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A Generalize Hardware debugging Approach for Large Language Models Semi-Synthetic, Datasets

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2025年第2期72卷 623-636页

作者： Fu, Weimin Li, Shijie Zhao, Yifang Yang, Kaichen Zhang, Xuan Jin, Yier Guo, Xiaolong Kansas State Univ Mike Wiegers Dept Elect & Comp Engn Manhattan KS 66506 USA Univ Sci & Technol China Sch Cyber Sci & Technol Hefei 230026 Anhui Peoples R China Michigan Technol Univ Dept Elect & Comp Engn Houghton MI 49931 USA Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA

Large Language Models (LLMs) have precipitated emerging trends towards intelligent automation. However, integrating LLMs into the hardware debug domain encounters challenges: the datasets for LLMs for hardware are often plagued by a dual dilemma - scarcity and subpar quality. Traditional hardware debug approaches that rely on experienced labor to generate detailed prompts are not cheaply scalable. Similarly, strategies that depend on existing LLMs and randomly generated prompts fail to achieve sufficient reliability. We propose a directed, semi-synthetic data synthetic method that leverages version control information and journalistic event descriptions. To produce high-quality data, this approach utilizes version control data from hardware projects combined with the 5W1H (Who, What, When, Where, Why, How) journalistic principles. It facilitates the linear scaling of dataset volumes without depending on skilled labor. We have implemented this method on a collected dataset of open-source hardware designs and fine-tuned fifteen general-purpose LLMs to enable their capability in hardware debugging tasks, thereby validating the efficacy of our approach.

关键词： Hardware Codes Training Software Large language models Chatbots debugging Synthetic data Open source hardware Computer bugs Large language model artificial intelligence hardware debug version control electronic design automation

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Measurement of Anti-debugging Techniques on the Windows and Linux Operating Systems for the Intel x86_64 Architecture

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IEEE ACCESS 2025年 13卷 46568-46583页

作者： Norby, Austin Rimal, Bhaskar P. Brizendine, Bramwell Bogart Associates Northern Virginia Reston VA 20190 USA Univ Idaho Dept Comp Sci Moscow ID 83844 USA Univ Alabama Dept Comp Sci Huntsville AL 35899 USA

Malware authors and software protection frameworks often use anti-debugging techniques to hinder understanding of the underlying code. Companies use anti-debugging techniques to prevent intellectual property, including music, movies, and games, from being stolen or abused by malicious actors. In addition, the encryption of program data or private data can also be classified as an anti-debugging technique because it requires additional effort to reverse engineer or debug it. Malware authors also use these techniques to prevent their software from being analyzed, detected, or blocked. While anti-debugging techniques are not novel, there is minimal research on their performance. This paper conducted novel research on commonly used anti-debugging techniques by measuring their performance on both the Windows and Linux operating system while also creating performance data about the most common anti-debugging techniques, including implementations and statistical measures for six categories of anti-debugging techniques. The statistical results describe a low overhead for the API tests, timing tests, and debug register tests. As expected, the memory encryption test had the highest overhead. Lastly, the paper discusses these results and their statistics per technique and includes code samples for future research.

关键词： Codes Malware Linux debugging Kernel Virtual machine monitors Encryption Timing Registers Data visualization Anti-debugging code obfuscation debugger malware analysis memory encryption OpenSSL

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Simplifying and Isolating Failure-Inducing Input: A Retrospective on Delta debugging

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2025年第3期51卷 820-824页

作者： Zeller, Andreas Hildebrandt, Ralf CISPA Helmholtz Ctr Informat Secur D-66133 Saarbrucken Germany Charite D-10117 Berlin Germany

Delta debugging is a technique to simplify and isolate failure-inducing changes. Its most popular application is on program inputs, where it reduces a failure-inducing input to a minimal input that still triggers the failure. This paper provides a retrospective on Delta debugging, discussing its origins, applications, and impact. We also discuss the limitations of Delta debugging and suggest directions for future research.

关键词： debugging Codes Python Software Servers History Computer bugs Software algorithms Search problems Manuals Delta debugging debugging software testing fault localization failure-inducing inputs

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"debugging: From Art to Science" A Case Study on a debugging Course and Its Impact on Student Performance and Confidence 2025

"Debugging: From Art to Science" A Case Study on a Debugging...

