Computer Science

In this paper, we propose the use of constraint logic programming as a way of modeling contextsensitive execution-times of program segments. The context-sensitive constraints are collected automatically through static analysis or measurements. We achieve considerable tightness in comparison to traditional calculation methods that exceeded 20% in some cases during evaluation. The use of constraint-logic programming in our calculations proves to be the right choice when compared to the exponential behaviour recorded by the use of integer linear-programming.

Knowledge about the Worst-Case Execution-Time (WCET) is of primordial importance in the validation of real-time systems. A WCET estimation must be safe and tight. Tightness in WCET estimation is highly desirable for an efficient utilisation of resources. In order to obtain accurate WCET values, more program execution-history must be accounted for. In this thesis we propose the use of Predicated WCET Analysis which uses constraint-logic programming to model context-sensitive execution-times of program segments. We prove that our predicated analysis is safe and very tight compared to contemporary analysis techniques.

Worst Case Execution Time (WCET) computation is crucial to the overall timing analysis of real-time embedded systems. Facing the ever increasing complexity of such systems, techniques dedicated to WCET analysis can take advantage of Component Based Software Engineering (CBSE) by decomposing a difficult problem into smaller pieces, easier to analyse. To achieve this objective, the corresponding analysis results have to be composed to provide timing guarantees on the whole system. In this paper, we express the WCET of a component as a formula, allowing to represent its different computational modes. We then propose a Model Driven Engineering (MDE) approach that derives parametric WCET for composite components from parametric WCET of their subcomponents. This approach gives more accurate WCET estimates than naïve additive compositional analysis by taking into account usage context of components. However, analysis scalability concerns lead us to consider a trade-off between precision and scalability. This trade-off can be specified in the model. The composition of WCET estimations is automated and produces the parametric WCET expression of the composite component under analysis. This approach has been integrated in PRIDE 1 .

Estimating the worst-case execution time (WCET) of real-time embedded systems is compulsory for the verification of their correct functioning. Traditionally, the WCET of a program is estimated assuming availability of the program's binary which is disassembled to reconstruct the program, and in some cases its source code to derive useful highlevel execution information. However, in certain scenarios the program's owner requires that the binary of the program not be reverse-engineered to protect intellectual property; and in extreme situations, the program's binary is not available for the analysis, in which case it is substituted by program-execution traces.

Abstract Estimating the worst-case execution time (WCET) of real-time programs is pivotal in their verification. WCET estimation either yields a numeric value that represents the maximum execution time of the program when executed on a specific hardware platform; or yields a parametric expression in the form of some function of the input which when instantiated with a particular input value, gives a WCET estimation of the program when triggered by this input specifically (on a specific hardware platform).

I take real pleasure in seeing the proceedings of the 12th International Workshop on Worst-Case Execution Time Analysis online already on the day of the workshop. This helps WCET'12 achieve its goal of facilitating discussion and interaction among participants as well as of returning value to the authors of the works that were accepted for presentation.

Corrosion occurs in many engineering structures such as bridges, pipelines, and refineries and leads to the destruction of materials in a gradual manner and thus shortening their lifespan. It is therefore crucial to assess the structural integrity of engineering structures which are approaching or exceeding their designed lifespan in order to ensure their correct functioning, for example, carrying ability and safety. An understanding of corrosion and an ability to predict corrosion rate of a material in a particular environment plays a vital role in evaluating the residual life of the material. In this paper we investigate the use of genetic programming and genetic algorithms in the derivation of corrosion-rate expressions for steel and zinc. Genetic programming is used to automatically evolve corrosion-rate expressions while a genetic algorithm is used to evolve the parameters of an already engineered corrosion-rate expression. We show that both evolutionary techniques yield corros...

In this paper, we propose the use of constraint logic programming as a way of modeling contextsensitive execution-times of program segments. The context-sensitive constraints are collected automatically through static analysis or measurements. We achieve considerable tightness in comparison to traditional calculation methods that exceeded 20% in some cases during evaluation. The use of constraint-logic programming in our calculations proves to be the right choice when compared to the exponential behaviour recorded by the use of integer linear-programming.

