Continuous Reasoning: Scaling the Impact of Formal Methods

July 9, 2018

Abstract

This paper describes work in continuous reasoning, where formal reasoning about a (changing) codebase is done in a fashion which mirrors the iterative, continuous model of software development that is increasingly practiced in industry. We suggest that advances in continuous reasoning will allow formal reasoning to scale to more programs, and more programmers. The paper describes the rationale for continuous reasoning, outlines some success cases from within industry, and proposes directions for work by the scientific community.

Download the Paper

AUTHORS

Written by

Peter O'Hearn

Publisher

Logic in Computer Science

Related Publications

February 27, 2025

Integrity

Theory

Logic.py: Bridging the Gap between LLMs and Constraint Solvers

Pascal Kesseli, Peter O'Hearn, Ricardo Silveira Cabral

February 27, 2025

Read the Paper

April 08, 2021

Responsible AI

Integrity

Towards measuring fairness in AI: the Casual Conversations dataset

Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton Ferrer

April 08, 2021

Read the Paper

February 07, 2020

Integrity

Generate, Segment and Refine: Towards Generic Manipulation Segmentation | Facebook AI Research

Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser-Nam Lim, Larry S. Davis

February 07, 2020

Read the Paper

February 24, 2018

Speech & Audio

Computer Vision

Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective | Facebook AI Research

Kim Hazelwood, Sarah Bird, David Brooks, Soumith Chintala, Utku Diril, Dmytro Dzhulgakov, Mohamed Fawzy, Bill Jia, Yangqing Jia, Aditya Kalro, James Law, Kevin Lee, Jason Lu, Pieter Noordhuis, Misha Smelyanskiy, Liang Xiong, Xiaodong Wang

February 24, 2018

Read the Paper

April 30, 2018