Executable Analysis using Abstract Interpretation with Circular Linear Progressions

Sen, Rathijit; Srikant, Y. N.

doi:10.1109/memcod.2007.371251

Cited by 21 publications

(20 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(xi) Consider the instantiation of the ATA framework with strided-intervals over bitvectors [14,17], denoted by SI …”

Section: Overviewmentioning

confidence: 99%

See 1 more Smart Citation

A New Abstraction Framework for Affine Transformers

Sharma¹,

Reps²

2017

Static Analysis

View full text Add to dashboard Cite

Abstract. This paper addresses the problem of abstracting a set of1 represent the prestate and post-state, respectively. We introduce a framework to harness any base abstract domain B in an abstract domain of affine transformations. Abstract domains are usually used to define constraints on the variables of a program. In this paper, however, abstract domain B is repurposed to constrain the elements of C and Ý Ñ d -thereby defining a set of affine transformers on program states. This framework facilitates intraand interprocedural analyses to obtain function and loop summaries, as well as to prove program assertions.

show abstract

“…(xi) Consider the instantiation of the ATA framework with strided-intervals over bitvectors [14,17], denoted by SI …”

Section: Overviewmentioning

confidence: 99%

“…Examples of foundation domains. We now present a few foundation domains that allow to construct the non-relational small-set, interval [2], and stridedinterval [14,17] base domains.…”

Section: Algorithm 1 Abstract Composition Via Symbolic Abstractionmentioning

confidence: 99%

A New Abstraction Framework for Affine Transformers

Sharma¹,

Reps²

2017

Static Analysis

View full text Add to dashboard Cite

show abstract

“…A natural alternative is to let intervals "wrap" [8,11,15]. The wrapped intervals (or w-intervals) of Navas et al [11] still approximate a set of values as a single interval.…”

Section: Example 1 (Traditional Intervals Lose Precision Over Machinementioning

confidence: 99%

Abstract Interpretation over Non-lattice Abstract Domains

et al. 2013

View full text Add to dashboard Cite

Abstract. The classical theoretical framework for static analysis of programs is abstract interpretation. Much of the power and elegance of that framework rests on the assumption that an abstract domain is a lattice. Nonetheless, and for good reason, the literature on program analysis provides many examples of non-lattice domains, including non-convex numeric domains. The lack of domain structure, however, has negative consequences, both for the precision of program analysis and for the termination of standard Kleene iteration. In this paper we explore these consequences and present general remedies.

show abstract

“…Abstract Interpretation is used for tracking address computations and cache behavior. Techniques developed in [18] are employed to compute a safe approximation of the set of memory locations that can be accessed by any data memory reference. The results of address analysis are used to predict data cache behavior using the Abstract Interpretation technique.…”

Section: Related Workmentioning

confidence: 99%

“…We adapt the techniques developed in [18] for the first sub-problem, namely, calculating addresses of memory accesses (or address analysis). For the second sub-problem, namely, inferring cache behavior (or cache analysis), we describe a static analysis technique to determine the data cache hit/miss probability and hence the mean execution time of data memory reference instructions of the program.…”

Section: Data Cache Modelingmentioning

confidence: 99%

Probabilistic modeling of data cache behavior

Puranik

Mitra

Srikant

2009

Proceedings of the Seventh ACM International Conference on Embedded Software

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a formal analysis approach to estimate the expected (average) data cache access time of an application across all possible program inputs. Towards this goal, we introduce the notion of probabilistic access history that intuitively summarizes the history of data memory accesses along different program paths (to reach a particular program point) and their associated probabilities. An efficient static program analysis technique has been developed to compute the access history at all program points. We estimate the cache hit/miss probabilities and hence the expected access time of each data memory reference from the access history. Our experimental evaluation confirms the accuracy and viability of the probabilistic data cache modeling approach.

show abstract

Executable Analysis using Abstract Interpretation with Circular Linear Progressions

Cited by 21 publications

References 12 publications

A New Abstraction Framework for Affine Transformers

A New Abstraction Framework for Affine Transformers

Abstract Interpretation over Non-lattice Abstract Domains

Probabilistic modeling of data cache behavior

Contact Info

Product

Resources

About