• Title/Summary/Keyword: software metrics

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Quantification Methods for Software Entity Complexity with Hybrid Metrics (혼성 메트릭을 이용한 소프트웨어 개체 복잡도 정량화 기법)

  • Hong, Euii-Seok;Kim, Tae-Guun
    • The KIPS Transactions:PartD
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    • v.8D no.3
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    • pp.233-240
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    • 2001
  • As software technology is in progress and software quantification is getting more important, many metrics have been proposed to quantify a variety of system entities. These metrics can be classified into two different forms : scalar metric and metric vector. Though some recent studies pointed out the composition problem of the scalar metric form, many scalar metrics are successfully used in software development organizations due to their practical applications. In this paper, it is concluded that hybrid metric form weighting external complexity is most suitable for scalar metric form. With this concept, a general framework for hybrid metrics construction independent of the development methodologies and target system type is proposed. This framework was successfully used in two projects that quantify the analysis phase of the structured methodology and the design phase of the object oriented real-time system, respectively. Any organization can quantify system entities in a short time using this framework.

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Metrics Measurement System Supporting Quality Evaluation of Java Program (Java 프로그램의 품질평가를 지원하는 메트릭 측정 시스템)

  • Park, Ok-Cha;Yoo, Cheol-Jung;Chang, Ok-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.2
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    • pp.151-164
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    • 2001
  • Java, used as the most representative object-oriented language, isil becoming the popular language for Internet/Intranet based program development. Moreover, it is used for development language in a variety of areas such as component based development language. In the view of reuse and maintenance of developed program, quality evaluation of program is becoming a more important issue. So, metrics measurement for quality evaluation of program that is developed at present including existing Java application is necessary. However, it is necessary that whether existing object-oriented software metrics is suitable on Java program is to be validated So, in this paper, we build an automated metrics measurement system that needs to validate on object-oriented software metrics and wish to support metrics measurement that is to determine it. The purpose of this system is to support a precise quality evaluation tool. In this system, we apply the metrics classified by Briand. Briand classified the metrics by formalizing mathematically them to verify feasibility of existing object-oriented software metrics. Using the proposed system, we can make comparison and analysis of validation on existing object-oriented metrics by calculating quantitative information more rapidly from Java source program. If there is any problem in feasibility of the metrics, we can establish a suitable metrics on Java program by considering reiJ,1forcement of the existing metrics or proposing new metrics.

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A Metrics Set for Measuring Software Module Severity (소프트웨어 모듈 심각도 측정을 위한 메트릭 집합)

  • Hong, Euy-Seok
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.1
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    • pp.197-206
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    • 2015
  • Defect severity that is a measure of the impact caused by the defect plays an important role in software quality activities because not all software defects are equal. Earlier studies have concentrated on defining defect severity levels, but there have almost never been trials of measuring module severity. In this paper, first, we define a defect severity metric in the form of an exponential function using the characteristics that defect severity values increase much faster than severity levels. Then we define a new metrics set for software module severity using the number of defects in a module and their defect severity metric values. In order to show the applicability of the proposed metrics, we performed an analytical validation using Weyuker's properties and experimental validation using NASA open data sets. The results show that ms is very useful for measuring the module severity and msd can be used to compare different systems in terms of module severity.

A new approach for minimum aggregation time scheduling in wireless sensor networks (에이전트 시스템 개발도구에 관한 연구)

  • Nguyen, Dung T.;Yeoum, Sanggil;Choo, Hyunseung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.79-81
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    • 2019
  • Collecting data in wireless sensor networks in minimum time is a traditional problem which is known NP-hard. Previous studies built the schedule using the node-based or link-based metrics to prioritize the transmissions. In this work, we combine the effect of both metrics to obtain a smaller aggregation time. We compare our work with state of the art schemes and report the improvement.

A Pragmatic Framework for Predicting Change Prone Files Using Machine Learning Techniques with Java-based Software

  • Loveleen Kaur;Ashutosh Mishra
    • Asia pacific journal of information systems
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    • v.30 no.3
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    • pp.457-496
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    • 2020
  • This study aims to extensively analyze the performance of various Machine Learning (ML) techniques for predicting version to version change-proneness of source code Java files. 17 object-oriented metrics have been utilized in this work for predicting change-prone files using 31 ML techniques and the framework proposed has been implemented on various consecutive releases of two Java-based software projects available as plug-ins. 10-fold and inter-release validation methods have been employed to validate the models and statistical tests provide supplementary information regarding the reliability and significance of the results. The results of experiments conducted in this article indicate that the ML techniques perform differently under the different validation settings. The results also confirm the proficiency of the selected ML techniques in lieu of developing change-proneness prediction models which could aid the software engineers in the initial stages of software development for classifying change-prone Java files of a software, in turn aiding in the trend estimation of change-proneness over future versions.

Bayesian Network-based Probabilistic Management of Software Metrics for Refactoring (리팩토링을 위한 소프트웨어 메트릭의 베이지안 네트워크 기반 확률적 관리)

  • Choi, Seunghee;Lee, Goo Yeon
    • Journal of KIISE
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    • v.43 no.12
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    • pp.1334-1341
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    • 2016
  • In recent years, the importance of managing software defects in the implementation stage has emerged because of the rapid development and wide-range usage of intelligent smart devices. Even if not a few studies have been conducted on the prediction models for software defects, their outcomes have not been widely shared. This paper proposes an efficient probabilistic management model of software metrics based on the Bayesian network, to overcome limits such as binary defect prediction models. We expect the proposed model to configure the Bayesian network by taking advantage of various software metrics, which can help in identifying improvements for refactoring. Once the source code has improved through code refactoring, the measured related metric values will also change. The proposed model presents probability values reflecting the effects after defect removal, which can be achieved by improving metrics through refactoring. This model could cope with the conclusive binary predictions, and consequently secure flexibilities on decision making, using indeterminate probability values.

