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18th International Conference on Augmented Cognition (AC)

作者： Pacol, Caren A. Rodrigo, Maria Mercedes T. Tablatin, Christine Lourrine S. Ateneo Manila Univ Quezon City Metro Manila Philippines Pangasinan State Univ Urdaneta Pangasinan Philippines

ISBN: (纸本)9783031615689;9783031615696

Debugging is an important skill to learn for novice programmers and since compiler error messages are instrumental to the debugging process, investigating how novice programmers read and process these messages has become a subject of interest among computer science education researchers. Prior studies were valuable because they identified differences in the visual attention patterns of high and low performers and of experts and novices. They were, however, subject to certain limitations. In this study, we attempted to bridge these gaps by continuing the study of Rodrigo and Tablatin [18] and Tablatin and Rodrigo [21]. Using the methodology detailed in Rodrigo & Tablatin [18], we investigated how student programmers process literal and non-literal syntax errors embedded in Java and C++ programs. The analysis of eye tracking data collected from participants of two schools revealed a variation in visual effort and attention patterns of high and low performers. We conclude that low performance is not always associated with low visual attention. The novice programmer code comprehension errors may be rooted in other causes such as tracing and debugging strategies that students use, cognitive skills, individual preference of learning and programming experience. These factors are out of scope for this paper but may be the subject of future work.

关键词： Eye-tracking Compiler Error Messages Error Lines syntax errors Visual Attention Visual Effort

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Data Mining of syntax errors in a Large-Scale Online Python Course 23rd

Data Mining of Syntax Errors in a Large-Scale Online Python ...

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23rd International Conference on Artificial Intelligence in Education (AIED)

作者： Lee, Jung A. Koprinska, Irena Jeffries, Bryn Univ Sydney Sch Comp Sci Sydney NSW Australia Univ Sydney Grok Acad Sydney NSW Australia

ISBN: (纸本)9783031116476;9783031116469

This paper investigates the common syntax errors students encounter when programming in Python using data from a large-scale online beginner course. We firstly analyse the error distribution to find differences between passing and failing students and then use clustering and Markov chains to identify clusters of student submissions with similar error pattern and how students move between these clusters during the course and between consecutive tasks. This type of analysis can be used by educators to understand student behaviour related to syntax errors and provide effective teaching support.

关键词： syntax errors Student behaviour Clustering Markov chains

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115Ways Not to Say Hello, World!: syntax errors Observed in a Large-Scale Online CS0 Python Course 22

115Ways Not to Say Hello, World!: Syntax Errors Observed in ...

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27th ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Jeffries, Bryn Lee, Jung A. Koprinska, Irena Grok Acad Sydney NSW Australia Univ Sydney Sch Comp Sci Sydney NSW Australia Univ Sydney Sch Comp Sci Sydney Australia

ISBN: (纸本)9781450392013

Online programming courses can provide detailed automatic feedback for code that fails to meet various test conditions, but novice students often struggle with syntax errors and are unable to write valid testable code. Even for very simple exercises, the range of incorrect code can be surprising to educators with mastery of a programming language. This research paper presents an analysis of the error messages from code run by students in an introductory Python 3 programming course, participated in by 8680 primary and high-school students from 680 institutions. The invalid programs demonstrate a wide diversity of mistakes: even for a one-line "Hello World!" exercise there were 115 unique invalid programs. The most common errors are identified and compared to the topics introduced in the course. The most generic errors in selected exercises are investigated in greater detail to understand the underlying causes. While the majority of students attempting an exercise reach a successful outcome, many students encounter at least one error in their code. Of these, many such errors indicate basic mistakes, such as unquoted string literals, even in exercises late in the course for which some proficiency of earlier concepts is assumed. These observations suggest there is significant scope to provide greater reinforcement of students' understanding of earlier concepts.

关键词： CS0 syntax errors

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syntax and Stack Overflow: A methodology for extracting a corpus of syntax errors and fixes

Syntax and Stack Overflow: A methodology for extracting a co...

