completion framework that leverages LLMs' general code knowledge and the repository-specific knowledge via a graph-based retrieval-generation process. In particular, GraphCoder captures the context of completion target more accurately through code context graph (CCG) that consists of control-flow, data- and control-dependence between code statements, a more structured way to capture the completion target context than the sequence-based context used in existing retrieval-augmented approaches;based on CCG, GraphCoder further employs a coarse-to-fine retrieval process to locate context-similar code snippets withthe completion target from the current repository. Experimental results demonstrate boththe effectiveness and efficiency of GraphCoder: Compared to baseline retrieval-augmented methods, GraphCoder achieves higher exact match (EM) on average, with increases of +6.06 in code match and +6.23 in identifier match, while using less time and space.
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