Earticle

소프트웨어에 있어서 가장 중요한 요인은 소프트웨어 품질이다. 소프트웨어를 평가하는 기준은 제품의 기능적인 측면이나 사용성적인 측면도 중요하지만 이것을 모두 한꺼번에 고려한 소프트웨어 품질이 가장 중요하다고 보여진다. 현재 국내 소프트웨어의 경우도 갈수록 품질에 대한 인식이 많이 변화하고 있다. 이러한 측면에서 본 연구는 소프트웨어 품질을 평가하기 위해서 기능성, 사용성, 신뢰성, 효율성, 이식성, 유지보수성의 6가지 품질에 대해서 시험의 횟수와 시험날짜에 가장 영향을 미치는 요인을 발견하고 제품의 종류별 품질 특성의 오류수에 대한 차이 검정을 실시하여 보았다. 본 조사결과 6가지 품질특성은 시험횟수와 시험날짜에 영향을 받고 있는 것으로 조사되었으며 제품의 종류에 따라서도 나타나는 오류의 수는 다르다는 것을 확인할 수 있었다. 또한 성별에 따라서도 발견하는 오류 수는 품질 특성별로 다르게 나타난다는 것을 알 수 있었다.

Software quality is very important in software. We think, software testing is very important in point of functionality, usability. But, we have to consider about all of the software quality. We change our thinking about software quality from time to time. In this paper, we try to the best to find important factors by the number of testing dates and the number of testing in point of functionality, usability, reliability, efficiency, portability, maintainability. We study the mean of the number of faults according to products. We find the difference the number of errors by sex of tester.

Burn-in is a test procedure to find and eliminate the inherent initial failure of a product during or at the final stage of production process. Software testing is the validation and verification process which is used to cut off the faults from a software. The two have the common function and objective of "debugging". This article summarizes some significant models on the optimal hardware and software burn-in time, and provides the relevant paper lists. The need for the development of the unified burn-in policy of a hardware-software system is addressed.addressed.

소프트웨어 품질에 대한 중요성이 강조되어지고 있다. 개발에 주력하던 회사들도 소프트웨어 품질에 많은 관심을 가지고 있으며 품질을 개선하기 위한 노력을 기울이고 있다. 본 연구에서는 소프트웨어 테스팅을 통해서 얻어진 데이터를 분석하려 한다. 소프트웨어의 시험수와 시험에 소요된 날짜, 각 기능별 나타나는 발견된 오류수를 중심으로 소프트웨어 테스팅에 영향을 미치는 요인을 발견하려 한다. 또한 회귀분석을 통해서 소프트웨어 총 오류수에 가장 영향을 미치는 변인을 찾아보려 한다. 또한 테스터의 성별에 따라서 영향을 미치는 요인에 대한 분석을 하려 한다

We consider about software quality nowadays. The company considers about software quality more and more compare to software development. We analyze the software testing data in this paper. We find the software effect according to the number of testing, the number of testing date, the number of fault according to characteristics. Also, we analyze the result by regression. Also, we propose the testing effect by sex.

소프트웨어의 중요성이 높아지면서 소프트웨어 품질평가에 대한 관심이 높아지고 있다. 본 연구에서는 소 프트웨어 품질 평가를 위한 국제 표준 문서를 비교 분석하고 테스트 데이터 분석을 통한 평가 방안을 제시한다. 국제표준 ISO/IEC 9126-2의 평가 모델과 ISO/IEC 25023의 평가 모델에 대한 차이점을 비교했다. ISO/IEC 25023 의 평가모델인 8가지 품질 특성, 즉 기능성, 신뢰성, 사용성, 유지보수성, 이식성, 효율성, 상호운영성, 보안성적인 측면에서 평가 메트릭을 제시했다. 실제 테스트를 통해 얻어진 331개 자료를 분석해서 테스트 데이터의 발견된 오 류 특징을 파악했다. 또한 결함 자료를 분석하고 차이점을 파악했다. 테스트데이터가 남녀에 따라서 시험 일수나 발견하는 품질 특성별 오류의 수에는 차이가 있음을 증명하고 시험일수를 기능성, 사용성, 성별을 가지고 예측했으 며, 제품의 종류에 따라서도 오류수에 차이가 있음을 증명했다.

As software is very important, modern men are interesting software quality testing. In this paper, we analyze the Internation standard and Test data, so, we propose the testing method by analysing testing data. We compare ISO/IEC 9126-2 testing model with ISO/IEC 25023 testing model. On the basis of ISO/IEC 25023, we classify the test data and we analyze the difference of International Standard to functionality, reliability, usability, efficiency, maintainability, portability, compatability, and security. By reality 331 testing data, we classify test data, and analyze difference according to sex. We find regression model by functionality, usability and testing date and we prove difference of testing date and the number of error by tester. Also, we prove difference of the number of error in software type.

