查看更多>>摘要：Because of the low convergence accuracy of the basic Harris Hawks algorithm,which quickly falls into the local optimal,a Harris Hawks algorithm combining tuna swarm algorithm and differential mutation strategy(TDHHO)is proposed.The escape energy factor of nonlinear periodic energy decline balances the ability of global exploration and regional development.The parabolic foraging approach of the tuna swarm algorithm is introduced to enhance the global exploration ability of the algorithm and accelerate the conver-gence speed.The difference variation strategy is used to mutate the individual position and calculate the fitness,and the fitness of the original individual position is compared.The greedy technique is used to select the one with better fitness of the objective function,which increases the diversity of the population and improves the possibility of the algorithm jumping out of the local extreme value.The test function tests the TDHHO algorithm,and compared with other optimization algorithms,the experimental results show that the conver-gence speed and optimization accuracy of the improved Harris Hawks are improved.Finally,the enhanced Harris Hawks algorithm is applied to engineering optimization and wireless sensor networks(WSN)coverage optimization problems,and the feasibility of the TDHHO algorithm in practical application is further verified.
查看更多>>摘要：Code comments are crucial in software engineering,aiding in program maintenance and code reuse.The process of generating clear and descriptive code comments,outlining code functionality,is called code summarization.Existing code summarization methods are typically trained using transformer-based models.However,these trained models often possess limited parameters and lack specific train-ing tasks,hindering their ability to capture code semantics effectively.This paper uses a high-capacity pre-trained model,CodeT5,for code summarization.CodeT5 is designed with an encoder-decoder architecture that excels in code summarization tasks.Furthermore,we adopt a novel paradigm,"pre-train,prompt,predict",to unlock the knowledge embedded within CodeT5.We devise a prompt template to convert input code into code prompts and fine-tune CodeT5 with these prompts—a process we term prompt tuning.Our effectiveness experiments demonstrate that prompt tuning CodeT5 with only 40％of the dataset can achieve comparable performance to fine-tuning CodeT5 with 100％of the dataset.This means our approach is applicable in few-shot learning scenarios.Additionally,our prompt learning method is not sensitive to the size of the tuning dataset.Our practicality experiments show that the performance of prompt-tuned CodeT5 far surpasses that of transformer-based models trained on code-comment datasets collected from Stack Overflow.
查看更多>>摘要：The program construction process is based on rigorous mathematical reasoning,which leads to a fully correct algorithmic pro-gram via step-by-step refinement of the program specifications.The existing program construction methods'refinement process is partly based on individual subjective speculation and analysis,which lacks a precise guidance method.Meanwhile,efficiency factors have usu-ally been ignored in the construction process,and most of the constructed abstract programs cannot be run directly by machines.In order to solve these problems,a novel program construction method for the sequence statistical class algorithms based on bidirectional scan induc-tion is proposed in this paper.The method takes into account the efficiency factor and thus improves the Morgan's refinement calculus.Fur-thermore,this paper validates the method's feasibility using an efficiency-sensitive sequential statistics class algorithm as a program con-struction example.The method proposed in this paper realizes the correctness construction process from program specifications to efficient executable programs.
查看更多>>摘要：Many search-based Automatic Program Repair(APR)techniques employ a set of repair patterns to generate candidate patches.Regarding repair pattern selection,existing search-based APR techniques either randomly select a repair pattern from the repair pattern set to apply or prioritize all repair patterns based on the bug's context information.In this paper,we introduce PatternNet,a multi-view feature fusion model capable of predicting the repair pattern for a reported software bug.To accomplish this task,PatternNet first extracts multi-view features from the pair of buggy code and bug report using different models.Specifically,a transformer-based model(i.e.,UniXcoder)is utilized to obtain the bimodal feature representation of the buggy code and bug report.Additionally,an Abstract Syntax Tree(AST)-based neural model(i.e.,ASTNN)is employed to learn the feature representation of the buggy code.Second,a co-attention mechanism is adopted to capture the dependencies between the statement trees in the AST of the buggy code and the textual tokens of the reported bug,resulting in co-attentive features between statement trees and reported bug's textual tokens.Finally,these multi-view features are combined into a unified representation using a feature fusion network.We quantitatively demonstrate the effectiveness of PatternNet and the feature fusion network for predicting software bug repair patterns.
查看更多>>摘要：This paper proposes a new density measurement algorithm to address the issues of poor applicability and inaccurate results as-sociated with the automatic density measurement algorithm for weft-knitted fabrics.The algorithm involves collecting the transmitted light image of the knitted fabric,calculating the tilt angle using the skewing correction algorithm,and rotating the image to correct the weft skew present therein.The pre-rotated and post-rotated images are then projected vertically and horizontally in grayscale,and the obtained projection curves are used to represent the distribution of loops in vertical and horizontal rows.This study proposed a wave peak coordi-nate verification algorithm that calculates the coursewise densities and walewise densities of the knitted fabric.In experiments,the pro-posed density measurement method is found to exhibit an accuracy above 98％when compared with the manual mode.
查看更多>>摘要：With the rapid development of Internet of Things(IoT)technology,smart home users can access and control smart devices re-motely to enjoy convenient and efficient services.However,sensitive data collected by smart devices is vulnerable to attacks such as eaves-dropping and simulation when transmitted through public channels.At the same time,the security of resource-constrained smart devices is low,and attackers may use the controlled devices to carry out malicious operations further.To address the aforementioned existing security issues,this paper proposes a lightweight user anonymous authentication scheme for resource-constrained smart home environments.At the same time,the security analysis is carried out to further prove the proposed scheme's security.Finally,the performance analysis between the proposed scheme and the existing similar schemes proves that the proposed scheme has advantages in calculation cost and safety char-acteristics.
查看更多>>摘要：Telecare Medical Information System(TMIS)can provide various telemedicine services to patients.However,information is communicated over an open channel.An attacker may intercept,replay,or modify this information.Therefore,many authentication schemes are proposed to provide secure communication for TMIS.Recently,Yu et al proposed a privacy-preserving authentication scheme in the Internet of Medical Things(IoMT)-enabled TMIS environments.They emphasize that their scheme is resistant to various attacks and ensures anonymity.Unfortunately,this paper demonstrates that Yu et al's scheme is vulnerable to impersonation attacks,replay attacks,and tracking attacks and cannot mutually authenticate.To overcome the shortcomings of Yu et al's scheme,we mainly improve the authentica-tion and key agreement process and propose a corresponding improved scheme.We also compare the improved scheme with several exist-ing authentication schemes in terms of security and computational efficiency.
查看更多>>摘要：Nowadays,Internet of Everything has become a major trend,and Internet of Things(IoT)has emerged.Wireless sensor net-works(WSNs)are core technologies for IoT to sense the real world.Due to the unattended and resource-constrained characteristics of WSNs,it is a great challenge to design an efficient and secure authentication scheme for communication between users and sensor nodes in WSNs.Recently,Hu et al proposed an authentication scheme for WSNs in an IoT environment.They claimed that their scheme could maximize the balance between security and computational cost as well as efficiency,and be resistant to many known attacks.However,we find that the scheme is difficult to resist stolen smart card attack and denial-of-service attack.Moreover,during the login and key negotia-tion phase of the scheme,Gateway(GWN)is unable to extract key values for subsequent computation based on the messages sent by the sensor nodes,which in turn leads to the inability to achieve mutual authentication and key agreement.To overcome these shortcomings,we propose an improved scheme.The proposed scheme enables real-time data exchange and transmission as well as secure communication be-tween users and sensor nodes.
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