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56th Technical Symposium on Computer Science Education

作者： Wilkin, G. Aaron Rose Hulman Inst Technol Terre Haute IN 47803 USA

ISBN: (纸本)9798400705328

This experience report examines a new course, "debugging: From Art to Science," and its impact on students' debugging approach, skills, confidence, and overall attitudes towards debugging. The course is designed to transform perceptions and approaches to debugging from a daunting task into a systematic and methodical approach, implementing the scientific method. The course introduced students to debugging techniques, tools, and best practices, and utilized exercises from several different programming languages, allowing students to apply debugging techniques to a wide range of defects. This multi-language approach ensured that students could generalize their debugging skills. Quantitative data collected from two smaller assignments with similar bugs, before and after the course, showed a notable improvement in students' debugging performance, with average error resolution times decreasing by an average of 60%. At the end of the course, 80% of the project teams working on a bug report in a non-trivial, open-source project found and fixed the code defect using the methods from the course. Qualitative data from surveys and interviews revealed that students felt more confident and positive about their debugging abilities, with 89% of participants expressing a heightened sense of competence and reduced anxiety when facing debugging tasks. This report highlights the course structure, key materials covered, and the pedagogical approaches that contributed to these outcomes. The findings suggest that a well-structured debugging course can enhance students' practical skills and alter their mindset, fostering a more confident, positive, and proactive approach to debugging in their future careers.

关键词： debugging debugging course case study debugging approach student confidence student performance debugging skills

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BugSpotter: Automated Generation of Code debugging Exercises 2025

BugSpotter: Automated Generation of Code Debugging Exercises

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56th Technical Symposium on Computer Science Education

作者： Padurean, Victor-Alexandru Denny, Paul Singla, Adish MPI SWS Saarbrucken Germany Univ Auckland Auckland New Zealand

ISBN: (纸本)9798400705311

debugging is an essential skill when learning to program, yet its instruction and emphasis often vary widely across introductory courses. In the era of code-generating large language models (LLMs), the ability for students to reason about code and identify errors is increasingly important. However, students frequently resort to trial-and-error methods to resolve bugs without fully understanding the underlying issues. Developing the ability to identify and hypothesize the cause of bugs is crucial but can be time-consuming to teach effectively through traditional means. This paper introduces BugSpotter, an innovative tool that leverages an LLM to generate buggy code from a problem description and verify the synthesized bugs via a test suite. Students interact with BugSpotter by designing failing test cases, where the buggy code's output differs from the expected result as defined by the problem specification. This not only provides opportunities for students to enhance their debugging skills, but also to practice reading and understanding problem specifications. We deployed BugSpotter in a large classroom setting and compared the debugging exercises it generated to exercises hand-crafted by an instructor for the same problems. We found that the LLM-generated exercises produced by BugSpotter varied in difficulty and were well-matched to the problem specifications. Importantly, the LLM-generated exercises were comparable to those manually created by instructors with respect to student performance, suggesting that BugSpotter could be an effective and efficient aid for learning debugging.

关键词： debugging programming education exercise generation generative AI LLMs BugSpotter test cases

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Eye-movement indices of reading while debugging Python source code

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JOURNAL OF COGNITIVE PSYCHOLOGY 2025年第2期37卷 89-107页

作者： Dempsey, Jack Tsiola, Anna Bosch, Nigel Christianson, Kiel Stites, Mallory Univ Illinois Dept Educ Psychol Champaign IL USA Univ Illinois Dept Linguist Champaign IL USA Univ Illinois Sch Informat Sci Champaign IL USA Univ Illinois Beckman Inst Adv Sci & Technol Urbana IL USA Sandia Natl Labs Albuquerque NM USA

Unlike text reading, the eye-movement behaviours associated with reading Python, a computer programming language, are largely understudied through a psycholinguistic lens. A general understanding of the eye movements involved in reading while troubleshooting Python, and how these behaviours compare to proofreading text, is critical for developing educational interventions and interactive tools for helping programmers debug their code. These data may also highlight to what extent humans use their underlying text reading ability when reading source code. The current work provides a profile of global reading behaviours associated with reading Python source code for debugging purposes. To this end, we recorded experienced programmers' eye movements while they determined whether 21 different Python functions would produce the desired output, an incorrect output, or an error message. Some reading behaviours seem to mirror those found in text reading (e.g. effects of stimulus complexity), while others may be specific to reading code. Results suggest that semantic errors that produce undesired outputs in programming source code may influence early stages of processing, likely due to the largely top-down strategy employed by experienced programmers when reading source code. The findings are framed to invigorate discussion and further exploration into psycholinguistic analysis of human source code reading.

关键词： Eye-tracking python reading programming languages debugging

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Mutation Testing via Iterative Large Language Model-Driven Scientific debugging

Mutation Testing via Iterative Large Language Model-Driven S...

