• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.11a
• /
• pp.377-382
• /
• 2003

In our previous study, we have developed sound quality index for steady rumbling sound of passenger car. In this paper, we will study sound quality index for transient rumbling noise. The subjective evaluation of rumbling sound can be indicated to objective parameters by sound metrics of psychoacoustics and principal rumble component. And artificial neural network can be estimated complexity and nonlinear characteristics of relation between subjective evaluation and sound metrics. We applied to sound metrics and artificial neural network to development of sound quality index for transient rumbling sound of passenger car.

• Journal of KIISE:Software and Applications
• /
• v.34 no.7
• /
• pp.603-615
• /
• 2007

Software changes for various kinds of reasons and they increase maintenance cost. Software metrics, as quantitative values about attributes of software, have been adopted for predicting maintenance cost and fault-proneness. This paper proposes relationship between some typical object-oriented metrics and software changes in industrial settings. We used seven metrics which are concerned with size, complexity coupling, inheritance and polymorphism, and collected data about the number of changes during the development of an Information system on .NET platform. Based on them, this paper proposes a model for predicting the number of changes from the object-oriented metrics using multiple regression analysis technique.

• Nuclear Engineering and Technology
• /
• v.44 no.6
• /
• pp.663-672
• /
• 2012

As software based digital I&C (Instrumentation and Control) systems are used more prevalently in nuclear plants, enhancement of software dependability has become an important issue in the area of nuclear I&C systems. Critical attributes of software dependability are safety and reliability. These attributes are tightly related to software failures caused by faults. Software testing and V&V (Verification and Validation) activities are hence important for enhancing software dependability. If the risky modules of safety-critical software can be predicted, it will be possible to focus on testing and V&V activities more efficiently and effectively. It should also make it possible to better allocate resources for regulation activities. We propose a prediction technique to estimate risky software modules by adopting machine learning models based on software complexity metrics. An empirical study with various machine learning algorithms was executed for comparing the prediction performance. Experimental results show SVMs (Support Vector Machines) perform as well or better than the other methods.

• Journal of KIISE:Software and Applications
• /
• v.30 no.5_6
• /
• pp.389-397
• /
• 2003

The component-based development methodology becomes famous as the new way for reuse. The goal of the reuse is improvement of quality, productivity and independence on the software development. For the improvement in the quality of a component-based system, it is necessary to research component metrics in the early phase of a component development. Hence, in this paper, we propose new component metrics using the information of a component analysis phase. Those are CCI(Complexity of Component Interface) and LCC(Lack Cohesion of Component interface). CCI indicates a difficulty about comprehension, modification, management, use of interface. LCC indicates a functional independence about how strong the elements are related with. Therefore, it is possible to predict and manage the quality of a component to be developed. Predicting a lowness of complexity and highness of cohesion as an independent functional unit by a component interface in the early phase of a component development, we can expect the improvement in the quality of a system.

• Journal of KIISE:Software and Applications
• /
• v.27 no.6
• /
• pp.595-606
• /
• 2000

Software metrics evaluate the development process, measure the software development effort, and control the software quality effectively. Moreover in a current status to emphasize reusability, it is necessary to study of cohesion and coupling that plays an important role in evaluating reusability. Object oriented methodology to use the concept like encapsulation, inheritance, and polymorphism demands metrics that are different from existing procedural methodology, so a study for object oriented metrics is in progress at the present time. In this paper, we propose cohesion and coupling metrics for object oriented program, evaluate the proposed metrics by using the complexity properties proposed by Weyuker and Briand, and extract cohesion and coupling from C++ code.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.4
• /
• pp.328-333
• /
• 2002

The deeper the hierarchy of a inheritance structure is, the better the reusability of the structure is, but the more difficult the understandability and the maintainability of it is. On the contrary, the shallower the hierarchy is, the worse the abstraction of the inheritance structure is, but the better the understandability and modifiability of it is. Therefore, it is to be desired that a deep hierarchy of a inheritance structure should be split to be shallow for the maintainability of a system. This paper proposed a complexity metric that is based on DIT and NOC of Chidamber and Kemerer, and solved the ambiguity of the metrics of them, which was pointed out by Li. The metric is a simple and heuristic one for measuring the complexity of class inheritance structures by considering the number of ancestor classes and descendant classes and the depth of inheritance hierarchy. This provides a quantitative information for assessing the complexity of a inheritance structure in splitting it.

