the recent program development industries have required problem-solving abilities for engineers, especially application developers. However, AI-based education systems to help solve computer algorithm problems have no...
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the recent program development industries have required problem-solving abilities for engineers, especially application developers. However, AI-based education systems to help solve computer algorithm problems have not yet attracted attention, while most big tech companies require the ability to solve algorithm problems including Google, Meta, and Amazon. the most useful guide to solving algorithm problems might be guessing the category (tag) of the facing problems. therefore, our study addresses the task of predicting the algorithm tag as a useful tool for engineers and developers. Moreover, we also consider predicting the difficulty levels of algorithm problems, which can be used as useful guidance to calculate the required time to solve that problem. In this paper, we present a real-world algorithm problem multi-task dataset, AMT, by mainly collecting problem samples from the most famous and large competitive programming website Codeforces. To the best of our knowledge, our proposed dataset is the most large-scale dataset for predicting algorithm tags compared to previous studies. Moreover, our work is the first to address predicting the difficulty levels of algorithm problems. We present a deep learning-based novel method for simultaneously predicting algorithm tags and the difficulty levels of an algorithm problem given.
An adaptive agent changes its behavior in response to the changes it observes in its operating environment. Conversely, it exhibits a particular behavior in between adaptations. It is beneficial for other agents to kn...
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the expediency of using multi-functional laboratory stands in the process of training specialists in the electromechanical profession is substantiated. the paper contains characteristics of the small-scale model of th...
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the proceedings contain 14 papers. the topics discussed include: towards developing effective fault localization techniques for termination bugs in loop programs;RepairCAT: applying large language model to fix bugs in...
ISBN:
(纸本)9798400705779
the proceedings contain 14 papers. the topics discussed include: towards developing effective fault localization techniques for termination bugs in loop programs;RepairCAT: applying large language model to fix bugs in AI-generated programs;automated program repair for introductory programming assignments via bidirectional refactoring;C-pack of IPAs: A C90 program benchmark of introductory programming assignments;ASAP-Repair: API-specific automated program repair based on API usage graphs;BOSS: Adataset to train ML-based systems to repair programs with out-of-bounds write flaws;large language models in automated repair of Haskell Type errors;and ARJA-e for the first international competition on automated program repair.
the development of programming education has given rise to automated program repair techniques tailored for introductory programming assignments (IPAs). Despite the promising performance of mainstream automated feedba...
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ISBN:
(纸本)9798350353020;9798400705779
the development of programming education has given rise to automated program repair techniques tailored for introductory programming assignments (IPAs). Despite the promising performance of mainstream automated feedback generation systems, they still struggle to handle scenarios where there is "no matching controlflow to generate repair" well. this paper presents Brafar, an innovative automated program repair tool for IPAs. Brafar tackles the core issue through a novel "bidirectional refactoring" algorithm which aligns the control-flow structures of the incorrect and reference programs without semantic changes. Additionally, Brafar incorporates a specification inference technique to further enhance the repair process, reducing the occurrence of unnecessary repairs. We have implemented the Brafar tool in Python and it is now publicly available. In comparative experiments, boththe Brafar tool and the baseline Refactory tool were evaluated using 100 real-life incorrect programs from 5 different IPAs. the outcomes of these experiments demonstrated that our Brafar tool outperformed the baseline tool in terms of repair accuracy.
the proceedings contain 57 papers. the topics discussed include: on network congestion reduction using public signals under boundedly rational user equilibria;incentive designs under disparate probabilistic outlooks a...
the proceedings contain 57 papers. the topics discussed include: on network congestion reduction using public signals under boundedly rational user equilibria;incentive designs under disparate probabilistic outlooks across decision makers;mitigating information asymmetry in two-stage contracts with non-myopic agents;to travel quickly or to park conveniently: coupled resource allocations withmulti-karma economies;learning-allocation dynamics in coalitional games with transferable utility;learning-based cognitive architecture for enhancing coordination in human groups;personalized artificial pancreas for glucose regulation in people with diabetes;preventing ankle sprain: integrating preview control barrier functions with human movement primitive prediction;and a novel dynamically self-tuned force/torque observer formulation for human interaction in collaborative robotic applications.
the widespread integration of renewable energy presents significant challenges for power system scheduling. Traditional power system scheduling is mainly based on the concept of "coordinating on a multi-time-leve...
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As microservices architecture has steadily emerged as the prevailing direction in software system design, the assurance of services within microservices systems has garnered increasing attention. the concept of intell...
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the proceedings contain 106 papers. the topics discussed include: joint sparse estimation with cardinality constraint via mixed-integer semidefinite programming;overdispersed photon-limited sparse signal recovery usin...
ISBN:
(纸本)9798350344523
the proceedings contain 106 papers. the topics discussed include: joint sparse estimation with cardinality constraint via mixed-integer semidefinite programming;overdispersed photon-limited sparse signal recovery using nonconvex regularization;k-subspaces for sequential data;a preconditioned hessian proximal algorithm for spectral compressed sensing;decoding the hidden: direct image classification using coded aperture imaging;clustering on the Stiefel manifold with symmetric block term decomposition;multi-model federated learning optimization based on multi-agent reinforcement learning;self-interference aware codebook design for full-duplex joint sensing and communication systems at mmWave;binary group sparsity in multi anchor direct localization;and multi-target tracking with transferable convolutional neural networks.
the proceedings contain 18 papers. the special focus in this conference is on Engineeringmulti-agentsystems. the topics include: Synthesizing multi-agent System Organization from Engineering Descriptions;towards...
ISBN:
(纸本)9783031485381
the proceedings contain 18 papers. the special focus in this conference is on Engineeringmulti-agentsystems. the topics include: Synthesizing multi-agent System Organization from Engineering Descriptions;towards Developing Digital Twin Enabled multi-agentsystems;Towards Context-Based Authorizations for Interactions in Hypermedia-Driven agent Environments - the CASHMERE Framework;towards Framing the agents & Artifacts Conceptual Model at the Knowledge Level: First Ideas and Experiments;pody: A Solid-Based Approach to Embody agents in Web-Based multi-agent-systems;Fantastic MASs and Where to Find them: First Results and Lesson Learned;the Entity-Operation Model for Practical multi-entity Deployment;Remote Deployment of a JADE agent in Docker;imperative and Event-Driven programming of Interoperable Software agents;vGOAL: A GOAL-Based Specification Language for Safe Autonomous Decision-Making;protocol-Based Engineering of Microservices;Exploiting Service-Discovery and OpenAPI in multi-agent MicroServices (MAMS) Applications;Using multi-agent MicroServices (MAMS) for agent-Based Modelling;dynamics of Causal Dependencies in multi-agent Settings;multi-armed Bandit Based Tariff Generation Strategy for multi-agent Smart Grid systems;Load Balancing in Distributed multi-agent Path Finder (DMAPF).
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