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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.

Band-pass signals are used everywhere in radio communications. The band-pass property makes the substitution of each RF/microwave/ optical analog signal processing possible with a low-frequency digital one in Software Defined Electronics (SDE). In SDE, the high frequency band-pass signals are transformed into the BaseBand (BB) by a universal HW device and every application is implemented in BB, entirely in software. SDE concept uses (i) the lowest sampling rate attainable theoretically and (ii) the same universal HW device in every application. The huge level of flexibility offered by the SW implementation is essential in many applications from cognitive radio to adaptive reconfigurable systems. This tutorial, written for interested readers who have no solid background in software defined radio, virtual instrumentation and SoC technology, surveys the SDE theory, uses a step-by-step approach for the derivation of BB equivalents and demonstrates the application of SDE concept in scientific research, prototyping and education.

People tend to resist changing their software even alternatives are better then the current one. This study examines the resistance to change in the use of software from the switching costs perspective based on status quo bias theory. For this study, we select Web Browsers as software. Based on the classification of switching costs into three groups (psychological, procedural, and loss), this study identifies six types of switching costs (uncertainty, commitment, learning, setup, lost performance, and sunk costs). This study tests the effects of six switching costs on user resistance to change based on the survey of 204 web browser users. The results indicate that lost performance costs and emotional costs have significant effects on user resistance to change. This research contributes towards understanding of switching costs and the effects on user resistance to change. This study also offers suggestions to software vendors for retaining their users and to organizations for managing user resistance in switching and adopting software.

소프트웨어 형상관리는 소프트웨어 제품에 기반이 되는 대규모 소프트웨어 산출물 집합을 관리하는 분야이다. 형상관리는 과거 수년 동안 빠르게 발달해왔지만, 새로운 형상관리 시스템은 여전히 요구되고 있다. 전통적인 방법을 쓰거나 형상관리에 대한 연구보다는 현재 개발 프로젝트의 필요한 전문적인 관리가 필요하다. 따라서 형상관리에 필요한 저장소의 일반적인 모델이나 형상관리에 변형에 따른 과정을 관리하고 프로그램에 연결되어 있는 프로그램의 인터페이스를 분리하여 관리하는 기법이 필요하다. 본 논문은 형상관리에 필요한 저장소를 제공하고 프로그램과 인터페이스를 분리하여 관리하는데 필요한 의사결정 시스템을 도입하였다. 따라서 필요한 형상관리의 의존도를 가지고 새로운 접근법을 시도하였다. 의존도가 높은 개별적 컴포넌트의 변형과 결합을 위해 의사결정 시스템을 이용하여 확인 및 검증을 하여 소프트웨어 개발에 필요한 형상관리를 제공하고 있다.

Software configuration management is a field of managing sets of large scale software outputs to be the basis of the software products. Configuration management has significantly improved for the past few years, yet new system is still required. Instead of using previous methods or researching about configuration management, professional management of developing project is needed. Therefore, techniques such as storage model for configuration management, management program for change procedure and management of program interface is needed. In this paper, we provide storage for configuration management and implement decision-making system to manage divided program and interface. Thus, we propose a new access method by the configuration management dependency. This paper provides configuration management for developing software to verify and classify using decision-making system for the change and combination of independent components with high dependency.

소프트웨어 제품의 정확한 인도시기를 예측하거나 효용성 및 신뢰성을 예측하기 위해서는 소 프트웨어 테스팅 과정에서 중요한 요소인 테스트 변화점를 이용하면 보다 효율적인 테스팅 작 업을 할 수 있다. 본 논문에서는 기존의 소프트웨어 신뢰성 모형인 지수 모형(Goel-Okumoto 모형)을 적용하여 변화점이 백분위수를 가질 경우를 고려하였다. 고장 간격시간으로 구성된 자료를 이용한 모수추 정 방법은 최우추정법과 일반적인 수치해석 방법인 이분법을 사용하여 모수 추정을 실시하고 효율적인 모형 선택은 편차자승합(SSE) 을 적용하여 모형들에 대한 효율적인 모형선택을 시도 하였다. 수치적인 예에서는 NTDS 자료를 사용하여 백분위수 변화점을 고려한 결과를 나열하였다.

Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process： Change-point problem. In this paper, exponential (Goel-Okumoto) model was reviewed, proposes the percentile change-point problem, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics, for the sake of efficient model, was employed. Using NTDS data, The numerical example of percentilechange-point problemi s presented.

본 연구에서는 무한고장 NHPP 로맥스 수명분포의 형상모수 변화에 따른 소프트웨어 신뢰성 모형의 속성을 새롭게 분석한 후 최적의 형상모수 조건을 제시하였다. 소프트웨어 고장현상을 분석하기 위하여 모수추정은 최우추정법을 사용하 였고, 비선형 방정식의 계산은 이분법을 적용하였다. 그 결과, 형상모수의 변화에 따른 속성을 비교하였을 때 형상모수 가 작을 수록 참값에 대한 예측능력이 우수하고, 신뢰 속성이 효율적임을 알 수 있었다. 본 연구를 통하여, 소프트웨어 개발자들은 형상모수에 근거한 소프트웨어 고장형태를 사전에 파악함으로서 신뢰도를 성장시킬 수 가 있으며, 또한, 소프 트웨어의 신뢰속성을 향상시키는데 필요한 기본정보로 활용할 수 있을 것으로 기대한다.

