Automated Program Repair(APR)techniques have shown significant potential in mitigating the cost and complexity associated with debugging by automatically generating corrective patches for software defects.Despite cons...Automated Program Repair(APR)techniques have shown significant potential in mitigating the cost and complexity associated with debugging by automatically generating corrective patches for software defects.Despite considerable progress in APR methodologies,existing approaches frequently lack contextual awareness of runtime behaviors and structural intricacies inherent in buggy source code.In this paper,we propose a novel APR approach that integrates attention mechanisms within an autoencoder-based framework,explicitly utilizing structural code affinity and execution context correlation derived from stack trace analysis.Our approach begins with an innovative preprocessing pipeline,where code segments and stack traces are transformed into tokenized representations.Subsequently,the BM25 ranking algorithm is employed to quantitatively measure structural code affinity and execution context correlation,identifying syntactically and semantically analogous buggy code snippets and relevant runtime error contexts from extensive repositories.These extracted features are then encoded via an attention-enhanced autoencoder model,specifically designed to capture significant patterns and correlations essential for effective patch generation.To assess the efficacy and generalizability of our proposed method,we conducted rigorous experimental comparisons against DeepFix,a state-of-the-art APR system,using a substantial dataset comprising 53,478 studentdeveloped C programs.Experimental outcomes indicate that our model achieves a notable bug repair success rate of approximately 62.36%,representing a statistically significant performance improvement of over 6%compared to the baseline.Furthermore,a thorough K-fold cross-validation reinforced the consistency,robustness,and reliability of our method across diverse subsets of the dataset.Our findings present the critical advantage of integrating attentionbased learning with code structural and execution context features in APR tasks,leading to improved accuracy and practical applicability.Future work aims to extend the model’s applicability across different programming languages,systematically optimize hyperparameters,and explore alternative feature representation methods to further enhance debugging efficiency and effectiveness.展开更多
介绍了高温蠕变工况下运行的压力容器可能出现的失效模式,结合工程设计现状,指出了我国当前压力容器标准体系在确定高温蠕变工况许用压应力时存在的技术瓶颈,在此基础之上引出ASME Code Case 3029,对其适用范围、发展历程、产生背景及...介绍了高温蠕变工况下运行的压力容器可能出现的失效模式,结合工程设计现状,指出了我国当前压力容器标准体系在确定高温蠕变工况许用压应力时存在的技术瓶颈,在此基础之上引出ASME Code Case 3029,对其适用范围、发展历程、产生背景及工程意义进行了简单的介绍,以某工程设计项目中的实际结构为例,介绍了该方法的使用过程及注意事项,并结合压力容器工程设计领域的实际需求,对我国标准体系下一步的制定或修订方向提出了展望。展开更多
Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a prom...Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a promising solution due to their outstanding error-correction performance and low complexity.Unequal error protection(UEP)involves nonuniform error safeguarding for distinct data segments,achieving a fine balance between error resilience and resource allocation,which ultimately enhancing system performance and efficiency.In this paper,we propose a novel class of UEP rateless polar codes.The codes are designed based on matrix extension of polar codes,and elegant mapping and duplication operations are designed to achieve UEP property while preserving the overall performance of conventional polar codes.Superior UEP performance is attained without significant modifications to conventional polar codes,making it straightforward for compatibility with existing polar codes.A theoretical analysis is conducted on the block error rate and throughput efficiency performance.To the best of our knowledge,this work provides the first theoretical performance analysis of UEP rateless polar codes.Simulation results show that the proposed codes significantly outperform existing polar coding schemes in both block error rate and throughput efficiency.展开更多
As artificial Intelligence(AI)continues to expand exponentially,particularly with the emergence of generative pre-trained transformers(GPT)based on a transformer’s architecture,which has revolutionized data processin...As artificial Intelligence(AI)continues to expand exponentially,particularly with the emergence of generative pre-trained transformers(GPT)based on a transformer’s architecture,which has revolutionized data processing and enabled significant improvements in various applications.This document seeks to investigate the security vulnerabilities detection in the source code using a range of large language models(LLM).Our primary objective is to evaluate the effectiveness of Static Application Security Testing(SAST)by applying various techniques such as prompt persona,structure outputs and zero-shot.To the selection of the LLMs(CodeLlama 7B,DeepSeek coder 7B,Gemini 1.5 Flash,Gemini 2.0 Flash,Mistral 7b Instruct,Phi 38b Mini 128K instruct,Qwen 2.5 coder,StartCoder 27B)with comparison and combination with Find Security Bugs.The evaluation method will involve using a selected dataset containing vulnerabilities,and the results to provide insights for different scenarios according to the software criticality(Business critical,non-critical,minimum effort,best effort)In detail,the main objectives of this study are to investigate if large language models outperform or exceed the capabilities of traditional static analysis tools,if the combining LLMs with Static Application Security Testing(SAST)tools lead to an improvement and the possibility that local machine learning models on a normal computer produce reliable results.Summarizing the most important conclusions of the research,it can be said that while it is true that the results have improved depending on the size of the LLM for business-critical software,the best results have been obtained by SAST analysis.This differs in“NonCritical,”“Best Effort,”and“Minimum Effort”scenarios,where the combination of LLM(Gemini)+SAST has obtained better results.展开更多