A Real-Time Monitoring Method and Dynamic Load-Balancing Metrics for CORBA Applications (코바 어플리케이션의 동적 부하 분산을 위한 실시간 모니터링 기법 및 메트릭스)

  • Choi, Chang-Ho;Kim, Soo-Dong
    • Journal of KIISE:Software and Applications
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    • v.27 no.4
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    • pp.315-326
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    • 2000
  • As Internet is being widely used as an infra of distributed applications, the most of today's softwares are changing into Internet-based distributed applications. The development methods using the middleware, like CORBA ORB, make the development of the web-based software easy. However, the performance verification method useful for an optimized software distribution is not provided at software development. Additionally, monitoring methods and metrics for dynamic load-balancing are not presented at run-time. This paper presents the method to monitor the message between objects, load metric, and metrics for load-balancing. To calculate a load of a node, we define events occurred between applications, time between the events, then extract the data related to a load. And we derive formula calculating the load from the extracted data. Then using the formula, we present the metrics for dynamic load-balancing. Moreover, we observe the utilization and efficiency of the monitoring algorithm, load metric, and load-balancing metrics.

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Development of A System for Quality Assessment and Complexity Metrics of Java programs (Java프로그램에 대한 품질 및 복잡도 메트릭스 평가시스템 구현)

  • 이상범;김경환
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.4 no.4
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    • pp.346-351
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    • 2003
  • In spite of the size and complexity of software becomes large and complicated, the demand of rapid development, cost reduction, good productivity and good quality software is increasing in these days. Many methods were proposed for efficient software development such as various Case tools. Metrics, Process improvement model (CMM, SPICE, ISO9000) and etc. However, most of them we useful to manage the whole projects rather than an individual programming. In this paper, we introduced a system for quality assessment and complexity metrics for Java programs to assess the individual programmer's quality rather than team's quality. This system shows not only the metrics value for quality assessment but also the source code and the soucture of classes simultaneously.

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Measurement of Classes Complexity in the Object-Oriented Analysis Phase (객체지향 분석 단계에서의 클래스 복잡도 측정)

  • Kim, Yu-Kyung;Park, Jai-Nyun
    • Journal of KIISE:Software and Applications
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    • v.28 no.10
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    • pp.720-731
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    • 2001
  • Complexity metrics have been developed for the structured paradigm of software development are not suitable for use with the object-oriented(OO) paradigm, because they do not support key object-oriented concepts such as inheritance, polymorphism. message passing and encapsulation. There are many researches on OO software metrics such as program complexity or design metrics. But metrics measuring the complexity of classes at the OO analysis phase are needed because they provide earlier feedback to the development project. and earlier feedback means more effective developing and less costly maintenance. In this paper, we propose the new metrics to measure the complexity of analysis classes which draw out in the analysis based on RUP(Rational Unified Process). By the collaboration complexity, is denoted by CC, we mean the maximum number of the collaborations can be achieved with each of the collaborator and determine the potential complexity. And the interface complexity, is denoted by IC, shows the difficulty related to understand the interface of collaborators each other. We verify theoretically the suggested metrics for Weyuker's nine properties. Moreover, we show the computation results for analysis classes of the system which automatically respond to questions of the user using the text mining technique. As a result of the comparison of CC and CBO and WMC suggested by Chidamber and Kemerer, the class that have highly the proposed metric value maintain the high complexity at the design phase too. And the complexity can be represented by CC and IC more than CBO and WMC. We can expect that our metrics may provide us the earlier feedback and hence possible to predict the efforts, costs and time required to remainder processes. As a result, we expect to develop the cost-effective OO software by reviewing the complexity of analysis classes in the first stage of SDLC(Software Development Life Cycle).

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Complexity Metrics for Analysis Classes in the Unified Software Development Process (Unified Process의 분석 클래스에 대한 복잡도 척도)

  • 김유경;박재년
    • The KIPS Transactions:PartD
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    • v.8D no.1
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    • pp.71-80
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    • 2001
  • Object-Oriented (OO) methodology to use the concept like encapsulation, inheritance, polymorphism, and message passing demands metrics that are different from structured methodology. There are many studies for OO software metrics such as program complexity or design metrics. But the metrics for the analysis class need to decrease the complexity in the analysis phase so that greatly reduce the effort and the cost of system development. In this paper, we propose new metrics to measure the complexity of analysis classes which draw out in the analysis phase based on Unified Process. By the collaboration complexity, is denoted by CC, we mean the maximum number of the collaborations can be achieved with each of the collaborator and detennine the potential complexity. And the interface complexity, is denoted by IC, shows the difficulty related to understand the interface of collaborators each other. We prove mathematically that the suggested metrics satisfy OO characteristics such as class size and inheritance. And we verify it theoretically for Weyuker' s nine properties. Moreover, we show the computation results for analysis classes of the system which automatically respond to questions of the it's user using the text mining technique. As we compared CC and IC to CBO and WMC, the complexity can be represented by CC and IC more than CBO and WMC. We expect to develop the cost-effective OO software by reviewing the complexity of analysis classes in the first stage of SDLC (Software Development Life Cycle).

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