Embedded computer systems commonly interact with the environment. There may be some realtime constraints imposed on this interaction. To guaranteesuchconstraints the knowledge about the worst case execution time (WCET) of the system components is mandatory. In the last years several concepts have been developed to obtain the WCET statically by code analysis or dynamically by measurements. In this paper we describe a method for static WCET analysis. This methodisbased on analysis with implicit path enumeration by the use of linear programming. This is a quite efficient approach with respect to the analysis time. We present a graph based formalism to analyze programs. This formalism handles in a smart way the different execution times of conditional instructions whether the branch is taken or not. This approach enables the calculation of tight WCET result with small effort.

Abstract ─ We present, in this paper, a new metric capturing in an integrated way different attributes of object-oriented systems. The metric uses basically control flow paths and probabilities. It captures the interactions between classes and related control. The study presented in this paper aims

that runs slower than their FORTRAN and C counterparts. The problem is the lack of an explicit control-flow graph at compile time, something which traditional data-flow analysis techniques require. In this dissertation, I present a technique for recovering the control-flow graph of a Scheme program

In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program

assignment form and the control dependence graph have been proposed to represent data flow and control flow propertiee of programs. Each of these previously unrelated techniques lends efficiency and power to a useful class of program optimization. Although both of these structures are attractive

with the network, plans, decides and acts on this information. Cognitive networks are different from other “intelligent ” communication technologies because these actions are taken with respect to the end-to-end goals of a data flow. In addition to the cognitive aspects of the network, a specification language

propose control-flow decoupling (CFD) to eradicate mispredictions of separable branches. The idea is to separate the loop containing the branch into two loops: the first contains only the branch’s predicate computation and the second contains the branch and its control-dependent instructions. The first

, the more IDs must be stored and checked at each branch. Moreover, perfect CFI cannot be realized with a purely static control-flow graph; for example, the permissible destinations of function returns depend on the calling context, which is only known at runtime. Fine-grained CFI therefore implements a

-grade bond yield changes on Treasury yield changes and stock returns (see Kwan (1996)) we find that the R 2 falls to five percent when the dependent variable is credit spread changes. Hence, while much is known about yield changes, we have very limited knowledge about the determinants of credit spread

of control-flow and control dependence analysis. We consider two classes of tools: execution measurement tools, which collect information about a particular program execution; and program analysis tools, which provide information about potential program behavior by statically analyzing the program. We