Differential pulse-position modulation(DP PM)can achieve a good compromise between power and bandwidth requirements.However,the output sequence has undetectable insertions and deletions.This paper proposes a successiv...Differential pulse-position modulation(DP PM)can achieve a good compromise between power and bandwidth requirements.However,the output sequence has undetectable insertions and deletions.This paper proposes a successive cancellation(SC)decoding scheme based on the weighted levenshtein distance(WLD)of polar codes for correcting insertions/deletions in DPPM systems.In this method,the WLD is used to calculate the transfer probabilities recursively to obtain likelihood ratios,and the low-complexity SC decoding method is built according to the error characteristics to match the DPPM system.Additionally,the proposed SC decoding scheme is extended to list decoding,which can further improve error correction performance.Simulation results show that the proposed scheme can effectively correct insertions/deletions in the DPPM system,which enhances its reliability and performance.展开更多
The ultracold neutron(UCN)transport code,MCUCN,designed initially for simulating UCN transportation from a solid deuterium(SD_2)source and neutron electric dipole moment experiments,could not simulate UCN storage and ...The ultracold neutron(UCN)transport code,MCUCN,designed initially for simulating UCN transportation from a solid deuterium(SD_2)source and neutron electric dipole moment experiments,could not simulate UCN storage and transportation in a superfluid^(4)He(SFHe,He-Ⅱ)source accurately.This limitation arose from the absence of an^(4)He upscattering mechanism and the absorption of^(3)He.And the provided source energy distribution in MCUCN is different from that in SFHe source.This study introduced enhancements to MCUCN to address these constraints,explicitly incorporating the^(4)He upscattering effect,the absorption of^(3)He,the loss caused by impurities on converter wall,UCN source energy distribution in SFHe,and the transmission through negative optical potential.Additionally,a Python-based visualization code for intermediate states and results was developed.To validate these enhancements,we systematically compared the simulation results of the Lujan Center Mark3 UCN system by MCUCN and the improved MCUCN code(iMCUCN)with UCNtransport simulations.Additionally,we compared the results of the SUN1 system simulated by MCUCN and iMCUCN with measurement results.The study demonstrates that iMCUCN effectively simulates the storage and transportation of ultracold neutrons in He-Ⅱ.展开更多
LargeLanguageModels(LLMs)are increasingly appliedinthe fieldof code translation.However,existing evaluation methodologies suffer from two major limitations:(1)the high overlap between test data and pretraining corpora...LargeLanguageModels(LLMs)are increasingly appliedinthe fieldof code translation.However,existing evaluation methodologies suffer from two major limitations:(1)the high overlap between test data and pretraining corpora,which introduces significant bias in performance evaluation;and(2)mainstream metrics focus primarily on surface-level accuracy,failing to uncover the underlying factors that constrain model capabilities.To address these issues,this paper presents TCode(Translation-Oriented Code Evaluation benchmark)—a complexity-controllable,contamination-free benchmark dataset for code translation—alongside a dedicated static feature sensitivity evaluation framework.The dataset is carefully designed to control complexity along multiple dimensions—including syntactic nesting and expression intricacy—enabling both broad coverage and fine-grained differentiation of sample difficulty.This design supports precise evaluation of model capabilities across a wide spectrum of translation challenges.The proposed evaluation framework introduces a correlation-driven analysis mechanism based on static program features,enabling predictive modeling of translation success from two perspectives:Code Form Complexity(e.g.,code length and character density)and Semantic Modeling Complexity(e.g.,syntactic depth,control-flow nesting,and type system complexity).Empirical evaluations across representative LLMs—including Qwen2.5-72B and Llama3.3-70B—demonstrate that even state-of-the-art models achieve over 80% compilation success on simple samples,but their accuracy drops sharply below 40% on complex cases.Further correlation analysis indicates that Semantic Modeling Complexity alone is correlated with up to 60% of the variance in translation success,with static program features exhibiting nonlinear threshold effects that highlight clear capability boundaries.This study departs fromthe traditional accuracy-centric evaluation paradigm and,for the first time,systematically characterizes the capabilities of large languagemodels in translation tasks through the lens of programstatic features.The findings provide actionable insights for model refinement and training strategy development.展开更多
Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively ...Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively high row weights,the existing blind recognition algorithms based on a candidate set generally perform worse.In this paper,we propose a blind recognition method for LDPC codes,called as tangent function assisted least square(TLS)method,which improves recognition performances by constructing a new cost function.To characterize the constraint degree among received vectors and paritycheck vectors,a feature function based on tangent function is constructed in the proposed algorithm.A cost function based on least square method is also established according to the feature function values satisfying the parity-check relationship.Moreover,the minimum average value in TLS is obtained on the candidate set.Numerical analysis and simulation results show that recognition performances of TLS algorithm are consistent with theoretical results.Compared with existing algorithms,the proposed method possesses better recognition performances.展开更多
Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Althoug...Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.展开更多
This paper proposes a class of novel progressive edge growth-based codebooks for downlink sparse code multiple access(SCMA)systems.In the first scheme,we propose to progressively design the codebooks of each resource ...This paper proposes a class of novel progressive edge growth-based codebooks for downlink sparse code multiple access(SCMA)systems.In the first scheme,we propose to progressively design the codebooks of each resource node(RN)instead of rotating a mother constellation(MC)as in the conventional SCMA works.In the other one,based on the MC,a multi-resources rotated codebooks are proposed to improve the performance of the superimposed constellations.The resultant codebooks are respectively referred to as the resource edge multidimensional codebooks(REMC)and the user edge multi-dimensional codebooks(UEMC).Additionally,we delve into the detailed design of the MC and the superimposed constellation.Then,we pay special attention to the application of the proposed schemes to challenging design cases,particularly for the high dimensional,high rate,and irregular codebooks,where the corresponding simplified schemes are proposed to reduce the complexity of codebook design.Finally,simulation results are presented to demonstrate the superiority of our progressive edge growth-based schemes.The numerical results indicate that the proposed codebooks significantly outperform the stateof-the-art codebooks.In addition,we also show that the proposed REMC codebooks outperform in the lower signal-to-noise ratio(SNR)regime,whereas the UEMC codebooks exhibit better performance at higher SNRs.展开更多
In this paper,we first generalize the constant dimension and orbit codes over finite fields to the constant rank and orbit codes over finite chain rings.Then we provide a relationship between constant rank codes over ...In this paper,we first generalize the constant dimension and orbit codes over finite fields to the constant rank and orbit codes over finite chain rings.Then we provide a relationship between constant rank codes over finite chain rings and constant dimension codes over the residue fields.In particular,we prove that an orbit submodule code over a finite chain ring is a constant rank code.Finally,for special finite chain ring F_(q)+γF_(q),we define a Gray mapφfrom(F_(q)+γF_(q))^(n)to F^(2n)_(q),and by using cyclic codes over F_(q)+γF_(q),we obtain a method of constructing an optimum distance constant dimension code over F_(q).展开更多
In erasure-coded storage systems,updating data requires parity maintenance,which often leads to significant I/O amplification due to“write-after-read”operations.Furthermore,scattered parity placement increases disk ...In erasure-coded storage systems,updating data requires parity maintenance,which often leads to significant I/O amplification due to“write-after-read”operations.Furthermore,scattered parity placement increases disk seek overhead during repair,resulting in degraded system performance.To address these challenges,this paper proposes a Cognitive Update and Repair Method(CURM)that leverages machine learning to classify files into writeonly,read-only,and read-write categories,enabling tailored update and repair strategies.For write-only and read-write files,CURM employs a data-differencemechanism combined with fine-grained I/O scheduling to minimize redundant read operations and mitigate I/O amplification.For read-write files,CURM further reserves adjacent disk space near parity blocks,supporting parallel reads and reducing disk seek overhead during repair.We implement CURM in a prototype system,Cognitive Update and Repair File System(CURFS),and conduct extensive experiments using realworld Network File System(NFS)and Microsoft Research(MSR)workloads on a 25-node cluster.Experimental results demonstrate that CURMimproves data update throughput by up to 82.52%,reduces recovery time by up to 47.47%,and decreases long-term storage overhead by more than 15% compared to state-of-the-art methods including Full Logging(FL),ParityLogging(PL),ParityLoggingwithReservedspace(PLR),andPARIX.These results validate the effectiveness of CURM in enhancing both update and repair performance,providing a scalable and efficient solution for large-scale erasure-coded storage systems.展开更多
Let m ≥ 2 be any natural number and let be a finite non-chain ring, where and q is a prime power congruent to 1 modulo (m-1). In this paper we study duadic codes over the ring and their extensions. A Gray map from to...Let m ≥ 2 be any natural number and let be a finite non-chain ring, where and q is a prime power congruent to 1 modulo (m-1). In this paper we study duadic codes over the ring and their extensions. A Gray map from to is defined which preserves self duality of linear codes. As a consequence self-dual, formally self-dual and self-orthogonal codes over are constructed. Some examples are also given to illustrate this.展开更多
Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitat...Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitations,a novel two-level serially concatenated MLC scheme,in which the bitlevels with similar reliability are bundled and transmitted together,is proposed.The proposed scheme hierarchically protects the two bit-level sets:the bitlevel sets at the higher level are sufficiently reliable and do not require excessive resources for protection,whereas only the bit-level sets at the lower level are encoded by polar codes.The proposed scheme has the advantages of low power consumption,low delay and high reliability.Moreover,an optimized constellation signal labeling rule that can enhance the performance is proposed.Finally,the superiority of the proposed scheme is validated through the theoretical analysis and simulation results.Compared with the bit interleaving coding modulation(BICM)scheme,under 256-quadrature amplitude modulation(QAM),the proposed scheme attains a performance gain of 1.0 dB while reducing the decoding complexity by 54.55%.展开更多