In this paper, we propose the use of constraint logic programming as a way of modeling contextsensitive execution-times of program segments. The context-sensitive constraints are collected automatically through static analysis or measurements. We achieve considerable tightness in comparison to traditional calculation methods that exceeded 20 % in some cases during evaluation. The use of constraint-logic programming in our calculations proves to be the right choice when compared to the exponential behaviour recorded by the use of integer linear-programming. 1.

Obtaining tight worst-case execution-time (WCET) estimations of real-time tasks is crucial since overly-pessimistic estimations are deemed impractical. One way of making WCET estimations tighter is to incorporate more program-flow information e.g., context-sensitive loop bounds, infeasible-path and same-path information, etc. In this paper we present and evaluate a completely automatic analysis that dynamically derives program-flow information to use in WCET analysis. Flow information is derived by a combination of test-data generation and parsing of programexecution traces to obtain flow-fact hypotheses which are then fed to a model checker to establish their correctness. Experimental evaluation shows that our method help achieve considerable tightness in WCET estimations at a manageable cost.

Estimating the worst-case execution time (WCET) of real-time programs is pivotal in their verification. WCET estimation either yields a numeric value that represents the maximum execution time of the program when executed on a specific hardware platform; or yields a parametric expression in the form of some function of the input which when instantiated with a particular input value, gives a WCET estimation of the program when triggered by this input specifically (on a specific hardware platform). Parametric WCET analysis provides extra accuracy as the WCET estimation can be tuned to particular input values at runtime; and is usually of interest to dynamic-scheduling schemes. In this paper we use genetic programming as an alternative method to approach the problem of parametric WCET analysis. Parametric expressions are captured automatically by the genetic program based on end-to-end executions of the program under analysis. The technique is complementary to static parametric WCET an...

I take real pleasure in seeing the proceedings of the 12th International Workshop on Worst-Case Execution Time Analysis online already on the day of the workshop. This helps WCET'12 achieve its goal of facilitating discussion and interaction among participants as well as of returning value to the authors of the works that were accepted for presentation. I also feel personal satisfaction in having achieved the production of these proceedings as a tangible manifestation of the considerable effort that went in making WCET'12 happen, ...

It is becoming increasingly difficult to ignore the complexity of software products. Software metrics are proposed to help show indications for quality, size, complexity, etc. of software products. In this paper, software metrics related to complexity are developed and evaluated. A dataset of many open source projects is built to assess the value of the developed metrics. Comparisons and correlations are conducted among the different tested projects. A classification is proposed to classify software code into different levels of complexity. The results showed that measuring the complexity of software products based on decision coverage gives a significant indicator of degree of complexity of those software products. However, such indicator is not exclusive as there are many other complexity indicators that can be measured in software products. In addition, we conducted a comparison among several available metric tools that can collect software complexity metrics. Results among those different tools were not consistent. Such comparison shows the need to have a unified standard for measuring and collecting complexity attributes.

Researchers in computer science and computer engineering devote a significant part of their efforts on communication and interaction between man and machine. Indeed, with the advent of multimedia and multimodal processing in real time, the computer is no longer considered only as a computational tool, but as a machine for processing, communication, collection and control. Many machines assist and support many activities in daily life. The main objective of this paper is to propose a new methodological solution by modeling an architecture that facilitates the work of multimodal system especially for a fission module. To realize such systems, we rely on ontology to integrate data semantically. Ontologies provide a structured vocabulary usedas support for data representation. This paper provides a better understanding of the fission system and multimodal interaction. We present our architecture and the description of the detection of optimal modalities. This is done by using an ontological model that contains different applicable scenarios and describes the environment where a multimodal system exists. Fusion Fission Multimodal System Environment Environment Command Modality In1 Modality In2 Modality Inn Modality Ou1 Modality Ou2 Modality Oun Figure 1. Multimodal system. Copyright © 2013 SciRes. JSEA Modeling Rules Fission and Modality Selection Using Ontology 355