[2508.05199] EvoGraph: Hybrid Directed Graph Evolution toward Software 3.0

-->

Computer Science > Software Engineering

arXiv:2508.05199 (cs)

[Submitted on 7 Aug 2025]

Title:EvoGraph: Hybrid Directed Graph Evolution toward Software 3.0

Authors:Igor Costa, Christopher Baran<br>View a PDF of the paper titled EvoGraph: Hybrid Directed Graph Evolution toward Software 3.0, by Igor Costa and 1 other authors

View PDF<br>HTML (experimental)

Abstract:We introduce **EvoGraph**, a framework that enables software systems to evolve their own source code, build pipelines, documentation, and tickets. EvoGraph represents every artefact in a typed directed graph, applies learned mutation operators driven by specialized small language models (SLMs), and selects survivors with a multi-objective fitness. On three benchmarks, EvoGraph fixes 83% of known security vulnerabilities, translates COBOL to Java with 93% functional equivalence (test verified), and maintains documentation freshness within two minutes. Experiments show a 40% latency reduction and a sevenfold drop in feature lead time compared with strong baselines. We extend our approach to **evoGraph**, leveraging language-specific SLMs for modernizing .NET, Lisp, CGI, ColdFusion, legacy Python, and C codebases, achieving 82-96% semantic equivalence across languages while reducing computational costs by 90% compared to large language models. EvoGraph's design responds to empirical failure modes in legacy modernization, such as implicit contracts, performance preservation, and integration evolution. Our results suggest a practical path toward Software 3.0, where systems adapt continuously yet remain under measurable control.

Comments:<br>15 pages, 3 tables, 1 algorithm. Submitted to ICSE 2025

Subjects:

Software Engineering (cs.SE); Artificial Intelligence (cs.AI)

ACM classes:<br>D.2.2; D.2.7; I.2.2

Cite as:<br>arXiv:2508.05199 [cs.SE]

(or<br>arXiv:2508.05199v1 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2508.05199

Focus to learn more

arXiv-issued DOI via DataCite

Submission history<br>From: Igor Petronio Costa [view email]<br>[v1]<br>Thu, 7 Aug 2025 09:36:30 UTC (105 KB)

Full-text links:<br>Access Paper:

View a PDF of the paper titled EvoGraph: Hybrid Directed Graph Evolution toward Software 3.0, by Igor Costa and 1 other authors<br>View PDF<br>HTML (experimental)<br>TeX Source

view license

Current browse context:

cs.SE

next >

new<br>recent<br>| 2025-08

Change to browse by:

cs<br>cs.AI

References & Citations

NASA ADS<br>Google Scholar

Semantic Scholar

export BibTeX citation<br>Loading...

BibTeX formatted citation

&times;

loading...

Data provided by:

Bookmark

Bibliographic Tools

Bibliographic and Citation Tools

Bibliographic Explorer Toggle

Bibliographic Explorer (What is the Explorer?)

Connected Papers Toggle

Connected Papers (What is Connected Papers?)

Litmaps Toggle

Litmaps (What is Litmaps?)

scite.ai Toggle

scite Smart Citations (What are Smart Citations?)

Code, Data, Media

Code, Data and Media Associated with this Article

alphaXiv Toggle

alphaXiv (What is alphaXiv?)

Links to Code Toggle

CatalyzeX Code Finder for Papers (What is CatalyzeX?)

DagsHub Toggle

DagsHub (What is DagsHub?)

GotitPub Toggle

Gotit.pub (What is GotitPub?)

Huggingface Toggle

Hugging Face (What is Huggingface?)

ScienceCast Toggle

ScienceCast (What is ScienceCast?)

Demos

Demos

Replicate Toggle

Replicate (What is Replicate?)

Spaces Toggle

Hugging Face Spaces (What is Spaces?)

Spaces Toggle

TXYZ.AI (What is TXYZ.AI?)

Related Papers

Recommenders and Search Tools

Link to Influence Flower

Influence Flower (What are Influence Flowers?)

Core recommender toggle

CORE Recommender (What is CORE?)

Author

Venue

Institution

Topic

About arXivLabs

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

Which authors of this paper are endorsers? |<br>Disable MathJax (What is MathJax?)