Aiming at the problem that the bit error rate(BER)of asymmetrically clipped optical orthogonal frequency division multiplexing(ACO-OFDM)space optical communication system is significantly affected by different turbule...Aiming at the problem that the bit error rate(BER)of asymmetrically clipped optical orthogonal frequency division multiplexing(ACO-OFDM)space optical communication system is significantly affected by different turbulence intensities,the deep learning technique is proposed to the polarization code decoding in ACO-OFDM space optical communication system.Moreover,this system realizes the polarization code decoding and signal demodulation without frequency conduction with superior performance and robustness compared with the performance of traditional decoder.Simulations under different turbulence intensities as well as different mapping orders show that the convolutional neural network(CNN)decoder trained under weak-medium-strong turbulence atmospheric channels achieves a performance improvement of about 10^(2)compared to the conventional decoder at 4-quadrature amplitude modulation(4QAM),and the BERs for both 16QAM and 64QAM are in between those of the conventional decoder.展开更多
The syndrome a posteriori probability of the log-likelihood ratio of intercepted codewords is used to develop an algorithm that recognizes the polar code length and generator matrix of the underlying polar code.Based ...The syndrome a posteriori probability of the log-likelihood ratio of intercepted codewords is used to develop an algorithm that recognizes the polar code length and generator matrix of the underlying polar code.Based on the encoding structure,three theorems are proved,two related to the relationship between the length and rate of the polar code,and one related to the relationship between frozen-bit positions,information-bit positions,and codewords.With these three theorems,polar codes can be quickly reconstruced.In addition,to detect the dual vectors of codewords,the statistical characteristics of the log-likelihood ratio are analyzed,and then the information-and frozen-bit positions are distinguished based on the minimumerror decision criterion.The bit rate is obtained.The correctness of the theorems and effectiveness of the proposed algorithm are validated through simulations.The proposed algorithm exhibits robustness to noise and a reasonable computational complexity.展开更多
National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire prote...National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire protection technologies has opened avenues for China to access a wealth of documents and codes,which are crucial in crafting regulations and developing a robust,scientific framework for fire code formulation.However,the translation of these codes into Chinese has been inadequate,thereby diminishing the benefits of technological exchange and collaborative learning.This underscores the necessity for comprehensive research into code translation,striving for higher-quality translations guided by established translation theories.In this study,we translated the initial segment of the NFPA 1 Fire Code into Chinese and examined both the source text and target text through the lens of Translation Shift Theory,a concept introduced by Catford.The conclusion culminated in identifying four key shifts across various linguistic levels:lexis,sentences,and groups,to ensure an accurate and precise translation of fire codes.This study offers a through and lucid explanation of how the translator integrates Catford’s theories to solve technical challenges in NFPA 1 Fire Code translation,and establish essential standards for construction translation practices.展开更多
Binary Code Similarity Detection(BCSD)is vital for vulnerability discovery,malware detection,and software security,especially when source code is unavailable.Yet,it faces challenges from semantic loss,recompilation va...Binary Code Similarity Detection(BCSD)is vital for vulnerability discovery,malware detection,and software security,especially when source code is unavailable.Yet,it faces challenges from semantic loss,recompilation variations,and obfuscation.Recent advances in artificial intelligence—particularly natural language processing(NLP),graph representation learning(GRL),and large language models(LLMs)—have markedly improved accuracy,enabling better recognition of code variants and deeper semantic understanding.This paper presents a comprehensive review of 82 studies published between 1975 and 2025,systematically tracing the historical evolution of BCSD and analyzing the progressive incorporation of artificial intelligence(AI)techniques.Particular emphasis is placed on the role of LLMs,which have recently emerged as transformative tools in advancing semantic representation and enhancing detection performance.The review is organized around five central research questions:(1)the chronological development and milestones of BCSD;(2)the construction of AI-driven technical roadmaps that chart methodological transitions;(3)the design and implementation of general analytical workflows for binary code analysis;(4)the applicability,strengths,and limitations of LLMs in capturing semantic and structural features of binary code;and(5)the persistent challenges and promising directions for future investigation.By synthesizing insights across these dimensions,the study demonstrates how LLMs reshape the landscape of binary code analysis,offering unprecedented opportunities to improve accuracy,scalability,and adaptability in real-world scenarios.This review not only bridges a critical gap in the existing literature but also provides a forward-looking perspective,serving as a valuable reference for researchers and practitioners aiming to advance AI-powered BCSD methodologies and applications.展开更多
