2010
DOI: 10.1007/978-3-642-16242-8_16
|View full text |Cite
|
Sign up to set email alerts
|

Lazy Abstraction for Size-Change Termination

Abstract: Abstract. Size-change termination is a widely used means of proving termination where source programs are first abstracted to size-change graphs which are then analyzed to determine if they satisfy the sizechange termination property. Here, the choice of the abstraction is crucial to the success of the method, and it is an open problem how to choose an abstraction such that no critical loss of precision occurs. This paper shows how to couple the search for a suitable abstraction and the test for size-change te… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2010
2010
2018
2018

Publication Types

Select...
4
2
1

Relationship

1
6

Authors

Journals

citations
Cited by 10 publications
(2 citation statements)
references
References 30 publications
0
2
0
Order By: Relevance
“…Concerning the individual techniques, currently CPF supports several classes of reduction orders (in alphabetical order): argument filters [2], matrix orders [9], polynomial orders over several carriers [18,20,22], recursive path orders [7], the Knuth-Bendix order [17], and SCNP reduction orders [5]. Moreover, the techniques of dependency graph decomposition [2], dependency pairs [2,13], dependency pair transformations (instantiation, narrowing, rewriting) [2,13], loops, non-looping nontermination [8], matchbounds [11], root-labeling [23], rule removal [15,20], semantic labeling and unlabeling [33], sizechange termination [21,26], string reversal, the subterm criterion [15], switching to innermost termination [14], uncurrying [16,24], and usable rules [2,13,28] are supported.…”
Section: Split the Input Trsmentioning
confidence: 99%
“…Concerning the individual techniques, currently CPF supports several classes of reduction orders (in alphabetical order): argument filters [2], matrix orders [9], polynomial orders over several carriers [18,20,22], recursive path orders [7], the Knuth-Bendix order [17], and SCNP reduction orders [5]. Moreover, the techniques of dependency graph decomposition [2], dependency pairs [2,13], dependency pair transformations (instantiation, narrowing, rewriting) [2,13], loops, non-looping nontermination [8], matchbounds [11], root-labeling [23], rule removal [15,20], semantic labeling and unlabeling [33], sizechange termination [21,26], string reversal, the subterm criterion [15], switching to innermost termination [14], uncurrying [16,24], and usable rules [2,13,28] are supported.…”
Section: Split the Input Trsmentioning
confidence: 99%
“…We mention two of the directions taken. [42,41,7,62] employ the dependency pair method, which like the model we are studying, was originally conceived for termination, and in fact has been effectively combined with size-change termination [67,35,25].…”
Section: Approaches In Complexity Analysismentioning
confidence: 99%