检索结果-内蒙古大学图书馆

Sequence-to-Sequence Learning-Based Conversion of pseudo-code to Source code Using Neural Translation Approach

IEEE ACCESS 2022年 10卷 26730-26742页

作者： Acharjee, Uzzal Kumar Arefin, Minhazul Hossen, Kazi Mojammel Uddin, Mohammed Nasir Uddin, Md Ashraf Islam, Linta Jagannath Univ Dept Comp Sci & Engn Dhaka 1100 Bangladesh Federat Univ Internet Commerce Secur Lab Ctr Informat & Appl Optimisat Ballarat Vic 3350 Australia

pseudo-code refers to an informal means of representing algorithms that do not require the exact syntax of a computer programming language. pseudo-code helps developers and researchers represent their algorithms using human-readable language. Generally, researchers can convert the pseudo-code into computer source code using different conversion techniques. The efficiency of such conversion methods is measured based on the converted algorithm's correctness. Researchers have already explored diverse technologies to devise conversion methods with higher accuracy. This paper proposes a novel pseudo-code conversion learning method that includes natural language processing-based text preprocessing and a sequence-to-sequence deep learning-based model trained with the SPoC dataset. We conducted an extensive experiment on our designed algorithm using descriptive bilingual understudy scoring and compared our results with state-of-the-art techniques. Result analysis shows that our approach is more accurate and efficient than other existing conversion methods in terms of several performances metrics. Furthermore, the proposed method outperforms the existing approaches because our method utilizes two Long-Short-Term-Memory networks that might increase the accuracy.

关键词： codes Natural language processing Semantics Computer languages Deep learning Transformers Tokenization Sequence-to-sequence learning model natural language processing pseudo-code machine translation source code

来源：评论

学校读者我要写书评

暂无评论

Unleashing the power of pseudo-code for binary code similarity analysis

引用

Cybersecurity 2023年第2期6卷 44-61页

作者： Weiwei Zhang Zhengzi Xu Yang Xiao Yinxing Xue School of Computer Science and Engineering University of Science and Technology of ChinaHefeiChina School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore Institute of Information Engineering Chinese Academy of SciencesBeijingChina School of Cyber Security University of Chinese Academy of SciencesBeijingChina

code similarity analysis has become more popular due to its significant applicantions,including vulnerability detection,malware detection,and patch *** the source code of the software is difficult to obtain under most circumstances,binary-level code similarity analysis(BCSA)has been paid much attention *** recent years,many BCSA studies incorporating Al techniques focus on deriving semantic information from binary functions with code representations such as assembly code,intermediate representations,and control flow graphs to measure the ***,due to the impacts of different compilers,architectures,and obfuscations,binaries compiled from the same source code may vary considerably,which becomes the major obstacle for these works to obtain robust *** this paper,we propose a solution,named UPPC(Unleashing the Power of pseudo-code),which leverages the pseudo-code of binary function as input,to address the binary code similarity analysis challenge,since pseudocode has higher abstraction and is platform-independent compared to binary *** selectively inlines the functions to capture the full function semantics across different compiler optimization levels and uses a deep pyramidal convolutional neural network to obtain the semantic embedding of the *** evaluated UPPC on a data set containing vulnerabilities and a data set including different architectures(X86,ARM),different optimization options(O0-O3),different compilers(GCC,Clang),and four obfuscation *** experimental results show that the accuracy of UPPC in function search is 33.2%higher than that of existing methods.

关键词： Binary code similarity Machine learning Software security pseudo-code

来源：评论

学校读者我要写书评

暂无评论

pseudo-code SIMULATION OF DESIGNER ACTIVITY IN CONCEPTUAL DESIGNING OF SOFTWARE INTENSIVE SYSTEMS

PSEUDO-CODE SIMULATION OF DESIGNER ACTIVITY IN CONCEPTUAL DE...

