1993
DOI: 10.1007/3-540-57209-0_33
|View full text |Cite
|
Sign up to set email alerts
|

Assertion-based debugging of imperative programs by abstract interpretation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

1999
1999
2010
2010

Publication Types

Select...
3
1
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(3 citation statements)
references
References 11 publications
0
3
0
Order By: Relevance
“…One use has been to calculate possible values for variables at different program points. This information can for example be used in a "static debugger" [6] which identifies (the risk of) array indices lying outside array ranges, and other possible errors in the analysed program. This idea has been further developed and commercialised under the name PolySpace [29].…”
Section: Classical Abstract Interpretationmentioning
confidence: 99%
See 1 more Smart Citation
“…One use has been to calculate possible values for variables at different program points. This information can for example be used in a "static debugger" [6] which identifies (the risk of) array indices lying outside array ranges, and other possible errors in the analysed program. This idea has been further developed and commercialised under the name PolySpace [29].…”
Section: Classical Abstract Interpretationmentioning
confidence: 99%
“…buf [5] buf [6] buf [3] buf [4] buf [2] buf[0] buf [1] arr [0] arr [2] arr [1] arr [ (e) Abstract memory and environment…”
Section: (C) Corresponding Nic Code Fragmentmentioning
confidence: 99%
“…The applications we have in mind are automated debugging [4,14] or automatic test selection [25], which may require precise and complex analyses. These are flow-sensitive (the analysis needs to take conditionals into account accurately), attribute-dependent (attributes (or properties) of variables are inter-related), and may require the use of infinite or even infinite-height lattices, in particular for the analysis of the properties numerical variables.…”
Section: Introductionmentioning
confidence: 99%