文摘Automated Program Repair(APR)techniques have shown significant potential in mitigating the cost and complexity associated with debugging by automatically generating corrective patches for software defects.Despite considerable progress in APR methodologies,existing approaches frequently lack contextual awareness of runtime behaviors and structural intricacies inherent in buggy source code.In this paper,we propose a novel APR approach that integrates attention mechanisms within an autoencoder-based framework,explicitly utilizing structural code affinity and execution context correlation derived from stack trace analysis.Our approach begins with an innovative preprocessing pipeline,where code segments and stack traces are transformed into tokenized representations.Subsequently,the BM25 ranking algorithm is employed to quantitatively measure structural code affinity and execution context correlation,identifying syntactically and semantically analogous buggy code snippets and relevant runtime error contexts from extensive repositories.These extracted features are then encoded via an attention-enhanced autoencoder model,specifically designed to capture significant patterns and correlations essential for effective patch generation.To assess the efficacy and generalizability of our proposed method,we conducted rigorous experimental comparisons against DeepFix,a state-of-the-art APR system,using a substantial dataset comprising 53,478 studentdeveloped C programs.Experimental outcomes indicate that our model achieves a notable bug repair success rate of approximately 62.36%,representing a statistically significant performance improvement of over 6%compared to the baseline.Furthermore,a thorough K-fold cross-validation reinforced the consistency,robustness,and reliability of our method across diverse subsets of the dataset.Our findings present the critical advantage of integrating attentionbased learning with code structural and execution context features in APR tasks,leading to improved accuracy and practical applicability.Future work aims to extend the model’s applicability across different programming languages,systematically optimize hyperparameters,and explore alternative feature representation methods to further enhance debugging efficiency and effectiveness.
文摘介绍了高温蠕变工况下运行的压力容器可能出现的失效模式,结合工程设计现状,指出了我国当前压力容器标准体系在确定高温蠕变工况许用压应力时存在的技术瓶颈,在此基础之上引出ASME Code Case 3029,对其适用范围、发展历程、产生背景及工程意义进行了简单的介绍,以某工程设计项目中的实际结构为例,介绍了该方法的使用过程及注意事项,并结合压力容器工程设计领域的实际需求,对我国标准体系下一步的制定或修订方向提出了展望。
基金supported by National Natural Science Foundation of China(No.62301008)China Postdoctoral Science Foundation(No.2022M720272)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a promising solution due to their outstanding error-correction performance and low complexity.Unequal error protection(UEP)involves nonuniform error safeguarding for distinct data segments,achieving a fine balance between error resilience and resource allocation,which ultimately enhancing system performance and efficiency.In this paper,we propose a novel class of UEP rateless polar codes.The codes are designed based on matrix extension of polar codes,and elegant mapping and duplication operations are designed to achieve UEP property while preserving the overall performance of conventional polar codes.Superior UEP performance is attained without significant modifications to conventional polar codes,making it straightforward for compatibility with existing polar codes.A theoretical analysis is conducted on the block error rate and throughput efficiency performance.To the best of our knowledge,this work provides the first theoretical performance analysis of UEP rateless polar codes.Simulation results show that the proposed codes significantly outperform existing polar coding schemes in both block error rate and throughput efficiency.
文摘As artificial Intelligence(AI)continues to expand exponentially,particularly with the emergence of generative pre-trained transformers(GPT)based on a transformer’s architecture,which has revolutionized data processing and enabled significant improvements in various applications.This document seeks to investigate the security vulnerabilities detection in the source code using a range of large language models(LLM).Our primary objective is to evaluate the effectiveness of Static Application Security Testing(SAST)by applying various techniques such as prompt persona,structure outputs and zero-shot.To the selection of the LLMs(CodeLlama 7B,DeepSeek coder 7B,Gemini 1.5 Flash,Gemini 2.0 Flash,Mistral 7b Instruct,Phi 38b Mini 128K instruct,Qwen 2.5 coder,StartCoder 27B)with comparison and combination with Find Security Bugs.The evaluation method will involve using a selected dataset containing vulnerabilities,and the results to provide insights for different scenarios according to the software criticality(Business critical,non-critical,minimum effort,best effort)In detail,the main objectives of this study are to investigate if large language models outperform or exceed the capabilities of traditional static analysis tools,if the combining LLMs with Static Application Security Testing(SAST)tools lead to an improvement and the possibility that local machine learning models on a normal computer produce reliable results.Summarizing the most important conclusions of the research,it can be said that while it is true that the results have improved depending on the size of the LLM for business-critical software,the best results have been obtained by SAST analysis.This differs in“NonCritical,”“Best Effort,”and“Minimum Effort”scenarios,where the combination of LLM(Gemini)+SAST has obtained better results.
