Programming from specifications (2nd ed.)
Programming from specifications (2nd ed.)
Object-oriented software construction (2nd ed.)
Object-oriented software construction (2nd ed.)
Dynamically Discovering Likely Program Invariants to Support Program Evolution
IEEE Transactions on Software Engineering - Special issue on 1999 international conference on software engineering
Extended static checking for Java
PLDI '02 Proceedings of the ACM SIGPLAN 2002 Conference on Programming language design and implementation
Automatic discovery of linear restraints among variables of a program
POPL '78 Proceedings of the 5th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
POPL '77 Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
The Science of Programming
A Discipline of Programming
Houdini, an Annotation Assistant for ESC/Java
FME '01 Proceedings of the International Symposium of Formal Methods Europe on Formal Methods for Increasing Software Productivity
A static analyzer for large safety-critical software
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Non-linear loop invariant generation using Gröbner bases
Proceedings of the 31st ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Efficient incremental algorithms for dynamic detection of likely invariants
Proceedings of the 12th ACM SIGSOFT twelfth international symposium on Foundations of software engineering
Generating all polynomial invariants in simple loops
Journal of Symbolic Computation
DySy: dynamic symbolic execution for invariant inference
Proceedings of the 30th international conference on Software engineering
HOL-Boogie -- An Interactive Prover for the Boogie Program-Verifier
TPHOLs '08 Proceedings of the 21st International Conference on Theorem Proving in Higher Order Logics
Reasoning about comprehensions with first-order SMT solvers
Proceedings of the 2009 ACM symposium on Applied Computing
Touch of Class: Learning to Program Well with Objects and Contracts
Touch of Class: Learning to Program Well with Objects and Contracts
Finding Loop Invariants for Programs over Arrays Using a Theorem Prover
FASE '09 Proceedings of the 12th International Conference on Fundamental Approaches to Software Engineering: Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2009
A comparative study of programmer-written and automatically inferred contracts
Proceedings of the eighteenth international symposium on Software testing and analysis
Automatic Verification of Integer Array Programs
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
Invariant synthesis for combined theories
VMCAI'07 Proceedings of the 8th international conference on Verification, model checking, and abstract interpretation
The Why/Krakatoa/Caduceus platform for deductive program verification
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Invariant and type inference for matrices
VMCAI'10 Proceedings of the 11th international conference on Verification, Model Checking, and Abstract Interpretation
Abstract interpretation with alien expressions and heap structures
VMCAI'05 Proceedings of the 6th international conference on Verification, Model Checking, and Abstract Interpretation
What's decidable about arrays?
VMCAI'06 Proceedings of the 7th international conference on Verification, Model Checking, and Abstract Interpretation
Proceedings of the 33rd International Conference on Software Engineering
Loop invariants: Analysis, classification, and examples
ACM Computing Surveys (CSUR)
Verifying while loops with invariant relations
International Journal of Critical Computer-Based Systems
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One of the obstacles in automatic program proving is to obtain suitable loop invariants. The invariant of a loop is a weakened form of its postcondition (the loop's goal, also known as its contract); the present work takes advantage of this observation by using the postcondition as the basis for invariant inference, using various heuristics such as "uncoupling" which prove useful in many important algorithms. Thanks to these heuristics, the technique is able to infer invariants for a large variety of loop examples. We present the theory behind the technique, its implementation (freely available for download and currently relying on Microsoft Research's Boogie tool), and the results obtained.