Alain Josué Ratovondrahona, Hanitriniaina Marielle Rakotozanany, Thomas Mahatody, Victor Manantsoa
{"title":"Human like programming using SPADE BDI agents and the GPT-3-based Transformer","authors":"Alain Josué Ratovondrahona, Hanitriniaina Marielle Rakotozanany, Thomas Mahatody, Victor Manantsoa","doi":"10.54941/ahfe1002939","DOIUrl":null,"url":null,"abstract":"Programming an application requires multiple people with skills and experience in\n that field. It will also take a lot of time with multiple steps before achieving the\n final result of an application. Today, developers are assisted by various tools,\n software, or applications based on Artificial Intelligence (AI) such as OpenAI's\n ChatGPT. These AI that automatically generates source code helps developers to develop\n applications much faster. However, although code generators are numerous and very\n helpful, we are not yet at the stage where we can generate a fully functional\n application, but just generate pieces of source code. And we don’t know yet how to\n understand textual descriptions of Software Requirements to generate an application\n directly. Or where to find data to train an AI capable of generating a functional\n application from textual descriptions. Therefore, we created a new architecture composed\n of virtual intelligent agents called SPADE BDI to create virtual developers. The virtual\n intelligent agents were responsible for keyword extraction, Software Requirements\n synthesis, and source file creation. Then we used a transformer based on pre-trained\n GPT-3 for source code generation. This transformer is orchestrated by a virtual\n intelligent agent. To solve the problem of training data, we collected and created a new\n dataset called WSBL. The data came from several projects developed with the Laravel\n Framework over 4 years. The result allowed us to have a functional application directly\n from a textual description. Each intelligent virtual agent played a role like a\n developer by analyzing textual of Software Requirements and then generating source code.\n With a 15% reduction in time to develop an application compared to brute development.\n Our new architecture allows for processing textual descriptions (Software Requirements)\n step by step using intelligent virtual agents named SPADE BDI and source code generation\n is done by a transformer based on pre-trained GPT-3 to have a directly functional\n application","PeriodicalId":383834,"journal":{"name":"Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial\n Intelligence and Future Applications","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial\n Intelligence and Future Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1002939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Programming an application requires multiple people with skills and experience in
that field. It will also take a lot of time with multiple steps before achieving the
final result of an application. Today, developers are assisted by various tools,
software, or applications based on Artificial Intelligence (AI) such as OpenAI's
ChatGPT. These AI that automatically generates source code helps developers to develop
applications much faster. However, although code generators are numerous and very
helpful, we are not yet at the stage where we can generate a fully functional
application, but just generate pieces of source code. And we don’t know yet how to
understand textual descriptions of Software Requirements to generate an application
directly. Or where to find data to train an AI capable of generating a functional
application from textual descriptions. Therefore, we created a new architecture composed
of virtual intelligent agents called SPADE BDI to create virtual developers. The virtual
intelligent agents were responsible for keyword extraction, Software Requirements
synthesis, and source file creation. Then we used a transformer based on pre-trained
GPT-3 for source code generation. This transformer is orchestrated by a virtual
intelligent agent. To solve the problem of training data, we collected and created a new
dataset called WSBL. The data came from several projects developed with the Laravel
Framework over 4 years. The result allowed us to have a functional application directly
from a textual description. Each intelligent virtual agent played a role like a
developer by analyzing textual of Software Requirements and then generating source code.
With a 15% reduction in time to develop an application compared to brute development.
Our new architecture allows for processing textual descriptions (Software Requirements)
step by step using intelligent virtual agents named SPADE BDI and source code generation
is done by a transformer based on pre-trained GPT-3 to have a directly functional
application