Segment Abstraction for Worst-Case Execution Time Analysis
Paper i proceeding, 2015

In the standard framework for worst-case execution time (WCET) analysis of programs, the main data structure is a single instance of integer linear programming (ILP) that represents the whole program. The instance of this NP-hard problem must be solved to find an estimate for WCET, and it must be refined if the estimate is not tight. We propose a new framework for WCET analysis, based on abstract segment trees (ASTs) as the main data structure. The ASTs have two advantages. First, they allow computing WCET by solving a number of independent small ILP instances. Second, ASTs store more expressive constraints, thus enabling a more efficient and precise refinement procedure. In order to realize our framework algorithmically, we develop an algorithm for WCET estimation on ASTs, and we develop an interpolation-based counterexample-guided refinement scheme for ASTs. Furthermore, we extend our framework to obtain parametric estimates of WCET. We experimentally evaluate our approach on a set of examples from WCET benchmark suites and linear-algebra packages. We show that our analysis, with comparable effort, provides WCET estimates that in many cases significantly improve those computed by existing tools.


P. Cerny

University of Colorado at Boulder

T. A. Henzinger

Laura Kovacs

Chalmers, Data- och informationsteknik, Programvaruteknik

A. Radhakrishna

University of Pennsylvania

J. Zwirchmayr

IRIT Institut de Recherche Informatique de Toulouse

Lecture Notes in Computer Science

0302-9743 (ISSN)

Vol. 9032 105-131