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Autonomous Agents in Software Development : A Vision Paper

Publiceringsår

2025

Upphovspersoner

Rasheed, Zeeshan; Waseem, Muhammad; Sami, Malik Abdul; Kemell, Kai-Kristian; Ahmad, Aakash; Duc, Anh Nguyen; Systä, Kari; Abrahamsson, Pekka

Abstrakt

Large Language Models (LLM) are reshaping the field of Software Engineering (SE). They enable innovative methods for executing many SE tasks, including automation of entire process of Software Development Life Cycle (SDLC). However, only a limited number of existing works have thoroughly explored the potential of LLM based AI agents to automate the entire lifecycle in SE. In this paper, we demonstrate the success of our initial efforts in automating the entire lifecycle autonomously based on given software specification as input, which has shown remarkable efficiency and significantly reduced development time. Our preliminary results suggest that the careful implementation of AI agents can enhance the development lifecycle. We aim to streamline the SDLC by integrating all phases into an AI-driven chat interface, enhancing efficiency and transparency. Furthermore, we seek to enhance collaboration, creating an environment where stakeholders from various backgrounds can contribute, review, and refine ideas and requirements in real-time. This forward-looking direction guarantees to redefine the paradigms of SE and also make software creation more inclusive, collaborative, and efficient.
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Organisationer och upphovspersoner

Jyväskylä universitet

Waseem Muhammad Orcid -palvelun logo

Publikationstyp

Publikationsform

Artikel

Moderpublikationens typ

Konferens

Artikelstyp

Annan artikel

Målgrupp

Vetenskaplig

Kollegialt utvärderad

Kollegialt utvärderad

UKM:s publikationstyp

A4 Artikel i en konferenspublikation

Öppen tillgång

Öppen tillgänglighet i förläggarens tjänst

Ja

Öppen tillgång till publikationskanalen

Helt öppen publikationskanal

Parallellsparad

Ja

Övriga uppgifter

Vetenskapsområden

Data- och informationsvetenskap

Nyckelord

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Publiceringsland

Schweiz

Förlagets internationalitet

Internationell

Språk

engelska

Internationell sampublikation

Ja

Sampublikation med ett företag

Nej

DOI

10.1007/978-3-031-72781-8_2

Publikationen ingår i undervisnings- och kulturministeriets datainsamling

Ja