• The Journal of Information Technology and Database
• /
• v.3 no.2
• /
• pp.97-118
• /
• 1996

Information systems quality engineering is one of the most problematic areas in practice and research, and needs cooperative efforts between practice and theory [Glass, 1996]. A model for evaluating the quality of system development process and ensuing success is proposed based on information processing theory of project unit design. A nomological net among a set of quality variables is identified from prior research in the areas of organization science, software engineering, and management information systems. More specifically, system development success was modelled as a function of project complexity, system development modelling environment, user participation, project unit structure, resource availability, and the level of iterative nature of development methodology. Based on the model developed from the information processing theory of project unit design in organization science. appropriate quality metrics for each variable in the proposed model are matched. In this way, a framework of relevant systems development and success quality metrics for controlling systems development processes and ensuing success is proposed. The causal relationships among the constructs in the proposed model are proposed as future empirical research for academicians and as managerial tools for quality managers. The framework and propositions help quality manager to select more parsimonious quality metrics for controlling information systems development processes and project success in an integrated way. Also this model can be utilized for evaluating software quality assurance programmes, which are developed and marketed by many vendors.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.3
• /
• pp.75-84
• /
• 2007

Due to the increasing complexity and shorter life cycle of web applications, web applications need to be restructured to improve flexibility and extensibility. These days approaches are being used where systems are understood and restructured through clustering techniques. In this paper, the coupling metrics are proposed for clustering web pages more effectively. To achieve this, web application models are defined, where the relationship between web pages and the numbers of parameters are included. Considering direct and indirect coupling strength based on these models, coupling metrics are defined. The more direct relations between two pages and the more parameters they have, the stronger direct coupling is. The higher indirect connectivity strength between two pages is, the more similar the patterns of relationships among other web pages are. We verify the suggested metrics according to the well known verification framework and provide a case study to show that our metrics complements some existing metrics.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.2
• /
• pp.373-384
• /
• 2000

There are many researches about metrics to measure a quality of Object-Oriented(OO) software. However, most of them have only discussed a concept or properties of metrics, and have not shown the detailed procedure for measuring them. They also define a measurement indicator as a threshold, but it has been influenced on a project size or application domains. In this paper, we propose metrics based on characteristics of OO design such as size, complexity, coupling and cohesion, and use a propotion to an average as the measurement indicator. It is easy to classify classes which have a result above the average, and to predict classes which reduced the quality of OO design. They will be modified to hold the average. Proposed metrics are analytically evaluated by Weyuker's nine properties. They are satisfied with seven properties except two properties co not apply to OO metrics. Also, we design a quality assessment system, ASSOD(ASsessment System of Object oriented Design), to measure the quality of the OO design independent of the platform.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.6
• /
• pp.1522-1545
• /
• 2012

Call admission control (CAC) plays an important role in mobile cellular network to guarantee the quality of service (QoS). In this paper, a dynamic hybrid CAC scheme with integrated cutoff priority and handoff queue for mobile cellular network is proposed and some performance metrics are derived. The unique characteristic of the proposed CAC scheme is that it can support any number of service types and that the cutoff thresholds for handoff calls are dynamically adjusted according to the number of service types and service priority index. Moreover, timeouts of handoff calls in queues are also considered in our scheme. By modeling the proposed CAC scheme with a one-dimensional Markov chain (1DMC), some performance metrics are derived, which include new call blocking probability ($P_{nb}$), forced termination probability (PF), average queue length, average waiting time in queue, offered traffic utilization, wireless channel utilization and system performance which is defined as the ratio of channel utilization to Grade of Service (GoS) cost function. In order to validate the correctness of the derived analytical performance metrics, simulation is performed. It is shown that simulation results match closely with the derived analytic results in terms of $P_{nb}$ and PF. And then, to show the advantage of 1DMC modeling for the performance analysis of our proposed CAC scheme, the computing complexity of multi-dimensional Markov chain (MDMC) modeling in performance analysis is analyzed in detail. It is indicated that state-space cardinality, which reflects the computing complexity of MDMC, increases exponentially with the number of service types and total channels in a cell. However, the state-space cardinality of our 1DMC model for performance analysis is unrelated to the number of service types and is determined by total number of channels and queue capacity of the highest priority service in a cell. At last, the performance comparison between our CAC scheme and Mahmoud ASH's scheme is carried out. The results show that our CAC scheme performs well to some extend.