Detection of overlapping communities is a challenging problem that has drawn a lot of research interest. this is motivated by the fact that in real-world networks, individuals frequently join multiple groups subsequen...
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Integrating Large Language Models (LLMs) into software fault localization represents a significant advancement in improving debugging efficiency for programmers. However, novice program fault localization, which is es...
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ISBN:
(纸本)9798350365634
Integrating Large Language Models (LLMs) into software fault localization represents a significant advancement in improving debugging efficiency for programmers. However, novice program fault localization, which is essential for computer science education, has not been thoroughly investigated in previous studies. In contrast to industrial programs target practical functionality, novice programs primarily deal with individual algorithmic issues. the distinct logic structures between novice and industrial programs can impact how effectively LLM understand and process them. Moreover, this difference reveals the inapplicability of the Competent Programmer Hypothesis, a fundamental assumption in industrial fault localization, to novice program fault localization. therefore, industrial methodologies are unsuitable for novice programming, emphasizing the need for our empirical studies. To fill this gap, we evaluate LLMs' effectiveness in localizing faults for novice programs in statement level. Using the widely used novice programs dataset Codeflaws and Condefects, we compare the performance of two commercial LLMs (i.e., ChatGPT-3.5 and ChatGPT-4) and three open-source LLMs (i.e., ChatGLM3, Llama2, and Code Llama) against traditional fault localization methods, examining their accuracy and overlap. Additionally, we investigate how prompt engineering improves localization precision. Our findings show ChatGPT-4's overall superior performance, with ChatGPT-3.5 exhibiting minor advantages in certain cases. ChatGPT-4 outperforms the traditional methods with best performance by 592% and 137% on Codeflaws and Condefects. Specifically, each method exhibits unique strengths in localizing novice programming faults. Moreover, carefully crafted prompts can improve LLMs' precision. these insights underscore the promising potential of utilizing LLMs for fault localization in novice programming.
this study intended to develop a new and improved approach to solve completely Fully Fuzzy Linear programming Problems(FFLPP) with Symmetric Trapezoidal Fuzzy Numbers(STFN) and findings results are compared withthe r...
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Creating a program that performs even a simple task and shows the result is unapproachable to most people, and even trained programmers face a burden to create a new program. In this paper, we introduce a prototype sy...
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ISBN:
(纸本)9781450396561
Creating a program that performs even a simple task and shows the result is unapproachable to most people, and even trained programmers face a burden to create a new program. In this paper, we introduce a prototype system and model for live visual dataflow programming where intermediate steps are visible and all components are tangible and manifest. Our system aims to allow a user to dive in and immediately have a working program that can be incrementally extended.
this paper presents a comprehensive survey of the progress made in the field, spanning from its foundational concepts to its application in challenging planning domains. the survey delves into the strengths and weakne...
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the current research on object tracking using visual and language information shows promise. A significant amount of research has been done to achieve this goal by constructing models that uniformly characterize multi...
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In order to improve the processing quality of traditional Chinese medicine rhubarb and control the processing process of rhubarb in real time, a programmable logic control system with Ethernet and Internet of things r...
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Long afterglow luminescence (LAL) phosphors hold potential for diverse applications. However, too many factors make it impossible to obtain a general afterglow mechanism, which hinders the exploration of the novel aft...
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Self-supervised graph learning has attracted intensive attention due to attempts to eliminate the need for expensive data labeling, especially graph contrastive learning. However, the existing graph contrastive learni...
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programming laboratories are very important for students to learn and understand the concepts of programming. In the recent past, the world has become digital owing to the pandemic of Covid-19. this has forced student...
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