PPT-Weakest Precondition Synthesis for Compiler Optimizations

Nuno Lopes and José Monteiro Deriving preconditions by hand is hard WPs are often nontrivial WPs derived by hand are often wrong Weaker preconditions expose more optimization opportunities. Bruce Worthington. Software Development Manager. Microsoft Corporation. Key Takeaways. Be a leader in advancing 64-bit computing. Adopt best practices and new tools. Let’s partner on new hardware directions. Sumit Gulwani. (MSR Redmond). Ramarathnam. . Venkatesan. (MSR Redmond). Saurabh. . Srivastava. (. Univ. . of Maryland). TexPoint. fonts used in EMF. . Read the . TexPoint. manual before you delete this box.: . Chapter 8. Classes. Collection of objects. Objects are not actions. Class names – Nouns. Method names – Verbs. What Makes a Good Class. Represent a single concept. Easy to understand. Examples. Concepts from math. in . Dyninst. Andrew . Bernat. , Matthew Legendre. Instrumentation is Complicated. User perspective: . “Insert some new code here, here, and here.”. Dyninst’s. perspective:. Relocation. – Move code to make space for instrumentation. and High-Coverage Tests. Presented by Yoni Leibowitz. EXE & KLEE. Automatically Generating Inputs of Death. David Dill. Vijay . Ganesh. Cristian Cadar. Dawson Engler. Peter Pawlowski. KLEE. EXE. Unassisted & Automatic Generation of High-Coverage Tests for Complex System Programs. Command Object. In . this program . the command object . is . AnImageAnimationCommand. A . command objects implements . Runnable. Contains method run(). Thread need . an . instance . of it to . do work. Prof. O. . Nierstrasz. Lecture notes by Marcus . Denker. © Marcus . Denker. Optimization. Roadmap. Introduction. Optimizations in the Back-end. The Optimizer. SSA Optimizations. Advanced Optimizations. & Assertions. Function Specification. Often want to communicate what a function does without indicating how it works:. The specification of a function can be defined by its pre-conditions and post-conditions. . Ross Tate. Michael Stepp. Sorin Lerner. University of California, San Diego. Optimizing by Hand. Original. for (i = 0; i < 50; i ). . for (j = 0; j < 50; j ). . img[i*50 j] = f(i, j);. Ross Tate. Michael Stepp. Sorin Lerner. University of California, San Diego. Optimizing by Hand. Original. for (i = 0; i < 50; i ). . for (j = 0; j < 50; j ). . img[i*50 j] = f(i, j);. Prof. Gennady . Pekhimenko. University of Toronto. Winter 2018. The content of this lecture is adapted from the lectures of . Todd Mowry and Phillip Gibbons. CSC D70: . Compiler Optimization. Introduction, Logistics. T. Chen, T. Moreau, Z. Jiang, L. Zheng, S. Jiao, E. Yan, H. Shen, M. Cowan, L. Wang, Y. Hu, L. . Ceze. , C. . Guestrin. , and A. Krishnamurthy . Presentation by Grzegorz . AnindicationofhowtheconnectionsareshownbetweenthestatemachinesforthedifferentdynamicsortsisgiveninFigure8wherethecompletemodelfortheDWRdomainispresented33ScalingtolargedomainsUsingthebasicOHLEdesignin . Sagiv. Slides from . Zvonimir. . Rakamaric. . 2. First-Order Logic. A formal notation for mathematics, with expressions involving . Propositional symbols. Predicates. Functions and constant symbols.