Loop Invariant Synthesis in a Combined Domain

Science of Computer Programming

Luo

et al. 2014

Self Cite

Automatically verifying heap-manipulating programs is a challenging task, especially when dealing with complex data structures with strong invariants, such as sorted lists and AVL/red-black trees. The verification process can greatly benefit from human assistance through specification annotations, but this process requires intellectual effort from users and is error-prone. In this paper, we propose a new approach to program verification that allows users to provide only partial specification to methods. Our approach will then refine the given annotation into a more complete specification by discovering missing constraints. The discovered constraints may involve both numerical and multi-set properties that could be later confirmed or revised by users. We further augment our approach by requiring partial specification to be given only for primary methods. Specifications for loops and auxiliary methods can then be systematically discovered by our augmented mechanism, with the help of information propagated from the primary methods. Our work is aimed at verifying beyond shape properties, with the eventual goal of analysing full functional properties for pointer-based data structures. Initial experiments have confirmed that we can automatically refine partial specifications with non-trivial constraints, thus making it easier for users to handle specifications with richer properties.

Section: Refining Specifications For Primary Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Automatically refining partial specifications for heap-manipulating programs

Science of Computer Programming

Luo

et al. 2014

Self Cite

“…Relational inductive shape analysis [6] employs inductive checkers to express shape and numerical information, where they only demonstrate how to analyse a program with one particular shape. Our previous loop invariant synthesis [26] also infers strong loop invariants. Compared with them, this work is inter-procedural and addresses specification refinement with pure properties in both pre-and postconditions in two phases (for shape and pure resp.)…”

Section: Related Work and Conclusionmentioning

confidence: 99%

Automatically Refining Partial Specifications for Program Verification

Lecture Notes in Computer Science

Luo

Chin

et al. 2011

Self Cite

When citing this source, please use the final published version as above.This document was downloaded from http://tees.openrepository.com/tees/handle/10149/141501 Please do not use this version for citation purposes.All items in TeesRep are protected by copyright, with all rights reserved, unless otherwise indicated. Abstract. Automatically verifying heap-manipulating programs is a challenging task, especially when dealing with complex data structures with strong invariants, such as sorted lists and AVL/red-black trees. The verification process can greatly benefit from human assistance through specification annotations, but this process requires intellectual effort from users and is error-prone. In this paper, we propose a new approach to program verification that allows users to provide only partial specification to methods. Our approach will then refine the given annotation into a more complete specification by discovering missing constraints. The discovered constraints may involve both numerical and multi-set properties that could be later confirmed or revised by users. We further augment our approach by requiring only partial specification to be given for primary methods. Specifications for loops and auxiliary methods can then be systematically discovered by our augmented mechanism, with the help of information propagated from the primary methods. Our work is aimed at verifying beyond shape properties, with the eventual goal of analysing full functional properties for pointer-based data structures. Initial experiments have confirmed that we can automatically refine partial specifications with non-trivial constraints, thus making it easier for users to handle specifications with richer properties.

“…Although the specifications written so far have been supplied by us, recent developments [25,26,28,27] in Hip/Sleek will allow the automatic inference of properties, making our approach more scalable.…”

Section: Future Workmentioning

confidence: 99%

Automated Verification of the FreeRTOS Scheduler in HIP/SLEEK

Ferreira

2012 Sixth International Symposium on Theoretical Aspects of Software Engineering

2012

Self Cite

Automated verification of operating system kernels is a challenging problem, partly due to the use of shared mutable data structures. In this paper, we show how we can automatically verify memory safety and functional correctness properties of the task scheduler component of the FreeRTOS kernel using the verification system Hip/Sleek. We show how some of Hip/Sleek features like user-defined predicates and lemmas make the specifications highly expressive and the verification process viable. To the best of our knowledge, this is the first code-level verification of memory safety and functional correctness properties of the FreeRTOS scheduler. The outcome of our experiment confirms that Hip/Sleek can indeed be used to verify code that is used in production. Moreover, since the properties that we verify are quite general, we envisage that the same approach can be adopted to verify components of other operating systems.