基金supported by National Natural Science Foundation of China(No.61801327).
文摘Differential pulse-position modulation(DP PM)can achieve a good compromise between power and bandwidth requirements.However,the output sequence has undetectable insertions and deletions.This paper proposes a successive cancellation(SC)decoding scheme based on the weighted levenshtein distance(WLD)of polar codes for correcting insertions/deletions in DPPM systems.In this method,the WLD is used to calculate the transfer probabilities recursively to obtain likelihood ratios,and the low-complexity SC decoding method is built according to the error characteristics to match the DPPM system.Additionally,the proposed SC decoding scheme is extended to list decoding,which can further improve error correction performance.Simulation results show that the proposed scheme can effectively correct insertions/deletions in the DPPM system,which enhances its reliability and performance.
基金the National Key R&D Program of China(No.2024YFE0110001)the National Natural Science Foundation of China(U1932219)the Mobility Programme endorsed by the Joint Committee of the Sino-German Center(M0728)。
文摘The ultracold neutron(UCN)transport code,MCUCN,designed initially for simulating UCN transportation from a solid deuterium(SD_2)source and neutron electric dipole moment experiments,could not simulate UCN storage and transportation in a superfluid^(4)He(SFHe,He-Ⅱ)source accurately.This limitation arose from the absence of an^(4)He upscattering mechanism and the absorption of^(3)He.And the provided source energy distribution in MCUCN is different from that in SFHe source.This study introduced enhancements to MCUCN to address these constraints,explicitly incorporating the^(4)He upscattering effect,the absorption of^(3)He,the loss caused by impurities on converter wall,UCN source energy distribution in SFHe,and the transmission through negative optical potential.Additionally,a Python-based visualization code for intermediate states and results was developed.To validate these enhancements,we systematically compared the simulation results of the Lujan Center Mark3 UCN system by MCUCN and the improved MCUCN code(iMCUCN)with UCNtransport simulations.Additionally,we compared the results of the SUN1 system simulated by MCUCN and iMCUCN with measurement results.The study demonstrates that iMCUCN effectively simulates the storage and transportation of ultracold neutrons in He-Ⅱ.
文摘LargeLanguageModels(LLMs)are increasingly appliedinthe fieldof code translation.However,existing evaluation methodologies suffer from two major limitations:(1)the high overlap between test data and pretraining corpora,which introduces significant bias in performance evaluation;and(2)mainstream metrics focus primarily on surface-level accuracy,failing to uncover the underlying factors that constrain model capabilities.To address these issues,this paper presents TCode(Translation-Oriented Code Evaluation benchmark)—a complexity-controllable,contamination-free benchmark dataset for code translation—alongside a dedicated static feature sensitivity evaluation framework.The dataset is carefully designed to control complexity along multiple dimensions—including syntactic nesting and expression intricacy—enabling both broad coverage and fine-grained differentiation of sample difficulty.This design supports precise evaluation of model capabilities across a wide spectrum of translation challenges.The proposed evaluation framework introduces a correlation-driven analysis mechanism based on static program features,enabling predictive modeling of translation success from two perspectives:Code Form Complexity(e.g.,code length and character density)and Semantic Modeling Complexity(e.g.,syntactic depth,control-flow nesting,and type system complexity).Empirical evaluations across representative LLMs—including Qwen2.5-72B and Llama3.3-70B—demonstrate that even state-of-the-art models achieve over 80% compilation success on simple samples,but their accuracy drops sharply below 40% on complex cases.Further correlation analysis indicates that Semantic Modeling Complexity alone is correlated with up to 60% of the variance in translation success,with static program features exhibiting nonlinear threshold effects that highlight clear capability boundaries.This study departs fromthe traditional accuracy-centric evaluation paradigm and,for the first time,systematically characterizes the capabilities of large languagemodels in translation tasks through the lens of programstatic features.The findings provide actionable insights for model refinement and training strategy development.
