1823005
Functional coverage metric generation from temporal event relation graph
Functional coverage is a technique which can be used for checking the completeness of test vectors. In this paper, automatic generation of temporal events for functional coverage is proposed. The TERG (Temporal Event Relation Graph) is the graph where the nodes represent basic temporal property and the edges represent the time-shift value between two properties. Hierarchical temporal events are generated by traversing TERG such that invalid or irrelevant properties are eliminated. Concurrent edge groups in TERG make it possible to generate more comprehensive temporal properties.
13416160
Bandwidth tracing arbitration algorithm for mixed-clock SoC with dynamic priority adaptation
As the processing capabilities and operating frequency of embedded system are growing, so is the needed data bandwidth to fully utilize the processing capability. The ability to transfer huge amount of data between the embedded core and external devices is required for efficient system operation. In this paper, the data communication architecture for the mixed-clock system is proposed. The dynamic priority adaptation algorithm for bus arbitration is proposed for bandwidth guarantee. The communication architecture that incorporates the proposed arbitration algorithm adapts the priority of communication components dynamically based on the information from FIFO. The experiments show that the measured bandwidth of each component traces the required bandwidth well compared to the other arbitration algorithms.
19995952
ATOMi: an algorithm for circuit partitioning into multiple FPGAs using time-multiplexed, off-chip, multicasting interconnection architecture
Logic emulation is so far the fastest method to verify the system functionality in the gate level before chip fabrication. Field-programmable gate array (FPGA)-based logic emulator with large gate capacity generally comprises a large number of FPGAs or special processors connected in mesh or crossbar topology. However, gate utilization of FPGAs and speed of emulation are limited by the number of signal pins among FPGAs and the interconnection architecture of the logic emulator. This paper first describes a new interconnection architecture called TOMi (Time-multiplexed, Off-chip, Multicasting interconnection) and proposes a circuit partitioning algorithm called ATOMi (Algorithm for TOMi) for multi-FPGA system incorporating four to eight FPGAs where FPGAs are interconnected through TOMi. ATOMi reduces the number of off-chip signal transfers to optimize the performance for multi-FPGA system implemented by TOMi. Experimental results using Partitioning93 benchmarks show that, by adopting the proposed TOMi interconnection architecture along with ATOMi, the pin count is reduced to 14.4%-88.6% while the critical path delay is reduced to 66.1%-90.1% compared to traditional architectures including mesh, crossbar, and VirtualWire architecture.
5100963
Scalable Modeling and Performance Evaluation of Wireless Sensor Networks
A notable features of many proposed Wireless Sensor Networks (WSNs) deployments is their scale: hundreds to thousands of nodes linked together. In such systems, modeling the state of the entire system as a cross-product of the states of individual nodes results in the well-known state explosion problem. Instead, we represent the system state by the probability distribution on the state of each node. In other words, the system state represents the probability that a randomly picked node is in a certain state. Although such statistical abstraction of the global state loses some information, it is nevertheless useful in determining many performance metrics of systems that exhibit Markov behavior. We have previously developed a method for specifying the performance metrics of such systems in a probabilistic temporal logic called iLTL and for evaluating the behavior through a novel method for model checking iLTL properties. In this paper, we describe a method for estimating the probabilities in a Discrete Time Markov Chain (DTMC) model of a large-scale system. We also provide a statistical test so that we can reject estimated DTMCs if the actual system does not have Markov behavior. We describe results of experiments applying our method toWSNs in an experimental test-bed, as well as using simulations. The results of our experiments suggest that our model estimation and model checking method provides a systematic, precise and easy way of evaluating performance metrics of some large-scale WSNs.
8261294
Inter-class mutation operators for Java
The effectiveness of mutation testing depends heavily on the types of faults that the mutation operators are designed to represent. Therefore, the quality of the mutation operators is key to mutation testing. Mutation testing has traditionally been applied to procedural-based languages, and mutation operators have been developed to support most of their language features. Object-oriented programming languages contain new language features, most notably inheritance, polymorphism, and dynamic binding. Not surprisingly; these language features allow new kinds of faults, some of which are not modeled by traditional mutation operators. Although mutation operators for OO languages have previously been suggested, our work in OO faults indicate that the previous operators are insufficient to test these OO language features, particularly at the class testing level. This paper introduces a new set of class mutation operators for the OO language Java. These operators are based on specific OO faults and can be used to detect faults involving inheritance, polymorphism, and dynamic binding, thus are useful for inter-class testing. An initial Java mutation tool has recently been completed, and a more powerful version is currently under construction.
9037240
Empirical evaluation of a fuzzy logic-based software quality prediction model
Software inspection, due to its repeated success on industrial applications, has now become an industry standard practice. Recently, researchers began analyzing inspection data to obtain insights on how software processes can be improved. For example, project managers need to identify potentially error-prone software components so that limited project resource may be optimally allocated. This paper proposes an automated and fuzzy logic-based approach to satisfy such a need. Fuzzy logic offers significant advantages over other approaches due to its ability to naturally represent qualitative aspect of inspection data and apply flexible inference rules. In order to empirically evaluate the effectiveness of our approach, we have analyzed published inspection data and the ones collected from two separate inspection experiments which we had conducted. χ2 analysis is applied to statistically demonstrate validity of the proposed quality prediction model.
61822837
Resilient Localization for Sensor Networks in Outdoor Environments
The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is often impractical due to time requirements, economic constraints or inherent limitations of deployment scenarios. We have developed a service for reliably localizing wireless sensor networks in environments conducive to ranging errors by using a custom hardware-software solution for acoustic ranging and a family of self-localization algorithms. The ranging solution improves on previous work, extending the practical measurement range threefold (20-30m) while maintaining a distance-invariant median measurement error of about 1% of maximum range (33cm). The localization scheme is based on least squares scaling with soft constraints. Evaluation using ranging results obtained from sensor network field experiments shows that the localization scheme is resilient against large-magnitude ranging errors and sparse range measurements, both of which are common in large-scale outdoor sensor network deployments
42278030
Hybrid knowledge-based architecture for building an intelligent nondestructive signal inspection system
The paper deals with the methods of implementing an intelligent inspection system for monitoring the health of any device or material using a nondestructive signal. A hybrid knowledge representation and processing architecture is proposed as a solution to problems encountered in the processes of the nondestructive inspection. In the proposed system, to modularize knowledge elicitation and to make knowledge processing reliable, the task of inspection is delegated to two subsystems each of which has a proper knowledge processing scheme to match the properties of its own task. The front-end subsystem which detects the signal patterns (events) for any harmful flaw is built by integrating a fuzzified syntactic pattern recognition concept and a neural network concept. The back-end subsystem which evaluates the characteristics of the events is based upon object-oriented rule base system concepts. The methods of integrating the approaches in the proposed architecture are also proposed in the paper. The proposed architecture is verified by developing and evaluating a prototype which automatically interprets eddy current Lissajous signals to inspect the state of tubes used in nuclear power plants.