In this study, the optimal shape parameter condition is presented after analyzing the attributes of the software reliability model according to the change of the shape parameter of Loma life distribution with infinite fault NHPP. In order to analyze the software failure phenomena, the parametric estimation method was applied to the Maximum Likelihood Estimation method , and the nonlinear equation was applied to the bisection method. As a result, it was found that when the attributes according to the change of the shape parameter are compared, the smaller the shape parameter is, the better the prediction ability of the true value, and reliability attributes are efficient. Through this study, it is expected that software developers can increase reliability by preliminarily grasping the type of software failure based on shape parameter, and can be used as basic information to improve the software reliability attributes.

Software reliability has the greatest impact on computer system reliability and software quality. For this software reliability analysis, In this study, we compare and analyze the trends of the properties affecting the reliability according to the shape parameters of Erlang distribution based on the finite fault NHPP. Software failure time data were used to analyze software failure phenomena, the maximum likelihood estimation method was used for parameter estimation. As a result, it can be seen that the intensity function is effective because it shows a tendency to decrease with time when the shape parameters a = 1 and a = 3. However, the pattern of the mean value function showed an underestimation pattern for the true values when the shape parameters a = 1 and a = 2, but it was found to be more efficient when a = 3 because the error width from the true value was small. Also, in the reliability evaluation of the future mission time, the stable and high trend was shown when the shape parameters a = 1 and a = 3, but on the contrary, when a = 2, the reliability decreased with the failure time. Through this study, the property of finite fault NHPP Erlang model according to the change of shape parameter without existing research case was newly analyzed, and new research information that software developers can use as basic guideline was presented.

Software change is an ineluctable part of the software lifecycle. To avoid the degradation of the software quality, changes need to be performed in a controlled and rigorous manner. Most often, the management of software changes presents itself as a decision problem where software analysts have to decide whether to accept the change request and eventually how to implement the change if it is accepted. The present work’s focus is on the architectural change management. We propose a solution to this problem, which requires the software analysts to assess the impact of the software change on a set of software attributes. This assessment uses the fuzzy sets theory. An algorithm is also designed to infer a common decision out of the analysts’ very likely subjective and inaccurate individual assessments. This part of the solution employs the Cognitive Attraction Theory. The solution is validated through an industrial case study.

Effective change management requires continual assessment of the potential change impact and the organization's willingness and ability to adopt the next wave of transformation. Naturally, no change management program goes completely according to the plan: people tend to react in unexpected ways; areas of anticipated resistance may fall away; and the external environment may shift. However, supported by solid decision-making processes and using the up-to-date information from the field, the change leaders usually make the adjustments necessary to maintain momentum and drive overall business results.

Software change management is an essential discipline for enterprise IT organizations. In modern enterprises, software automates a wide variety of business processes. Changes made to software are, in effect, changes made to the business processes themselves. While the majority of enterprises have implemented basic software change management processes, these processes fall down in the face of the increased complexity of today’s business and IT environments. Truly effective and efficient software change management will require better coordination of change across geographic, organizational, functional, and technological arena of IT implemented organization. This paper presents a classification of the change management problems derived from the literature study done. This study explores software change management — the definition and implementation of defined processes to control changes made to software. It also addresses the specific problems in the change management of application software development.

As software systems become increasingly large and complex, the need increases to predict and control the effects of software changes. Our research objective is to provide an impact analysis methodology that uses historical change record for executable and non executable files in a software system to identify and prioritize potentially affected area of a system modification based on risk. Software Change Impact Analysis captures the latest information on the science and art of determining what software parts affect each other. It provides ideas for doing impact analysis better, presents a framework for the field, and focuses attention on important results. To identifies key impact analysis definitions and themes and illustrates the important themes to give a solid understanding for tackling impact analysis problems specifically in ERP. It includes study on software source code dependency analysis and software traceability analysis and shows how results from both areas can more effectively support impact analysis in software engineering repositories.

Software reliability growth models (SRGMs) investigating software debugging process have recently been developed by some researchers to estimate software reliability measures. However, these SRGMs either did not involve resource expenditures spent on fault remove process or assumed that the rate of resources consumed is constant. In practice, software fault intensity may be not continuous for many conditions. Thus, in order to address the problem, this paper develops models incorporating the resource expenditures and change-point, which spent on software debugging process. A real software failure project is demonstrated the effectiveness of proposed models, and numerical results prove new models can provide better fit and prediction.