基金Fundamental Research Funds for the Central Universities under Grant 3072025YC0802the National Natural Science Foundation of China under Grant 62001138Heilongjiang Provincial Natural Science Foundation of China under Grant LH2021F009。
文摘Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively high row weights,the existing blind recognition algorithms based on a candidate set generally perform worse.In this paper,we propose a blind recognition method for LDPC codes,called as tangent function assisted least square(TLS)method,which improves recognition performances by constructing a new cost function.To characterize the constraint degree among received vectors and paritycheck vectors,a feature function based on tangent function is constructed in the proposed algorithm.A cost function based on least square method is also established according to the feature function values satisfying the parity-check relationship.Moreover,the minimum average value in TLS is obtained on the candidate set.Numerical analysis and simulation results show that recognition performances of TLS algorithm are consistent with theoretical results.Compared with existing algorithms,the proposed method possesses better recognition performances.
基金supported by Key Laboratory of Cyberspace Security,Ministry of Education,China。
文摘Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.
文摘This paper proposes a class of novel progressive edge growth-based codebooks for downlink sparse code multiple access(SCMA)systems.In the first scheme,we propose to progressively design the codebooks of each resource node(RN)instead of rotating a mother constellation(MC)as in the conventional SCMA works.In the other one,based on the MC,a multi-resources rotated codebooks are proposed to improve the performance of the superimposed constellations.The resultant codebooks are respectively referred to as the resource edge multidimensional codebooks(REMC)and the user edge multi-dimensional codebooks(UEMC).Additionally,we delve into the detailed design of the MC and the superimposed constellation.Then,we pay special attention to the application of the proposed schemes to challenging design cases,particularly for the high dimensional,high rate,and irregular codebooks,where the corresponding simplified schemes are proposed to reduce the complexity of codebook design.Finally,simulation results are presented to demonstrate the superiority of our progressive edge growth-based schemes.The numerical results indicate that the proposed codebooks significantly outperform the stateof-the-art codebooks.In addition,we also show that the proposed REMC codebooks outperform in the lower signal-to-noise ratio(SNR)regime,whereas the UEMC codebooks exhibit better performance at higher SNRs.
基金Supported by Research Funds of Hubei Province(D20144401,Q20174503)。
文摘In this paper,we first generalize the constant dimension and orbit codes over finite fields to the constant rank and orbit codes over finite chain rings.Then we provide a relationship between constant rank codes over finite chain rings and constant dimension codes over the residue fields.In particular,we prove that an orbit submodule code over a finite chain ring is a constant rank code.Finally,for special finite chain ring F_(q)+γF_(q),we define a Gray mapφfrom(F_(q)+γF_(q))^(n)to F^(2n)_(q),and by using cyclic codes over F_(q)+γF_(q),we obtain a method of constructing an optimum distance constant dimension code over F_(q).
基金supported by the National Natural Science Foundation of China(Grant No.62362019)the Natural Science Foundation of Hainan Province(Grant No.624RC482)the Hainan Provincial Higher Education Teaching Reform Research Project(Grant Hnjg2024-27).
文摘In erasure-coded storage systems,updating data requires parity maintenance,which often leads to significant I/O amplification due to“write-after-read”operations.Furthermore,scattered parity placement increases disk seek overhead during repair,resulting in degraded system performance.To address these challenges,this paper proposes a Cognitive Update and Repair Method(CURM)that leverages machine learning to classify files into writeonly,read-only,and read-write categories,enabling tailored update and repair strategies.For write-only and read-write files,CURM employs a data-differencemechanism combined with fine-grained I/O scheduling to minimize redundant read operations and mitigate I/O amplification.For read-write files,CURM further reserves adjacent disk space near parity blocks,supporting parallel reads and reducing disk seek overhead during repair.We implement CURM in a prototype system,Cognitive Update and Repair File System(CURFS),and conduct extensive experiments using realworld Network File System(NFS)and Microsoft Research(MSR)workloads on a 25-node cluster.Experimental results demonstrate that CURMimproves data update throughput by up to 82.52%,reduces recovery time by up to 47.47%,and decreases long-term storage overhead by more than 15% compared to state-of-the-art methods including Full Logging(FL),ParityLogging(PL),ParityLoggingwithReservedspace(PLR),andPARIX.These results validate the effectiveness of CURM in enhancing both update and repair performance,providing a scalable and efficient solution for large-scale erasure-coded storage systems.
文摘Let m ≥ 2 be any natural number and let be a finite non-chain ring, where and q is a prime power congruent to 1 modulo (m-1). In this paper we study duadic codes over the ring and their extensions. A Gray map from to is defined which preserves self duality of linear codes. As a consequence self-dual, formally self-dual and self-orthogonal codes over are constructed. Some examples are also given to illustrate this.
基金supported by the External Cooperation Program of Science and Technology of Fujian Province,China(2024I0016)the Fundamental Research Funds for the Central Universities(ZQN-1005).