引用

27th European Conference on Modelling and Simulation, ECMS 2013

作者： Sosnin, Petr Ulyanovsk State Tech Univ Comp Dept Ulyanovsk 432027 Russia

The paper presents an experiential approach to a real time activity of designers at a conceptual stage of their work. The offered approach is based on a pseudo-code simulation of such activity. The simulation are bein... 详细信息

ISBN: (纸本)9780956494467

关键词： Conceptual designing pseudo-code simulation

来源：评论

学校读者我要写书评

暂无评论

Is the Corpus Ready for Machine Translation? A Case Study with Python to pseudo-code Corpus

引用

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2023年第2期48卷 1845-1858页

作者： Rai, Sawan Belwal, Ramesh Chandra Gupta, Atul PDPM Indian Inst Informat Technol Design & Mfg Jabalpur 482005 India

The availability of data is the driving force behind most of the state-of-the-art techniques for machine translation tasks. Understandably, this availability of data motivates researchers to propose new techniques and claim about the superiority of their techniques over the existing ones by using suitable evaluation measures. However, the performance of underlying learning algorithms can be greatly influenced by the correctness and the consistency of the corpus. We present our investigations for the relevance of a publicly available python to pseudo-code parallel corpus for automated documentation task, and the studies performed using this corpus. We found that the corpus had many visible issues like overlapping of instances, inconsistency in translation styles, incompleteness, and misspelled words. We show that these discrepancies can significantly influence the performance of the learning algorithms to the extent that they could have caused previous studies to draw incorrect conclusions. We performed our experimental study using statistical machine translation and neural machine translation models. We have recorded a significant difference (similar to 10% on BLEU score) in the models' performance after removing the issues from the corpus.

关键词： Parallel corpus Python code pseudo-code Statistical machine translation Neural machine translation

来源：评论

学校读者我要写书评

暂无评论

First approach to the design of a natural pseudo-code language: the case of keywords 24

First approach to the design of a natural pseudo-code langua...

引用

International Symposium on Computers in Education (SIIE)

作者： Lopez Garcia, Antonio Urquiza-Fuentes, Jaime Univ Rey Juan Carlos LITE Lab Informat Technol Educ Madrid Spain

ISBN: (数字)9781665474641

ISBN: (纸本)9781665474641

pseudo-code is a well-known and widely used tool for beginners in learning programming. It supposes a first approach to a textual programming language avoiding in part the formalities of these, for example, using the mother tongue pseudocode. The intuitive idea is that much of the pseudo-code used today is similar and quite close to a direct translation from high level programming languages. The motivation of this work is to investigate to what extent the pseudo-code fulfills its function of approach to programming. the main objective of pseudo-code is to express the tasks to be carried out by the program. Therefor, to facilitate learning, pseudo-code's constructions should be easy to understand. This work focuses on keywords commonly used for basic instructions and execution flow control. It consists of a survey of students from different vocational training cycles about these keywords. The initial result seems to show that, in some cases, their responses match the "classic" pseudo-code, but in others they are quite different. However, we believe it is convenient to extend the study to a greater population.

关键词： pseudo-code mother tongue keywords studentcentered design training cycle

来源：评论

学校读者我要写书评

暂无评论

The pseudo-code representation of Test Resources and Test Requirements in ATML 6

The Pseudo-code representation of Test Resources and Test Re...

引用

6th International Conference on Information Science and Control Engineering (ICISCE)

作者： Fan Shuyi Wei Baohua Jiang Huixia Army Engn Univ Shijiazhuang Campus Shijiazhuang Hebei Peoples R China

ISBN: (数字)9781728157122

ISBN: (纸本)9781728157122

The ATML documents are used to describe test information and are represented in XML format. We can consider using computer to automatically identify and extract relevant test information in the document, based on which the test program of the test system can be automatically generated. Therefore, it is necessary to analyze the documents that representing the elements of the test system to determine the pseudo-code representation of these elements, so as to facilitate the automatic generation of test programs. This paper analyses the test capability of test instruments in ATML test description document and the test requirements of UUT, as well as the cable connection between ATE, ITA and UUT. On this basis, the data structures of connectors, ports, resources, switches, capabilities and cable connections are defined, which lays the foundation for automatic generation of test programs.

