36457558
Verification Framework for UML-Based Design of Embedded Systems
System level design incorporating system modeling and formal specification in combination with formal verification can substantially contribute to the correctness and quality of the embedded systems and consequently help reduce the development costs. Ensuring the correctness of the designed system is, of course, a crucial design criterion especially when complex distributed (realtime) embedded systems are considered. Therefore, this paper aims at presenting a verification framework designated for formal verification and validation of UML-based design of embedded systems. It first introduces an approach of using the AsmL language for acquiring formal models of the UML semantics and consequently presents an on-the-fly model checking technique designed to run the formal verification directly over those semantic models.
30853891
Comprehensive Verification Framework for Dependability of Self-optimizing Systems
By integrating formal specification and formal verification into the design phase of a system development process, the correctness of the system can be ensured to a great extent. However, it is not sufficient for a self-optimizing system that needs to exchange its components safely and consistently over time. Therefore, this paper presents a comprehensive verification framework to guarantee the dependability of such a self-optimizing system at the design phase (off-line verification) as well as at the runtime phase (on-line verification). The proposed verification framework adopts AsmL as intermediate representation for the system specification and on-the-fly model checking technique for alleviating the state space explosion problem. The off and the on -line verifications are performed at (RT-UML) model level. The properties to be checked are expressed by RT-OCL where the underlying temporal logic is restricted to time-annotated ACTL/LTL formulae. In particular, the on-line verification is achieved by running the on-the-fly model checking interleaved with the execution of the checked system in a pipelined manner.
27884919
Writing photo captions for the Web
Photographs are rarely self-sufficient. They need captions. A caption tells us something about the person or thing photographed, also something about the photographer. In this article, we discuss how to write photo captions for the Web. We provide examples from adultso and childrenos work.
15935019
Statistical interval-valued fuzzy systems via linear regression
In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system. In order to make the type-2 fuzzy logic system reasonable and reliable, a new simple statistical linear method to decide interval-valued fuzzy membership functions and a new probability type reduce reasoning method for the interval-valued fuzzy logic system are proposed in this paper. An example of statistical interval-valued FLS is performed and results show that the developed method is more accurate to design a fuzzy logic system than type-1 method and computation is efficient.
10708118
Fault modeling and simulation for crosstalk in system-on-chip interconnects
System-on-chips (SOCs) using ultra deep sub-micron (DSM) technologies and GHz clock frequencies have been predicted by the 1997 SIA Road Map. Recent studies, as well as experiments reported in this paper, show significant crosstalk effects in long on-chip interconnects of GHz DSM chips. Recognizing the importance of high-speed, reliable interconnects in GHz SOCs, we address in this paper the problem of testing for glitch and delay errors caused by crosstalk in buses and interconnects between components of a SOC. Since it is not possible to explicitly test for all the possible process variations and defects that can lead to crosstalk errors in SOC interconnects, we present an abstract model, Maximum Aggressor (MA) fault model, and its test requirements. The attractiveness of the model is that it can abstract crosstalk defects in interconnects with a linear number of faults, while the corresponding MA tests provide complete coverage for all level defects related to cross-coupling capacitance the interconnects. A SPICE-level fault simulation methodology is presented which allows simulation of a small subset of the potentially exponential number of defects. The simulation methodology also enables validation of the proposed fault model and the resulting test set.
11721850
Estimating LOC for information systems from their conceptual data models
Effort and cost estimation is crucial in software management. Estimation of software size plays a key role in the estimation. Line of Code (LOC) is still a commonly used software size measure. Despite the fact that software sizing is well recognized as an important problem for more than two decades, there is still much problem in existing methods. Conceptual data model is widely used in the requirements analysis for information systems. It is also not difficult to construct conceptual data models in the early stage of developing information systems. Much characteristic of an information system is actually reflected from its conceptual data model. We explore into the use of conceptual data model for estimating LOC. This paper proposes a novel method for estimating LOC for an information system from its conceptual data model through the use of multiple linear regression model. We have validated the method through collecting samples from both the industry and open-source systems.
17699590
Adapting K-Means Algorithm for Discovering Clusters in Subspaces
Subspace clustering is a challenging task in the field of data mining. Traditional distance measures fail to differentiate the furthest point from the nearest point in very high dimensional data space. To tackle the problem, we design minimal subspace distance which measures the similarity between two points in the subspace where they are nearest to each other. It can discover subspace clusters implicitly when measuring the similarities between points. We use the new similarity measure to improve traditional k-means algorithm for discovering clusters in subspaces. By clustering with low-dimensional minimal subspace distance first, the clusters in low-dimensional subspaces are detected. Then by gradually increasing the dimension of minimal subspace distance, the clusters get refined in higher dimensional subspaces. Our experiments on both synthetic data and real data show the effectiveness of the proposed similarity measure and algorithm.