Semi natural language algorithm to programming language interpreter

Nadkarni, Sharvari; Panchmatia, Parth; Karwa, Tejas; Kurhade, Swapnali

doi:10.1109/hmi.2016.7449190

Cited by 7 publications

(2 citation statements)

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“…It is used with the KBMT and LBMT. This approach was used (partially) to develop an interpreter for converting algorithms written in natural English language to C code [35]. As we noted, the previous works based on this approach did not consider verb classification, thematic role, and SRL -the advanced topics of natural language semantic processing.…”

Section: Related Approaches and Workmentioning

confidence: 99%

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

Imam

Alnsour

2019

Journal of Intelligent Systems

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AbstractAlthough current computer-aided software engineering tools support developers in composing a program, there is no doubt that more flexible supportive tools are needed to address the increases in the complexity of programs. This need can be met by automating the intellectual activities that are carried out by humans when composing a program. This paper aims to automate the composition of a programming language code from pseudocode, which is viewed here as a translation process for a natural language text, as pseudocode is a formatted text in natural English language. Based on this view, a new automatic code generator is developed that can convert pseudocode to C# programming language code. This new automatic code generator (ACG), which is called CodeComposer, uses natural language processing (NLP) techniques such as verb classification, thematic roles, and semantic role labeling (SRL) to analyze the pseudocode. The resulting analysis of linguistic information from these techniques is used by a semantic rule-based mapping machine to perform the composition process. CodeComposer can be viewed as an intelligent computer-aided software engineering (I_CASE) tool. An evaluation of the accuracy of CodeComposer using a binomial technique shows that it has a precision of 88%, a recall of 91%, and an F-measure of 89%.

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Section: Related Approaches and Workmentioning

confidence: 99%

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

Imam

Alnsour

2019

Journal of Intelligent Systems

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“…Check each Keyword if exits in the database then take the keyword else print the keyword in output textbox. 1…”

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confidence: 99%

Online Algorithm Converter for C++.

Patil.¹

2017

IJAR

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The first step in problem solving is to develop a foolproof algorithm for the same. This algorithm encompasses of the central logic that will be used to solve the problem. The logical steps that are followed while writing an algorithm play an integral part in the development of a coherent solution. Writing a correct algorithm ensures an efficient code which results in optimum utilization of resources. In order to develop a student's problem solving skills, the logical correctness of an algorithm is more important than the actual implementation. The aim of this paper is to develop a web-based application into which a student or novice programmer can enter an algorithm and get an equivalent C language code for the same. Various Natural Language Processing (NLP) constructs will be used for the same. The user will be able to focus on the logic of the solution without having to worry about the syntax. The application will also provide the facility of running the converted code using a GCC compiler to check for its correctness in terms of syntax and logic. It will be designed as a tool for learning the basics of problem-solving and leveraging those skills.Copy Right, IJAR, 2017,. All rights reserved. …………………………………………………………………………………………………….... Introduction:-With the growing complexity of computer science problems that are used in real-world applications, it is essential for students to learn how to develop their logic for effective problem solving first without having to focus on the syntax and constraints of programming languages. Students have difficulties in abstracting the problem from its description and breaking it down into sub-problems. There are several learning tools available online, but all of them focus on various programming languages without actually focusing on how a problem can be solved by using various techniques. The motivation behind this paper is to allow students first to be able to clear their logic, work on their problem-solving skills and then perfect the art of writing code. The aim is to create a web-based application which takes any algorithm written in plain English and converts that algorithm into a syntactically correct code. This can be done using natural language processing. Techniques like parts-of-speech recognition, tagging, labeling and tokenizing are used to capture the essence of the algorithm. The tagged keywords are then arranged in a syntactically correct format by the system, thus generating the final code. The proposed system also comes with a compiler which compiles the generated C-code and displays the output on the console. This paper is aimed at developing the logic of students who are just introduced to various problems in Computer Science. The ease of understanding, combined with the easy to use user interface makes this application an efficient learning tool. It overcomes the various drawbacks of the pre-existing systems and hence is very useful. The flow of conventional problem-solving techniques is shown in figure 1.

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Text to Code: Pseudo Code Generation

Din

Adnan

2019

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Semi natural language algorithm to programming language interpreter

Cited by 7 publications

References 4 publications

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

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

Online Algorithm Converter for C++.

Text to Code: Pseudo Code Generation

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