关键词： ATML pseudo-code Automatic Test Program Generation Test resources Test Requirements

来源：评论

学校读者我要写书评

暂无评论

Generating pseudo-code from Source code Using Deep Learning 25

Generating Pseudo-Code from Source Code Using Deep Learning

引用

25th Australasian Software Engineering Conference (ASWEC)

作者： Alhefdhi, Abdulaziz Dam, Hoa Khanh Hata, Hideaki Ghose, Aditya Univ Wollongong Wollongong NSW Australia Nara Inst Sci & Technol Ikoma Japan

ISBN: (纸本)9781728112411

pseudo-code written in natural language and mathematical expressions is a useful description of source code. pseudocode aids programmers in understanding the code written in a programming language they are not familiar with. However, writing pseudo-code for each code statement is labour intensive. In this paper, we propose a novel approach to automatically generate pseudo-code from source code using Neural Machine Translation. Our model is built upon the deep learning encoder-decoder using the attention-based Long Short-Term Memory architecture to capture the long-term dependencies in both source code and pseudo-code. An empirical evaluation on a real Python dataset demonstrates the applicability of our approach in practice.

关键词： pseudo-code encoder-decoder seq2seq documentation lstm

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Approach to Convert pseudo-code to Domain-Specific Programming Language 39

A Machine Learning Approach to Convert Pseudo-Code to Domain...

引用

39th IEEE International Conference on Software Maintenance and Evolution (ICSME)

作者： Neal, Jacob Rogers, Shane Parra, Esteban Binary Evolut Fayetteville TN 72701 USA Belmont Univ Dept Math & Comp Sci Nashville TN 37212 USA

ISBN: (纸本)9798350327830

The California Department of Energy oversees a set of standards and rules that new constructions (i.e., buildings) must adhere to within the State of California (the California Energy code). Energy code Ace (ECA) is a website that helps users plan their future construction in California and see if the plans for their structure comply with the California Energy code. However, there are thousands of details and sections in the California Energy code that need to be translated into questions and fields on the website for the user to fill out. To do this, the Department of Energy provides a web development team at Binary Evolution with XML schematics that contain details of each field and pseudo-code of the logic that fields should follow compared to the other fields on the ECA website. A very large portion of the developers' job involves reading the pseudo-code and writing real code in a language developed by Binary Evolution. Reading and handwriting the code as described in the schematics can take up to hours of a developer's time. This paper presents ECAi, a new approach for automatically generating executable code from pseudo-code schematics. ECAi uses a Decision Tree Classifier trained on 23,864 lines of pseudo-code and had to classify a line of pseudo-code into one of 13 categories achieving an 89.87% F1-score. Leveraging the classifier category, ECAi then calls a code-writing algorithm to parse the line of pseudo-code and writes the executable code that corresponds with the given pseudo-code line. The implementation of a prototype of the system shows a statistically significant (p=0.0116) decrease in the time it takes a developer to obtain an executable piece of code. ECAi has saved countless hours of development work during the maintenance workflow of ECA.

关键词： automatic code generation pseudo-code machine learning

来源：评论

学校读者我要写书评

暂无评论

An XML-based pseudo-code Online Editing and Conversion System

An XML-based Pseudo-code Online Editing and Conversion Syste...

引用

2011 13th IEEE Joint International Computer Science and Information Technology Conference(JICSIT 2011)

作者： Liu Haowen Computer School of Wuhan University Wuhan, China Li Wei, Long Yin Computer School of Wuhan University Wuhan, China

The present researchers urgently need a network tool that is able to edit pseudo-code and convert it into source code on-line. This paper puts forward an XML-based pseudo- code online editing and conversion system. The pseudo-code is described and saved with XML document which is analyzed and parsed by DOM4J, so as to realize the reuse of pseudo- code and source code.

关键词： pseudo-code editing conversion XML DOM4J

来源：评论

学校读者我要写书评

暂无评论

Design of pseudo-code CW RVD Radar Signal Processor

Design of Pseudo-code CW RVD Radar Signal Processor

引用

ICEMI'2005第七届国际电子测量与仪器学术会议

作者： Geng Shengqun Wu Siliang ( Beijing Institute of Technology, Beijing 100081 China )

In this paper, the design of a pseudo-code CW Rendezvous and Docking (RVD) radar signal processor is presented. The system is made of radar and transponder, radar transmits spread-spectrum signal modu

关键词： Radar pseudo-code rendezvous and docking.

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：