Teaching secure programming, including concepts like buffer overflow, is challenging. Advanced AI Coding Assistants aim to help with programming instruction, but it's unclear how effective they are at promoting se...
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Executable models of biological circuits offer the ability to simulate their behavior under different settings with important biomedical applications. In particular, Boolean network models have been a prime research f...
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ISBN:
(纸本)9781071639887;9781071639894
Executable models of biological circuits offer the ability to simulate their behavior under different settings with important biomedical applications. In particular, Boolean network models have been a prime research focus and dozens of manually curated Boolean models are available in public databases. A key challenge in studying the dynamics of these models is determining their asymptotic behavior, that is the state-sets or attractors they converge to. This is particularly challenging for large networks, as the state space size grows exponentially. Here we introduce a novel method for identifying stable components within attractors under an asynchronous update scheme. Our method leverages the observation that the majority of cellular functions in current models can be described as linear threshold functions, facilitating an efficient integer programming formulation for the problem. We conduct simulations on both synthetic and real biological networks, demonstrating that our proposed method is highly efficient and outperforms previous methods.
Smart homes are usually programmed using Event-Condition-Action rules, which is problematic for integrity maintenance, as the user needs to know which events may lead to an invalid state, and which actions - depending...
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ISBN:
(纸本)9783031724060;9783031724077
Smart homes are usually programmed using Event-Condition-Action rules, which is problematic for integrity maintenance, as the user needs to know which events may lead to an invalid state, and which actions - depending on the event - to take to repair the system. This paper describes an approach for integrity maintenance in a smart home system using Answer Set programming. Using the popular open source home automation platform "Home Assistant" as a framework, we allow users to specify desired integrity constraints for their home in a familiar syntax, i.e. Python Boolean expressions with some special functions. By rewriting the user's system invariant to goal descriptions and adding ASP rules for planning service calls to change device states where possible, the system tries to restore itself to a desired state, whenever necessary.
Large language models (LLMs) are revolutionizing the field of computing education with their powerful code-generating capabilities. Traditional pedagogical practices have focused on code writing tasks, but there is no...
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ISBN:
(纸本)9798400704239
Large language models (LLMs) are revolutionizing the field of computing education with their powerful code-generating capabilities. Traditional pedagogical practices have focused on code writing tasks, but there is now a shift in importance towards reading, comprehending and evaluating LLM-generated code. Alongside this shift, an important new skill is emerging - the ability to solve programming tasks by constructing good prompts for code-generating models. In this work we introduce a new type of programming exercise to hone this nascent skill: 'Prompt Problems'. Prompt Problems are designed to help students learn how to write effective prompts for AI code generators. A student solves a Prompt Problem by crafting a natural language prompt which, when provided as input to an LLM, outputs code that successfully solves a specified programming task. We also present a new web-based tool called Promptly which hosts a repository of Prompt Problems and supports the automated evaluation of prompt-generated code. We deploy Promptly in one CS1 and one CS2 course and describe our experiences, which include student perceptions of this new type of activity and their interactions with the tool. We find that students are enthusiastic about Prompt Problems, and appreciate how the problems engage their computational thinking skills and expose them to new programming constructs. We discuss ideas for the future development of new variations of Prompt Problems, and the need to carefully study their integration into classroom practice.
Despite the numerous benefits of reversible computing, non-reversible systems remain relevant in the real world. There are cases where reversibility is even detrimental, for example when performing lossy data compress...
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ISBN:
(纸本)9783031620751;9783031620768
Despite the numerous benefits of reversible computing, non-reversible systems remain relevant in the real world. There are cases where reversibility is even detrimental, for example when performing lossy data compressions, where the removal of information is inherently required. For reversible systems to be more broadly adopted, they need to be able to interact with non-reversible systems in one way or another. To allow for seamless co-operation between both paradigms, we propose the integration of optional non-reversibility as a first-class citizen into reversible programming languages to create what we call hybrid programming languages. A hybrid programming language can express both reversible and non-reversible computations in a single host language. This paper describes the hybrid static single assignment form HSSA. Based on the principles of RSSA, HSSA puts reversibility and determinism first, while providing facilities to allow for explicit nondeterminism in either direction. This also includes forward-nondeterminism while maintaining the useful properties of symmetry and invertibility.
This article explores the intersection of the translation of machine code and translation of natural languages. Starting with the deep-seated metaphor the brain is a computer, this study demonstrates the extent to whi...
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This article explores the intersection of the translation of machine code and translation of natural languages. Starting with the deep-seated metaphor the brain is a computer, this study demonstrates the extent to which computerscience, cognitive science, linguistics and translation are intertwined. The parallels between difficulties of translating computer code and natural languages point to the failure to find a workable interlingua and the importance of complexity studies and emergent properties for both fields. Thus translation studies would do well to examine more carefully the extent to which a computational understanding of the brain has shaped basic concepts and approaches to translation. At the same time, homologies between the market for translation of computer languages and natural languages and the need in programming to be more sensitive to the needs of non-English speakers suggests that translation studies has much to offer to computerscience.
