The Use of Natural Language Processing Approach for Converting Pseudo Code to C# Code

Imam, Ayad Tareq; Alnsour, Ayman Jameel

doi:10.2139/ssrn.3463701

Cited by 1 publication

(2 citation statements)

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“…Accuracy (%) Error rate (%) Search-based Process [13] 44.7 55.3 Semantic Scaffolds Method [15] 55.1 44.9 Natural Language Processing Approach [16] 72.8 27.2 Conceptual-Metamodel Mechanism [20] 76. 6 represents BLEU portion of efficiency for predicting the correct source code.…”

Section: Methodsmentioning

confidence: 99%

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Sequence-to-Sequence Learning-Based Conversion of Pseudo-Code to Source Code Using Neural Translation Approach

et al. 2022

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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 stateof-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.

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Section: Methodsmentioning

confidence: 99%

“…Imam and Alnsour [16] proposed an automated translation system emphasizing Natural Language Processing (NLP) to translate the programming language from the pseudocode. This hybrid approach (Code-Composer) [17] can compose the language automatically by transforming pseudocode into the Cprogramming language.…”

Section: Literature Reviewmentioning

confidence: 99%