Termination Analysis by Learning Terminating Programs
Not on the map. Why?
Abstract (arXiv)
We present a novel approach to termination analysis. In a first step, the analysis uses a program as a black-box which exhibits only a finite set of sample traces. Each sample trace is infinite but can be represented by a finite lasso. The analysis can "learn" a program from a termination proof for the lasso, a program that is terminating by construction. In a second step, the analysis checks that the set of sample traces is representative in a sense that we can make formal. An experimental evaluation indicates that the approach is a potentially useful addition to the portfolio of existing approaches to termination analysis.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 May 2014.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 4; 2022: 4; 2023: 1.
9 papers.
- 2021Neural Termination Analysiscited by 16
- 2021SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysiscited by 0
- 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Searchcited by 0
- 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generationcited by 0
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectorscited by 0
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networkscited by 0
- 2022Explanation-Guided Fairness Testing through Genetic Algorithmcited by 0
- 2022Using Graph Neural Networks for Program Terminationcited by 0
- 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGramcited by 0
- 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGram16 Mar 2023
- 2022Using Graph Neural Networks for Program Termination28 Jul 2022
- 2022Explanation-Guided Fairness Testing through Genetic Algorithm16 May 2022
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks8 Mar 2022
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors6 Feb 2022
- 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generation13 Sep 2021
- 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Search5 Aug 2021
- 2021SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysis3 Aug 2021
- 2021Neural Termination Analysis7 Feb 2021