Adoption and focus

FähndrichManuel,; DeLineRobert,

doi:10.1145/543552.512532

Cited by 26 publications

(2 citation statements)

References 21 publications

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“…Dynamic Buffer Overflow Detection [30] surveys some tools in this category including Valgrind [21], CCured [20], CRED [26], ProPolice [15], StackGuard [10], TinyCC [27], Chaperon, and Insure++. Safe Systems Programming Languages [19] surveys SafeC [4], CCured [20], Vault [13,16], and Cyclone [18].…”

Section: Related Workmentioning

confidence: 99%

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Using Pit to improve security in low-level programs

Pedersen

Reza

2009

J Supercomput

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Pit (Pedersen on http://pit.devpit.org, 2008; Pedersen and Reza in ISOLA '06: proceedings of the second international symposium on leveraging applications of formal methods, verification and validation (ISOLA 2006(ISOLA ), pp. 111-118, 2006) is a new language for low-level programming, designed to be a self-hosting alternative to C. The novelty is that it supports automated memory management without excluding manual memory management, and without hindering key features associated with low-level programming, such as raw pointers, inline assembly code, and precise control over execution.This paper presents Pit as a language, and then examines how Pit's approach to memory allocation can be used to significantly increase the security of low-level programs. Automatic memory allocation is a useful tool of abstraction in many situations. Since Pit provides this tool without hindering low-level programming, it allows automated memory management to be used in programs where it previously could not be used, such as kernels. Specifically, this tool of abstraction can assist the programmer significantly in writing low-level code with fewer security problems caused by buffer overrun or integer overflow bugs by reducing the number of opportunities for such bugs in areas of code that do not need the precision of manual memory allocation. Existing solutions, such as Cyclone (Jim et al. in ATEC '02: proceedings of the general track: USENIX annual technical conference, pp. [275][276][277][278][279][280][281][282][283][284][285][286][287][288] 2002), add various ways of checking bounds, but have two major disadvantages: they require extra work from the programmer, and they detect but do not fix memory allocation bugs. Pit's approach simplifies what the programmer writes, making the code more understandable.

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Section: Related Workmentioning

confidence: 99%

“…Vault [13,16] is an entirely new language that does not support pointer arithmetic, which makes it unsuitable for kernel code. It also suffers from the disadvantage of requiring the programmer to explicitly track memory allocations while restricting pointers so tightly that it could have automated memory management entirely.…”

Section: Related Workmentioning

confidence: 99%

Using Pit to improve security in low-level programs

Pedersen

Reza

2009

J Supercomput

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Linear Regions Are All You Need

Fluet

Morrisett

Ahmed

2006

Programming Languages and Systems

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The type-and-effects system of the Tofte-Talpin region calculus makes it possible to safely reclaim objects without a garbage collector. However, it requires that regions have last-in-first-out (LIFO) lifetimes following the block structure of the language. We introduce λ rgnUL , a core calculus that is powerful enough to encode Tofte-Talpin-like languages, and that eliminates the LIFO restriction. The target language has an extremely simple, substructural type system. To prove the power of the language, we sketch how Tofte-Talpin-style regions, as well as the firstclass dynamic regions and unique pointers of the Cyclone programming language can be encoded in λ rgnUL .

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Typestate Verification: Abstraction Techniques and Complexity Results

Field¹,

Goyal²,

Ramalingam³

et al. 2003

Static Analysis

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Abstract. We consider the problem of typestate verification for shallow programs; i.e., programs where pointers from program variables to heap-allocated objects are allowed, but where heap-allocated objects may not themselves contain pointers. We prove a number of results relating the complexity of verification to the nature of the finite state machine used to specify the property. Some properties are shown to be intractable, but others which appear to be quite similar admit polynomial-time verification algorithms. While there has been much progress on many aspects of automated program verification, we are not aware of any previous work relating the difficulty of typestate verification to properties of the finite state automaton. Our results serve to provide insight into the inherent complexity of important classes of verification problems. In addition, the program abstractions used for the polynomial-time verification algorithms may be of independent interest.

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Adoption and focus

Cited by 26 publications

References 21 publications

Using Pit to improve security in low-level programs

Using Pit to improve security in low-level programs

Linear Regions Are All You Need

Typestate Verification: Abstraction Techniques and Complexity Results

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