文摘Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitations,a novel two-level serially concatenated MLC scheme,in which the bitlevels with similar reliability are bundled and transmitted together,is proposed.The proposed scheme hierarchically protects the two bit-level sets:the bitlevel sets at the higher level are sufficiently reliable and do not require excessive resources for protection,whereas only the bit-level sets at the lower level are encoded by polar codes.The proposed scheme has the advantages of low power consumption,low delay and high reliability.Moreover,an optimized constellation signal labeling rule that can enhance the performance is proposed.Finally,the superiority of the proposed scheme is validated through the theoretical analysis and simulation results.Compared with the bit interleaving coding modulation(BICM)scheme,under 256-quadrature amplitude modulation(QAM),the proposed scheme attains a performance gain of 1.0 dB while reducing the decoding complexity by 54.55%.
基金supported by the National Natural Science Foundation of China(No.12104141).
文摘Aiming at the problem that the bit error rate(BER)of asymmetrically clipped optical orthogonal frequency division multiplexing(ACO-OFDM)space optical communication system is significantly affected by different turbulence intensities,the deep learning technique is proposed to the polarization code decoding in ACO-OFDM space optical communication system.Moreover,this system realizes the polarization code decoding and signal demodulation without frequency conduction with superior performance and robustness compared with the performance of traditional decoder.Simulations under different turbulence intensities as well as different mapping orders show that the convolutional neural network(CNN)decoder trained under weak-medium-strong turbulence atmospheric channels achieves a performance improvement of about 10^(2)compared to the conventional decoder at 4-quadrature amplitude modulation(4QAM),and the BERs for both 16QAM and 64QAM are in between those of the conventional decoder.
基金supported by the National Natural Science Foundation of China(62371465)Taishan Scholar Project of Shandong Province(ts201511020)the Chinese National Key Laboratory of Science and Technology on Information System Security(6142111190404).
文摘The syndrome a posteriori probability of the log-likelihood ratio of intercepted codewords is used to develop an algorithm that recognizes the polar code length and generator matrix of the underlying polar code.Based on the encoding structure,three theorems are proved,two related to the relationship between the length and rate of the polar code,and one related to the relationship between frozen-bit positions,information-bit positions,and codewords.With these three theorems,polar codes can be quickly reconstruced.In addition,to detect the dual vectors of codewords,the statistical characteristics of the log-likelihood ratio are analyzed,and then the information-and frozen-bit positions are distinguished based on the minimumerror decision criterion.The bit rate is obtained.The correctness of the theorems and effectiveness of the proposed algorithm are validated through simulations.The proposed algorithm exhibits robustness to noise and a reasonable computational complexity.
基金Hangzhou Philosophy and Social Science Planning Program(24JD15)。
文摘National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire protection technologies has opened avenues for China to access a wealth of documents and codes,which are crucial in crafting regulations and developing a robust,scientific framework for fire code formulation.However,the translation of these codes into Chinese has been inadequate,thereby diminishing the benefits of technological exchange and collaborative learning.This underscores the necessity for comprehensive research into code translation,striving for higher-quality translations guided by established translation theories.In this study,we translated the initial segment of the NFPA 1 Fire Code into Chinese and examined both the source text and target text through the lens of Translation Shift Theory,a concept introduced by Catford.The conclusion culminated in identifying four key shifts across various linguistic levels:lexis,sentences,and groups,to ensure an accurate and precise translation of fire codes.This study offers a through and lucid explanation of how the translator integrates Catford’s theories to solve technical challenges in NFPA 1 Fire Code translation,and establish essential standards for construction translation practices.
文摘Binary Code Similarity Detection(BCSD)is vital for vulnerability discovery,malware detection,and software security,especially when source code is unavailable.Yet,it faces challenges from semantic loss,recompilation variations,and obfuscation.Recent advances in artificial intelligence—particularly natural language processing(NLP),graph representation learning(GRL),and large language models(LLMs)—have markedly improved accuracy,enabling better recognition of code variants and deeper semantic understanding.This paper presents a comprehensive review of 82 studies published between 1975 and 2025,systematically tracing the historical evolution of BCSD and analyzing the progressive incorporation of artificial intelligence(AI)techniques.Particular emphasis is placed on the role of LLMs,which have recently emerged as transformative tools in advancing semantic representation and enhancing detection performance.The review is organized around five central research questions:(1)the chronological development and milestones of BCSD;(2)the construction of AI-driven technical roadmaps that chart methodological transitions;(3)the design and implementation of general analytical workflows for binary code analysis;(4)the applicability,strengths,and limitations of LLMs in capturing semantic and structural features of binary code;and(5)the persistent challenges and promising directions for future investigation.By synthesizing insights across these dimensions,the study demonstrates how LLMs reshape the landscape of binary code analysis,offering unprecedented opportunities to improve accuracy,scalability,and adaptability in real-world scenarios.This review not only bridges a critical gap in the existing literature but also provides a forward-looking perspective,serving as a valuable reference for researchers and practitioners aiming to advance AI-powered BCSD methodologies and applications.
