N. Heintze and D. McAllester. On the complexity of set-based analysis. In Proceedings of ICFP'97, pages 150163. ACM Press, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... generality (we can recover the k CFA analyses by taking suitable instantiations of the approximation function) nor eOEciency (the only overheads of SRA, as compared to CFA, are those incurred by controlAEow sensitivity) Again, this is in strong contrast with Set Based Analysis, see e.g. [3, 6], which trades generality for simplicity. The main purpose of this paper is to dene Static Reduction Analysis for an object oriented language. Its applications to program transformation, including partial evaluation, and program verication, including security, will be reported elsewhere. The ....

N. Heintze and D. McAllester. On the complexity of set-based analysis. In Proceedings of ICFP'97, pages 150163. ACM Press, 1997.

....programs [55] safety checking [24, 50] and detecting uncaught exceptions [69] A basic, often seen form of ow analyses can be done in O(n 3 ) time where n is the size of the program. This so called monovariant form of analysis can be varied in minor ways without changing the time complexity [28], and for simplicity we will refer to all of these variations as 0 CFA. CFA is an abbreviation introduced by Shivers [59] it stands for control ow analysis . A common observation is that 0 CFA is sometimes rather imprecise, resulting in, for example, little or no optimization. The key ....

Nevin Heintze and David McAllester. On the complexity of set based analysis. In Proceedings of ACM International Conference on Functional Programming, 1997.

....Amadio Cardelli type system. This is consistent with something we had observed in unpublished work, where we gave a linear time reduction from the 2NPDA recognition problem to CFL reachability. Heintze and McAllester have also examined the complexity of set based analysis with data constructors [20, 10]. A variety of work exists that has applied graph reachability (of various forms) to analysis of imperative programs. Kou [19] and Hecht [6] gave linear time graph reachability algorithms for solving intraprocedural bit vector dataflow analysis problems. This approach was later applied to ....

D. McAllester and N. Heintze. On the complexity of set-based analysis. In ICFP '97: Proceedings of the Second ACM SIGPLAN International Conference on Functional Programming, 1997.

....constraints is that they are more expensive to solve than equality constraints. The best known algorithm for solving the simplest inclusion constraints is dynamic transitive closure which requires cubic time, and for more expressive constraints solvability becomes at least EXPTIME hard [AKVW93, MH97] To make inclusion constraint based analyses practical, a lot of effort is spent on tuning the representation and manipulation of constraints. Most importantly, inclusion constraints must be simplified to obtain more concise representations of solutions [Pot96, FA96, TS96, FF97] While ....

David McAllester and Nevin Heintze. On the complexity of set-based analysis. In ICFP'97 [ICF97], pages 150--63.

.... of set based approximation in the earlier work of Mishra [72] and Yardeni and Shapiro [97,98] They gave such a definition for logic programs in terms of the TP operator, which is obtained from the TP operator by replacing substitutions with set valued substitutions (later, McAllester and Heintze [70] gave such a definition for functional languages) The TP operator formalizes the intuition of set environments given above. They gave an equivalent characterization of the set based approximation of the logic program P via a transformation of P to another logic program P 0 . They were ....

....to provide a family of set based safety analysis. Early work in this domain was done by Mishra and Reddy [73] and Thatte [90] and was extended by many researchers including Aiken, Wimmers and Lakshman [5 7,2,9] Palsberg and O Keefe [79] Palsberg and Schwartzbach [80] McAllester and Heintze [70] systematized the notion of set based analyses of functional languages and gave a thorough study of its complexity. Heintze and McAllester [58,59] address the complexity of controlflow analysis, which is at the heart of set based analyses for ML. Cousot and Cousot [27] showed that set based ....

D. McAllester and N. Heintze. On the complexity of set-based analysis. www.ai.mit.edu/people/dam/setbased.ps.

....Amadio Cardelli type system. This is consistent with something we had observed in unpublished work, where we gave a linear time reduction from the 2NPDA recognition problem to CFL reachability. Heintze and McAllester have also examined the complexity of set based analysis with data constructors [33, 20]. 7.3 Applications of CFL reachability Dolev, Even, and Karp used CFL reachability to devise a formal model for studying the vulnerability to intrusion by a third party of a class of two party ( ping pong ) protocols in distributed systems to intrusion by a third party [11] Although messages in ....

D. McAllester and N. Heintze. On the complexity of set-based analysis. In ICFP '97: Proceedings of the Second ACM SIGPLAN International Conference on Functional Programming, 1997.

....paper is given in the figures and their captions. The body of the paper is used primarily to give examples of the concepts and analyses defined in the figures. Due to space restrictions many of the proofs have been omitted here. However, proofs can be found in the full paper available on the web [11]. 2 Results The syntax and semantics of a simple operational language with case statements is given in figure 1. The semantics is given as a set of reduction rules which can be used to reduce a term to a value (which is another term) One of the classical goals of static analysis is to provide a ....

....in the general case. The rules are similar to those of figure 7 but the space of abstract values is expanded to include intersections of program nodes with program patterns and negations of program patterns. Proofs of the other results in figure 6 can be found on the web in the full paper [11]. 3 Conclusions This paper contains two significant results. The first is a unification of various notions of set based analysis into a single definition which can be applied to any language whose operational semantics BETA EVAL( f w) f x:u x w; f w) u CASE EVAL(CASE(u of p1 : e1 ; ....

D. McAllester and N. Heintze. On the complexity of set based analysis. http://www.ai.mit.edu/people/dam/setbased.ps.

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N. Heintze and D. McAllester. On the complexity of set-based analysis. In Proceedings of ICFP'97, pages 150163. ACM Press, 1997.

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D. McAllester and N. Heintze. On the complexity of set-based analysis. In ICFP '97: Proceedings of the Second ACM SIGPLAN International Conference on Functional Programming, 1997.

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