Recent advances in artificial intelligence have led to the development of large language models (LLMs), which are able to generate text, images, and source code based on prompts provided by humans. In this paper, we e...
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ISBN:
(纸本)9798400701382
Recent advances in artificial intelligence have led to the development of large language models (LLMs), which are able to generate text, images, and source code based on prompts provided by humans. In this paper, we explore the capabilities of an LLM - OpenAI's GPT3 model to provide feedback for student written code. Specifically, we examine the feasibility of GPT-3 to check, critique and suggest changes to code written by learners in an online programming exam of an undergraduate Python programming course. We collected 1211 student code submissions from 7 questions asked in a programming exam, and provided the GPT-3 model with separate prompts to check, critique and provide suggestions on these submissions. We found that there was a high variability in the accuracy of the model's feedback for student submissions. Across questions, the range for accurately checking the correctness of the code was between 57% to 79%, between 41% to 77% for accurately critiquing code, and between 32% and 93% for suggesting appropriate changes to the code. We also found instances where the model generated incorrect and inconsistent feedback. These findings suggest that models like GPT-3 currently cannot be 'directly' used to provide feedback to students for programming assessments.
Students' difficulties to learn concurrent programming are well known amongst computerscience instructors. While in the International Computing Education community it is still up to debate the extent to which suc...
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ISBN:
(纸本)9783031448997;9783031449000
Students' difficulties to learn concurrent programming are well known amongst computerscience instructors. While in the International Computing Education community it is still up to debate the extent to which such topic should be included in pre-university curricula, based on our country's Ministerial guidelines for technical high schools with a specialization in computerscience, students are expected to acquire key concurrent programming skills. With the aim of getting insights about the nature of students' difficulties, as well as to identify possible pedagogical approaches to be adopted by teachers, we have undertaken an investigation on students' perception, proficiency and self-confidence when dealing with concurrency and synchronization tasks. We then present the results of a preliminary study carried out by submitting a survey in a couple of representative high schools of our area. The survey includes subjective perception questions as well as small program comprehension tasks addressing students' understanding of thread synchronization. Moreover, we also analyze students' self-confidence in connection with their actual performance in such tasks. A total of 68 high school students were engaged in the survey. Our findings indicate that students' perception of self-confidence tends to weakly correlate to their actual performance, although more in general they express a low self-confidence level in relation to the topic. In particular, the results clearly show that the concept of thread synchronization is especially difficult to master for a large majority of them.
There were few papers for interdisciplinary integration of Scratch programming, English learning, and local cultures as far as the digital animated E-book creation of elementary schools was concerned. This article pro...
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There were few papers for interdisciplinary integration of Scratch programming, English learning, and local cultures as far as the digital animated E-book creation of elementary schools was concerned. This article proposes an interdisciplinary innovative teaching mode, with college students as teachers, Scratch programming and English learning as tools, and a local legend The Wind Chasers of Siraya as material for schoolchildren in a remote area of Taiwan. Schoolchildren were divided into four groups, and each group was responsible for a part, and finally these four parts were integrated into a complete animated English picture book with images, sound, music, and games. The purpose is to enhance the acquisition and learning of information technology and English application among schoolchildren in the remote area. Participants were evaluated in accordance with their learning motivation, self-efficacy, and learning effect. The self-efficacy scale was designed from three dimensions of the self-efficacy theory presented by Bandura and the syllabus of five functions in Scratch. The teaching effects were investigated with paired sample t test. The results of these assessments revealed that schoolchildren's learning motivation has been elevated, with a significant improvement of self-efficacy and overall learning achievement. In addition, the post-test revealed that Scratch programming and English learning from the culture-based illustration book had significant correlation, which suggested that the overall program successfully integrated these two subjects.
Brain activity analysis can be used to determine an individual's mental state while performing a certain task. This study examined the learners’ brain activity changes, the correlation between their performances ...
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ISBN:
(纸本)9781665454810
Brain activity analysis can be used to determine an individual's mental state while performing a certain task. This study examined the learners’ brain activity changes, the correlation between their performances in reading tasks and answering exercises, and regression analysis to determine the significant impact of mental load tasks on the performance score of the learners. This experiment involved 15 learners, performing eleven (11) tasks which included reading, exercise questions, and coding tasks at their own pace while wearing EmotivEpocX brainware technology. The EEG signals collected were processed to compute the absolute power spectra that served as input values for analysis. Findings in this study revealed that the learners exhibited a frequency band BETA classified as "high mental load," indicating that learners were actively engaged and alert in performing the tasks, and there were no significant differences based on Gamma, Beta, Alpha, and Theta. Moreover, the correlation analysis revealed that the mental load tasks were not statistically significant since the p-value of the variables in between was greater than the 0.05 level of significance. Likewise, regression analysis showed that the brain activity, having a "high mental load" had no significant impact or relationship on the learners' over-all performance score with an F-statistic of 0.9293. As all the p-value of the task coefficients were found to be greater than the significant level, the teaching-learning activities must be revisited to further improve the analytical and logical skills of the learners and serve as a strong basis for educational strategists to manage the activities and avoid information overload that clearly affects the learners' performance.
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