[2209.01803] Detecting unanticipated mutual recursion using Elegant Objects representation of object-oriented programs
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Programming Languages

arXiv:2209.01803 (cs)
[Submitted on 5 Sep 2022]

Title:Detecting unanticipated mutual recursion using Elegant Objects representation of object-oriented programs

Authors:Nikolai Kudasov, Mikhail Olokin, Oleksii Potyomkin, Nikolay Shilov, Maxim Stepanov
View PDF
Abstract:Elegant Objects (EO) is a variation of the object-oriented programming paradigm that favors pure objects and decoration. EO programming language is based on these ideas and has been suggested by Bugayenko as an intermediate representation for object-oriented programs. This paper provides plausible representations in EO of some class-based constructions from Java, C++, and Python. We then reformulate the classical fragile base class problem in the context of these representations. Finally, we discuss an algorithm for detecting a subset of fragile base class patterns in EO programs. We show that using EO as an intermediate language is plausible and discuss possible improvements to the language to assist in richer static analysis.
Subjects: Programming Languages (cs.PL)
Cite as: arXiv:2209.01803 [cs.PL]
  (or arXiv:2209.01803v1 [cs.PL] for this version)
  https://doi.org/10.48550/arXiv.2209.01803

Submission history

From: Nikolai Kudasov [view email]
[v1] Mon, 5 Sep 2022 07:32:15 UTC (99 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
license icon view license
Current browse context:
cs.PL
< prev   |   next >
new | recent | 2022-09
Change to browse by:
cs

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

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? | Disable MathJax (What is MathJax?)