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  1. Transactions on Software Engineering and Methodology (TOSEM)
  2. ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 23
  3. Issue 4(Special Issue International Conference on Software Engineering (ICSE 2012) and Regular Papers), August 2014
  4. DIG: A Dynamic Invariant Generator for Polynomial and Array Invariants
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ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 25
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 24
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 23
Issue 4(Special Issue International Conference on Software Engineering (ICSE 2012) and Regular Papers), August 2014
Some Code Smells Have a Significant but Small Effect on Faults
Scaling Up Symbolic Analysis by Removing Z-Equivalent States
Peer Review on Open-Source Software Projects: Parameters, Statistical Models, and Theory
Editorial
Introduction to the Special Issue International Conference on Software Engineering (ICSE 2012)
Automated Detection of Client-State Manipulation Vulnerabilities
DIG: A Dynamic Invariant Generator for Polynomial and Array Invariants
On the Comprehension of Program Comprehension
Amplifying Tests to Validate Exception Handling Code: An Extended Study in the Mobile Application Domain
Issue 3, May 2014
Issue 2, March 2014
Issue 1, February 2014
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 22
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 21
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 20
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 19
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 18
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 17
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 16
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 15
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 14
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 13
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 12
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 11
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 10
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 9
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 8
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 7
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 6
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 5
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 4
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 3
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 2
ACM Transactions on Software Engineering and Methodology (TOSEM) : Volume 1

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DIG: A Dynamic Invariant Generator for Polynomial and Array Invariants

Content Provider ACM Digital Library
Author Weimer, Westley Nguyen, Thanhvu Forrest, Stephanie Kapur, Deepak
Copyright Year 2014
Abstract This article describes and evaluates DIG, a dynamic invariant generator that infers invariants from observed program traces, focusing on numerical and array variables. For numerical invariants, DIG supports both nonlinear equalities and inequalities of arbitrary degree defined over numerical program variables. For array invariants, DIG generates nested relations among multidimensional array variables. These properties are nontrivial and challenging for current static and dynamic invariant analysis methods. The key difference between DIG and existing dynamic methods is its generative technique, which infers invariants directly from traces, instead of using traces to filter out predefined templates. To generate accurate invariants, DIG employs ideas and tools from the mathematical and formal methods domains, including equation solving, polyhedra construction, and theorem proving; for example, DIG represents and reasons about polynomial invariants using geometric shapes. Experimental results on 27 mathematical algorithms and an implementation of AES encryption provide evidence that DIG is effective at generating invariants for these programs.
Starting Page 1
Ending Page 30
Page Count 30
File Format PDF
ISSN 1049331X
e-ISSN 15577392
DOI 10.1145/2556782
Volume Number 23
Issue Number 4
Journal ACM Transactions on Software Engineering and Methodology (TOSEM)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-09-05
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Program analysis Array invariants Dynamic analysis Geometric invariant inference Invariant generation Nonlinear invariants Theorem proving
Content Type Text
Resource Type Article
Subject Software
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