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IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW

作者： Philipp Straubinger Marvin Kreis Stephan Lukasczyk Gordon Fraser University of Passau Passau Germany JetBrains Research Munich Germany

ISBN: (数字)9798331534677

ISBN: (纸本)9798331534684

Large Language Models (LLMs) can generate plausible test code. Intuitively they generate this by imitating tests seen in their training data, rather than reasoning about execution semantics. However, such reasoning is important when applying mutation testing, where individual tests need to demonstrate differences in program behavior between a program and specific artificial defects (mutants). In this paper, we evaluate whether Scientific debugging, which has been shown to help LLMs when debugging, can also help them to generate tests for mutants. In the resulting approach, LLMs form hypotheses about how to kill specific mutants, and then iteratively generate and refine tests until they succeed, all with detailed explanations for each step. We compare this method to three baselines: (1) directly asking the LLM to generate tests, (2) repeatedly querying the LLM when tests fail, and (3) search-based test generation with Pynguin. Our experiments evaluate these methods based on several factors, including mutation score, code coverage, success rate, and the ability to identify equivalent mutants. The results demonstrate that LLMs, although requiring higher computational cost, consistently outperform Pynguin in generating tests with better fault detection and coverage. Importantly, we observe that the iterative refinement of test cases is important for achieving high-quality test suites.

关键词： Codes Costs Large language models Fault detection Computational modeling debugging Software Cognition Test pattern generators Iterative methods

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ILDBug: A New Approach to Teaching debugging 2025

ILDBug: A New Approach to Teaching Debugging

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Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 2

作者： Liia Butler Charlotte Kiesel Dipayan Mukherjee Mohammed Hassan Mattox Beckman Geoffrey Herman Siebel School of Computing and Data Science University of Illinois at Urbana-Champaign Urbana IL USA Siebel School of Computing and Data Science University of Illinois Urbana-Champaign Urbana IL USA

ISBN: (纸本)9798400705328

ILDBug is a novel debugging approach inspired by the pedagogical technique Interactive Lecture Demonstrations (ILDs). During ILDs, students predict a demonstration's result, experience the demonstration, and then reflect on their experience. We adapted this process to teach debugging (ILDBug) by having students engage in detecting the bug for prediction, then locating and correcting the bug for experience, and then reflecting on the debugging process. The ILDBug approach is designed to be a lightweight technique to create a debugging exercise that is adaptable to many contexts. This demo will cover the high-level pieces the audience needs to create their own ILDBug using our approach, an example ILDBug in an introductory programming context so they can see it in action, and finally tips on how to adapt our technique to fit their own classroom context.

关键词： debugging

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FPGA Implementation of a JPEG Encoder for Efficient Web debugging of an Unmanned Mobile Vehicle

FPGA Implementation of a JPEG Encoder for Efficient Web Debu...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Kengo Yanagihara Kenyu Okino Shuto Abe Yuta Hashiguchi Takumi Obayashi Kim Chaeseung Tatsunosuke Shiota Yukito Taguchi Ryuki Tsuruda Kyosuke Oshima Syouta Kaga Ren Nakao Sakuya Yamaguchi Masahiro Nishimura Taito Manabe Yuichiro Shibata Graduate School of Engineering Nagasaki University Japan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

We are developing an SoC FPGA-based unmanned mobile vehicle for an FPGA design contest. A web server is running on the vehicle, and the input video from the camera and the white line extraction result video can be checked on the client PC. We have implemented a JPEG encoder on an FPGA to improve the processing performance and debugging efficiency of the operation control. The automated driving system was mounted on AMD's Zynq UltraScale+ MPSoC and the performance of the software and hardware implementations of the JPEG encoder was compared, showing the effectiveness of the hardware implementation.

关键词： System performance Image processing Transform coding Process control debugging Hardware Software Web servers Field programmable gate arrays Consumer electronics

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Design and Implementation of debugging Tool for Power Terminal Equipment Based on Bluetooth Technology

Design and Implementation of Debugging Tool for Power Termin...

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Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Naichong Fan Xiang Cui Xiaoyi Yang School of Software Beihang University Beijing China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

This article explores in depth the design and implementation method of a Bluetooth based power terminal device debugging tool, aiming to significantly improve the convenience and safety of power terminal devices during installation and debugging. In modern power systems, the importance of power terminal equipment as a key component for data monitoring is self-evident. However, due to the complex and variable installation environment of power terminal equipment, as well as the high safety risks, it has brought great challenges to the debugging work. Therefore, this article proposes an innovative solution based on Bluetooth technology, combined with the State Grid 698 protocol as a communication bridge, to build a debugging platform through mobile devices such as smartphones and tablets, realizing remote debugging and on-site maintenance of power terminal equipment. This solution simplifies the debugging process, reduces the operational difficulty of on-site personnel, and significantly improves the personal safety of on-site installation and operation personnel. This plan provides a new solution for the debugging and operation of the power system, which is of great significance for promoting the intelligent and secure development of the power industry.

关键词： Bluetooth Protocols Design methodology Packet loss debugging User interfaces Power system stability Safety Personnel Smart phones

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