789216
Program slicing based on specification
Slicing techniques can provide solutions to many software engineering problems such as testing, program understanding and extraction of a reusable component. However, current slicing criteria and the corresponding techniques might obtain slices that contain unnecessary statements in some situations. In this paper, we propose a new slicing technique that takes the specification of the slice into account. The information present in the specification helps to produce more precise slices by removing statements that are not relevant to the specification for the slice. Our technique is based on the weakest precondition and strongest postcondition. We present an example of applying the proposed technique in extracting a reusable component from an existing program.
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.
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.
16141068
Improving cohesion metrics for classes by considering dependent instance variables
The existing cohesion metrics for classes do not consider the characteristics of dependent instance variables that are commonly used in a class and, thus, do not properly reflect the cohesiveness of the class. This paper presents an approach for improving the cohesion metrics by considering the characteristics of the dependent instance variables in an object-oriented program.
15507852
Testing of concurrent programs based on message sequence charts
Most prior work on specification-based testing of concurrent programs have postulated an equivalence relation between specifications and programs. However the equivalence relation, which requires a specification and a program to encompass the same set of synchronization sequences, is not well-suited for resting concurrent programs against partial and nondeterministic specifications. We present a new specification-based approach to testing concurrent programs against Message Sequence Charts (MSCs) with partial and nondeterministic semantics. New conformance relations, named behavioral conformance and nondeterminacy conformance, are defined and the details of the proposed testing methodology based on the conformance relations are given. The effectiveness of our testing approach is investigated using a telephone switching system example.
12216769
Change impact analysis for a class hierarchy
Modified programs are required to be retested to determine whether changes have been made correctly and to investigate whether those cause any adverse effect on the program behavior. Then, the key issue is the extent of the retesting tasks. To save time and efforts, retesting should be done on only the parts that might be affected by changes. Change impact analysis is the activity which identifies the parts to be retested. Object-oriented paradigm is based on several concepts such as encapsulation, inheritance, polymorphism, and dynamic binding. Although these features contribute to the reusability and extensibility of systems, they produce complex dependencies between classes and attributes, which make it difficult to identify the affected components by changes. We propose an approach for analyzing change impact in a class hierarchy. Our approach is based on the class firewall method, but aims to reduce the retesting effort significantly by taking a member function as a test unit. We deal with the impacts of changes associated with various object-oriented features as well as types of changes which can occur at the level of a data member a member function, a class, and an inheritance relation.
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.
10182888
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure optimization in artificial neural networks. There were many nonlinear feature extraction methods using neural networks but they still have the same difficulties arisen from the fixed network topology. In this paper, we propose a novel combination of genetic algorithm and feedforward neural networks for nonlinear feature extraction. The genetic algorithm evolves the feature space by utilizing characteristics of hidden neurons. It improved remarkably the performance of neural networks on a number of real world regression and classification problems.
13194172
ActorNet: an actor platform for wireless sensor networks
We present actorNet, a mobile agent platform for wireless sensor networks (WSNs). WSNs are well-suited to multiagent systems: agent autonomy reduces the need for communication, saving precious energy. Mobile agents are also an intuitive technique for remotely reprogramming sensors deployed in the field. However, implementing agent programs directly on a WSN is complicated by the many limitations of sensor nodes, including limited memory, slow processors, low bandwidth and finite energy. ActorNet eases development by providing an abstract environment for lightweight concurrent object-oriented mobile code on WSNs. As such, it enables a wide range of new dynamic applications, including fully customizable queries and aggregation functions, in-network interactive debugging and high-level concurrent programming on the inherently parallel sensor network platform. Moreover, actorNet cleanly integrates all of these features into a fine-tuned, multi-threaded embedded Scheme interpreter that supports compact, maintainable programs---a significant advantage over primitive stack-based virtual machines.
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
7677555
Stock prediction based on financial correlation
In this paper, we propose a neuro-genetic stock prediction system based on financial correlation between companies. A number of input variables are produced from the relatively highly correlated companies. The genetic algorithm selects a set of informative input features among them for a recurrent neural network. It showed notable improvement over not only the buy-and-hold strategy but also the recurrent neural network using only the input variables from the target company.