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35th IEEE International Conference on Software Maintenance and Evolution (ICSME)

作者： Wong, Alexander William Salimi, Amir Chowdhury, Shaiful Hindle, Abram Univ Alberta Dept Comp Sci Edmonton AB Canada

ISBN: (纸本)9781728130941

One problem when studying how to find and fix syntax errors is how to get natural and representative examples of syntax errors. Most syntax error datasets are not free, open, and public, or they are extracted from novice programmers and do not represent syntax errors that the general population of developers would make. Programmers of all skill levels post questions and answers to Stack Overflow which may contain snippets of source code along with corresponding text and tags. Many snippets do not parse, thus they are ripe for forming a corpus of syntax errors and corrections. Our primary contribution is an approach for extracting natural syntax errors and their corresponding human made fixes to help syntax error research. A Python abstract syntax tree parser is used to determine preliminary errors and corrections on code blocks extracted from the SOTorrent data set. We further analyzed our code by executing the corrections in a Python interpreter. We applied our methodology to produce a public data set of 62,965 Python Stack Overflow code snippets with corresponding tags, errors, and stack traces. We found that errors made by Stack Overflow users do not match errors made by student developers or random mutations, implying there is a serious representativeness risk within the field. Finally we share our dataset openly so that future researchers can re-use and extend our syntax errors and fixes.

关键词： stack overflow natural syntax errors python mining software repositories

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Can ChatGPT Learn to Count Letters?

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COMPUTER 2025年第3期58卷 96-99页

作者： Conde, Javier Martinez, Gonzalo Reviriego, Pedro Gao, Zhen Liu, Shanshan Lombardi, Fabrizio Univ Politecn Madrid ETSI Telecomunicac Madrid 28040 Spain Univ Carlos III Madrid Madrid 28911 Spain Tianjin Univ Tianjin 300072 Peoples R China Univ Elect Sci & Technol China Chengdu 611731 Peoples R China Northeastern Univ Boston MA 02115 USA

Large language models (LLMs) struggle on simple tasks such as counting the number of occurrences of a letter in a word. In this paper, we investigate if ChatGPT can learn to count letters and propose an efficient solu... 详细信息

关键词： Basic Reproduction Number Letter Word syntax errors Strawberry Fine Tuned Model Sequence Of Letters Fine Tuning Process Previous Text Tokenized

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Applying Software Engineering Anti-patterns to Programming Error Messages 2023

Applying Software Engineering Anti-patterns to Programming E...

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54th Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE TS)

作者： Santos, Eddie Antonio Karvelas, Ioannis Becker, Brett A. Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450394338

Programming error messages (PEMs) have long been a hindrance to novice programmers. This work aims to establish a catalog of PEM anti-patterns-common, reoccurring features of PEMs that make them unhelpful or actively harmful to programmers. The goal is for educators to be aware of, and actively teach concrete ways that PEMs can be misleading to students;to encourage language implementers to be cognizant of these;and avoid them when designing error feedback. A pilot study is being conducted to validate the presence of anti-patterns in error messages.

关键词： human factors programming error messages computer science education error messages software engineering computing education hci compiler error messages novice programmers compilers syntax errors anti-patterns cs1

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Investigating Preprocessor-Based syntax errors 13

Investigating Preprocessor-Based Syntax Errors

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12th International Conference on Generative Programming: Concepts and Experiences

作者： Medeiros, Flavio Ribeiro, Marcio Gheyi, Rohit Univ Fed Campina Grande Campina Grande Brazil Univ Fed Alagoas Maceio Brazil

ISBN: (纸本)9781450323734

The C preprocessor is commonly used to implement variability in program families. Despite the widespread usage, some studies indicate that the C preprocessor makes variability implementation difficult and error-prone. However, we still lack studies to investigate preprocessor-based syntax errors and quantify to what extent they occur in practice. In this paper, we define a technique based on a variability-aware parser to find syntax errors in releases and commits of program families. To investigate these errors, we perform an empirical study where we use our technique in 41 program family releases, and more than 51 thousand commits of 8 program families. We find 7 and 20 syntax errors in releases and commits of program families, respectively. They are related not only to incomplete annotations, but also to complete ones. We submit 8 patches to fix errors that developers have not fixed yet, and they accept 75% of them. Our results reveal that the time developers need to fix the errors varies from days to years in family repositories. We detect errors even in releases of well-known and widely used program families, such as Bash, CVS and Vim. We also classify the syntax errors into 6 different categories. This classification may guide developers to avoid them during development.