Impact analysis predicts the parts of the software system that can be affected by changes in the system. Selecting the approach to perform impact analysis in the software development phase requires consideration of the class artifact status. Static analysis approaches do not require class artifacts to be fully developed. However, the analysis tends to overestimate the number of affected classes. So it is of little practical use. On the other hand, dynamic analysis approaches expect all the class artifacts to be fully developed. So the analysis tends to be imprecise when not all class artifacts are fully developed. This paper reviews current impact analysis techniques’ capability from the perspective of supporting the software development phase implementation. Based on this review, the needs of a new impact analysis technique for the software development phase are then constructed.

Accepting too many software change requests could contribute to expense and delay in project delivery. On the other hand rejecting the changes may increase customer dissatisfaction. Software project management might use a reliable estimation on potential impacted artifacts to decide whether to accept or reject the changes. In software development phase, an assumption that all classes in the class artifact are completely developed is impractical compared to software maintenance phase. This is due to some classes in the class artifact are still under development or partially developed. This paper extends our previous works on developing an impact analysis approach for the software development phase in automating the approach which we call it CIAT (Change Impact Analysis Tool). The significant achievements of the tool are demonstrated through an extensive experimental validation using several case studies. The experimental analysis shows improvement in the accuracy over current impact analysis results.

Interesting information and Meta-information about software systems can be extracted by analyzing their evolution histories. This information has been proved useful for understanding software evolution, predicting future changes, and performing an efficient change impact analysis. A rich source code repository is a prerequisite for a high quality evolution analysis. Nonetheless, the evolutionary information contained in current versioning systems for Aspect Oriented (AO) software is incomplete and of low quality, hence limiting the scope of AO software evolution analysis. In spite of AO Programming (AOP) characteristics, none of current versioning tools match the need of controlling and storing the AO software evolution, they do not perform well with obliviousness and quantification found in AO code. In this paper, we suggest a rule-based repository for AO software evolution, and specifically for AspectJ programming language. This repository is dedicated to handle the proper characteristics of AO paradigm. In our proposal changes are formulated as rewriting rules and recorded in the repository when they are applied. Then, this last is analyzed to detect change patterns in AspectJ software evolution. We give here, the details of our rule-based repository, as well as the proposed approach for change pattern detection. We present a tool validation and some experimentation to prove the feasibility and the efficiency of our proposals.

Impact analysis aims to quickly predict the extent of changes which will be required to software project products as a result of a potential change request. The existence of partially developed classes in the software development phase artifacts causes several challenges to the current static analysis and dynamic analysis techniques. Thus, this paper proposes a new approach that integrates between these two techniques to support those challenges. There are two main contributions of this paper: (1) a new change impact analysis approach that is able to support the software development phase; and (2) evaluation results that show the new approach gives higher accuracy of results over the selected current impact analysis approaches.

Most software reliability growth models (SRGMs) take software faults detected that may be removed immediately into consideration. In fact, it costs often considerable resources to identify the root causes of faults detected and to remove them. In additional, detection effort and correction effort have the great effect on software debugging process. The detection effort function and correction effort function are defined as resource expenditures spent on software debugging process, respectively. In this paper, we investigate software debugging process using the queue theory. We propose finite server queuing models with resource and change-point under imperfect debugging environment. A real software failure project is demonstrated the effectiveness of proposed models, and numerical results demonstrate that new models can provide better fit and prediction.

Embedded System이 고도화, 지능화되어감에 따라 이를 구동하는 Embedded Software의 역할과 크기 그리고 복잡도 역시 증가하고 있어 주어진 개발 기간동안 안정되고 품질이 보장된 Embedded Software 개발을 위해서는 기존의 방법보다 간편하고 유연하며 개발 프로세스를 지원하는 새로운 변경 관리 기법과 병렬 환경구성이 방법이 필요하게 되었다. 이에 따라, 기존의 방법을 추상화하여 사용과 관리가 용이하며 프로세스 지원이 가능한 Unified Change Management(UCM)을 Embedded Software인 Handset Platform 개발에 적용하여 병렬 개발 환경 구축과 Change Control and Problem Tracking 측면에서 기존의 방법과 비교하여 그 효용성을 살펴보고자 한다.

Change detection is a core function of remote sensing. It can be widely used in public services such as land monitoring, damage assessment from disaster, analysis of city growth, etc. However, it seems that the change detection using satellite imagery has not been fully used in public services. For the person who is in charge of public services, it seems not to be ease to implement the change detection because various functions are combined into it. So, to promote the use of the change detection in public services, the standard, the process and the method for the change detection in public services should be established. And the software which supports that will be very useful. This study aims to promote the use of satellite imagery in public services by building up the change detection process which are suitable for general public services and developing the change detection software to support the process. The software has been developed using ETRI Components for Satellite Image Processing to support the interoperability with other GIS software.

This paper describes what an operational change detection tool requires and the software which was designed and developed according to the requirements. The top requirement for the application of the software to operational change detection was identified: minimization of false detections, missing detections and operational cost. In order to meet such a requirement, the software was designed with the concept that the ultimate decision and isolation of changes must be performed manually by visual interpretation and all automatic algorithms and/or visualization techniques must be defined as support functions. In addition, the modular structure of the proposed software enables the addition of a new support function with the minimum development cost and minimum change of the operational environment.