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

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.348-358
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• 2022

Software fault prediction is a method to compute fault in the software sections using software properties which helps to evaluate the quality of software in terms of cost and effort. Recently, several software fault detection techniques have been proposed to classifying faulty or non-faulty. However, for such a person, and most studies have shown the power of predictive errors in their own databases, the performance of the software is not consistent. In this paper, we propose a hybrid soft computing technique for SFP based on optimal feature extraction and classification (HST-SFP). First, we introduce the bat induced butterfly optimization (BBO) algorithm for optimal feature selection among multiple features which compute the most optimal features and remove unnecessary features. Second, we develop a layered recurrent neural network (L-RNN) based classifier for predict the software faults based on their features which enhance the detection accuracy. Finally, the proposed HST-SFP technique has the more effectiveness in some sophisticated technical terms that outperform databases of probability of detection, accuracy, probability of false alarms, precision, ROC, F measure and AUC.

• Nuclear Engineering and Technology
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• v.38 no.3
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• pp.259-276
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• 2006

As the use of digital systems becomes more prevalent, adequate techniques for software specification and analysis have become increasingly important in nuclear power plant (NPP) safety-critical systems. Additionally, the importance of software verification and validation (V&V) based on adequate specification has received greater emphasis in view of improving software quality. For thorough V&V of safety-critical systems, V&V should be performed throughout the software lifecycle. However, systematic V&V is difficult as it involves many manual-oriented tasks. Tool support is needed in order to more conveniently perform software V&V. In response, we developed four kinds of computer aided software engineering (CASE) tools to support system specification for a formal-based analysis according to the software lifecycle. In this work, we achieved optimized integration of each tool. The toolset, NuSEE, is an integrated environment for software specification and V&V for PLC based safety-critical systems. In accordance with the software lifecycle, NuSEE consists of NuSISRT for the concept phase, NuSRS for the requirements phase, NuSDS for the design phase and NuSCM for configuration management. It is believed that after further development our integrated environment will be a unique and promising software specification and analysis toolset that will support the entire software lifecycle for the development of PLC based NPP safety-critical systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1356-1376
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• 2023

Software effort estimation is one of the most difficult tasks in software development whereas predictability is also of equal importance for strategic management. Accurate prediction of the actual cost that will be incurred in software development can be very beneficial for the strategic management. This study discusses the latest trends in software estimation focusing on analogy-based techniques to show how they have improved the accuracy for software effort estimation. It applies the standard deviation technique to the expected value of analogy-based estimates to improve accuracy. In more than 60 percent cases the applied technique of this study helped in improving the accuracy of software estimation by reducing the Magnitude of Relative Error (MRE). The technique is simple and it calculates the expected value of cost or time and then uses different confidence levels which help in making more accurate commitments to the customers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.932-951
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• 2021

The effectiveness of testing in Model-based Testing (MBT) for Software Product Line (SPL) can be achieved by considering fault detection in test case. The lack of fault consideration caused test case in test suite to be listed randomly. Test Case Prioritization (TCP) is one of regression techniques that is adaptively capable to detect faults as early as possible by reordering test cases based on fault detection rate. However, there is a lack of studies that measured faults in MBT for SPL. This paper proposes a Test Case Prioritization (TCP) approach based on dissimilarity and string based distance called Last Minimal for Local Maximal Distance (LM-LMD) with Dice-Jaro-Winkler Dissimilarity. LM-LMD with Dice-Jaro-Winkler Dissimilarity adopts Local Maximum Distance as the prioritization algorithm and Dice-Jaro-Winkler similarity measure to evaluate distance among test cases. This work is based on the test case generated from statechart in Software Product Line (SPL) domain context. Our results are promising as LM-LMD with Dice-Jaro-Winkler Dissimilarity outperformed the original Local Maximum Distance, Global Maximum Distance and Enhanced All-yes Configuration algorithm in terms of Average Fault Detection Rate (APFD) and average prioritization time.

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.743-756
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• 2001

Component-based software development (CBSD) is a method for building large software system by integrating previously-existing software components. Software development method using components has several advantages such that reducing time to delivery and development costs, and increasing productivity etc. But integrating components developed from multiple vendors is too difficult As a result it is required the understanding on the context of use to develop reusable components. The context of use for software component of determined by software architecture. Therefore, it is possible to develop an application based on components if is based on software architecture. Also, it is essential to consider domain concepts for CBSD. To increase the reusability of components. we should develop components in a domain which is a set of related systems. In this paper, we proposed a domain architecture development methodology that supports component-based software development. Domain architecture that represents components and their relationship is produced through domain analysis and design process. We believe that component development methodology using proposed domain architecture can efficiently develop highly reusable components as well as easily develop and application using information acquired from domain architecture.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.539-545
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• 2010

Through the AUTOSAR methodology, the embedded software shall become more flexible, reusable, maintainable than ever. However, it is not mentioned about specific timing constraints of software components in AUTOSAR. There are a few basic principles for mapping runnable entities. At this point, AUTOSAR software design with optimal scheduling method is one of the enabling technologies in vehicle embedded system. This paper presents an approach based on mapping runnable entities and task scheduling design method for EPS (Electric Power Steering) software components, based on AUTOSAR. In addition, the experimental results of concurrent simulation show that the proposed scheduling technique and timing synchronization in the software component design can achieve the improved torque ripple performance and it well suited for EPS application software.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.4
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• pp.251-259
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• 2007

AUTOSAR is a partnership of automotive manufacturers and suppliers working together to develop and establish a de-facto open industry standard for automotive software architectures. In the AUTOSAR architecture, the runtime environment is at in the heart of the AUTOSAR architecture to provides the infrastructure services that enable communication between software components and between software components and basic software components. The RTE generator is an automated generation tool for AUTOSAR specification based RTE according to the ECU configuration. It generates communication API function for the software components and the basic software components like OS and COM of the application. The availability and the accuracy of the RTE generator are important for the automobile software which is based on AUTOSAR architecture, this paper proposes an architectural design of the RTE generator for auto-generation of the AUTOSAR based RTE.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.7 no.1
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• pp.133-151
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• 1997

Industrial ventilation is one of crucial engineering measures to protect workers from hazardous airborne contaminants. Designing a ventilation system is not an easy task. To solve this problem, U.S. computer programs and softwares have been developed. In Korea, a software, called as VPMC(Velocity Pressure Method Calculation), was developed by Korean Industrial Safety Corporation. Since VPMC is a DOS-based software, it could not be a user-friendly one. In this study, a Windows-based software was thus developed to overcome the difficulty in using a software for designing the ventilation system. As far as we know, this kind of Windows-based software is the first in the world. But this software should be kept being revised. The future work would include introduction of GUI(Graphic User Interface) and enhancement of editing functions by using Data-Base programs.