关键词： Program Families Preprocessors syntax errors

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Assessing Student Learning Across Various Database Query Languages 53

Assessing Student Learning Across Various Database Query Lan...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Li, Zepei Yang, Sophia Cunningham, Kathryn Alawini, Abdussalam University of Illinois Urbana-Champaign Department of Computer Science UrbanaIL United States

ISBN: (纸本)9798350336429

Previous research has shown that students encounter difficulties when learning database systems and their corresponding languages. Researchers have categorized these challenges into syntax and semantic errors and have identified common error types and overall learning obstacles among students. However, most existing studies have primarily focused on quantitatively assessing students' overall performance in an aggregated manner' which may overlook valuable insights into individual-level knowledge transfer. In this study, we scrutinized over 250,000 submissions to query language programming assignments, their corresponding error messages, and the performance data of 702 students who took a database course in the Fall 2022 semester at the University of Illinois Urbana-Champaign to gain a comprehensive overview of each student's performance. We followed each student's progress in semantic and syntax errors across three query languages to determine their overall learning experience and whether knowledge transfer had occurred. Consequently, we discovered that many students may still encounter difficulties when transferring their knowledge from one language to another, despite having already learned and practiced the same abstract data operation concepts in one language. On the other hand, the majority of students were able to reduce syntax errors through practice in one language, but the rate of improvement varied among individuals. This study seeks to investigate two key aspects: the potential transfer of abstract data operation concepts among different database languages, and the possibility of a decrease in syntax errors through consistent practice within a single query language. © 2023 IEEE.

关键词： knowledge transfer MongoDB Neo4j semantic errors Structured Query Language (SQL) syntax errors

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What makes a programming error message good? 22

What makes a programming error message good?

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4th Conference on United Kingdom and Ireland Computing Education Research (UKICER)

作者： Santos, Eddie Antonio Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450397421

Programming error messages (PEMs) often prove to be troublesome for novice programmers. Guidelines to improve PEMs often lack theoretical or empirical justification. This research will establish a theoretical foundation for what makes a "good" PEM, based on existing theories that have not yet been applied to PEMs. These findings will be applied to an existing programming environment and result in empirically-validated advice for language implementers.

关键词： Compilers Compiler Error Messages Computer Science Education Computing Education CS1 Error Messages HCI Human Factors Human Computer Interaction Novice Programmers Programming errors Programming Error Messages Programming Languages Software Engineering syntax errors

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Large-Scale Analysis of Error Frequencies in Logo Programming 2022

Large-Scale Analysis of Error Frequencies in Logo Programmin...

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53rd Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Staub, Jacqueline Chothia, Zaheer Univ Trier FB 4 Abt Informat D-54296 Trier Germany ETHZ Dept Comp Sci CH-8092 Zurich Switzerland

ISBN: (纸本)9781450390705

With the widespread introduction of computer science as a new school subject, programming is experiencing a strong and promising upswing in primary school education. Programming concepts can be taught in a constructive manner, fostering students' precision and algorithmic problem-solving skills. Simultaneously, this form of learning is also inherently challenging and error-prone. During a year-long study, we collected a trace of all failing Logo programs committed in the XLogoOnline programming environment. Analyzing this data set allows us to confirm that Logo errors follow the same patterns as many other programming languages. In particular, we shed a light on the following three areas of Logo programming: (i) we determine which programming errors occur and their respective frequency, (ii) we verify previous work confirming that a handful of error classes account for the vast majority of all errors committed, and (iii) we highlight that some errors are rooted in deep misunderstandings of programming concepts rather than mere syntactical flaws. A core tenet, we argue, is that whilst errors cannot be eliminated entirely they offer an opportunity for both researchers and pupils alike.

关键词： programming education syntax errors runtime error frequency analysis

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