본 논문은 소프트웨어 테스트와 보안 점검의 통합적 중요성을 다루고 있다. 우선 소프트웨어 테스트는 내부적 결함을 발견하고 품질을 보장하기 위한 필수 절차이며, 이를 통해 소프트웨어의 안정성과 신뢰성을 높일 수 있다 고 강조한다. 동시에 현대 소프트웨어 환경에서의 보안 위협은 기능적 결함 이상의 심각한 위험을 초래할 수 있 기에, 보안 점검 역시 소프트웨어 개발 생명주기(SDLC) 전체에 걸쳐 수행되어야 함을 주장한다. 특히 AI 기반 코 드 생성 도구가 널리 도입됨에 따라, 개발 프로세스에 환경에 변화가 생기있어 예측하기 어려운 결함이 나타날 가능성이 커졌다. 이에 따라 전통적 테스트 기법을 넘어, AI가 생성한 코드를 검증하고 보안 취약점을 사전에 식별ㆍ차단하는 접근이 요구된다. 이에 취약점 진단, 모의해킹, 시큐어코딩 점검 등 다양한 보안 점검 기법의 특징과 수행 시점을 구분하고, 이를 기존 테스트 프로세스에 병행ㆍ통합하여 적용하는 방법론적 방향을 제시한다. 이를 통해 통합된 품질 보증(Integrated Quality Assurance) 목적으로 소프트웨어 신뢰성과 보안성을 동시에 달성할 수 있는 방법론을 제안한다.

This paper emphasizes the importance of combining software testing and security checks. Software testing is a key process for finding and fixing internal defects, which improves the stability and reliability of the software. At the same time, today’s software faces security threats that can be more serious than typical functional errors, meaning security checks should happen throughout the entire Software Development Life Cycle (SDLC). AI-based code generation tools have become common, and they can lead to new and unpredictable defects in development. Therefore, it is necessary to move beyond traditional testing methods by verifying AI-generated code and detecting security risks early. This paper outlines various security approaches, including vulnerability assessments, penetration testing, and secure coding reviews, and explains how to integrate them into existing testing processes. By using this combined method—called Integrated Quality Assurance—software teams can achieve both reliability and security at the same time.

본 연구는 소프트웨어 품질이란 측면에서 소프트웨어 시험 자료를 활용하여 예측을 위한 모델을 소개하고 소프트웨어 시험과정에서 추출한 자료를 이용해서 품질 특성별 시험 결과를 분석하려 한다. 소프트웨어 시험 평가 를 위해서는 소프트웨어 시험 평가에 소요되는 기간에 대한 분석을 실시하고 소프트웨어 품질특성별 오류 수에 대 한 분석과 성별에 따라서 소프트웨어 시험 기간에 미치는 차이를 분석한다. 본 연구에서는 기존 시험을 통해서 얻어 진 자료를 활용하여 소프트웨어 시험을 위한 소요일 수를 분석하는 모델을 제시하고 소프트웨어 종류별 6가지 품질 특성에 따른 오류수를 분석하기 위한 모델을 제시한다.

In this paper, we propose a method for estimation software quality in terms of software test data, and it is necessary to predict the period of time required for software test evaluation. We need a model to understand of estimation of software quality. In this paper, we propose a model to estimate the number of days for software test using the data obtained through the tester’s sex, and present a model for analysing the number of errors according to six quality characteristics by software type.

소프트웨어 신뢰도 성장 모델을 비동차 포아송 프로세스(NHPP)로 공식화하고, 이 모델을 이용하여 소프트웨어 신뢰도 척도에 대한 데이터 분석기법을 개발한다. 그간 여러 문헌에서 소프트웨어 신뢰도 성장 모델을 연구할 때 소프트웨어 테스트 중에 소요되는 테스트노력의 양으로서 지수함수형, 레일레이형, 웨이불형, 로지스틱형 테스트노적함수를 고려하여, 경우에 따라 이 중 하나의 적합한 형태를 사용해 왔다. 본 논문에서는 이 네 가지 형태에 대해서 최소자승평가자(LSE)와 최대가능성평가자(MLE)를 써서 파라미터를 구하는 방법을 검토한다.

본 논문에서는 소프트웨어 테스트 단계중에 발생되는 테스트노력 소요량을 고려한 소프트웨어 신뢰도 성장 모델을 제시하여 시간종속적인 테스트 노력소요량 동태를 일정 테스트 노력일 때와 웨이불 테스트 노력일 때를 비교하여 연구한다. 테스트 단계중에 소요되는 테스트 노력의 양에 대한 결함 검출비를 현재의 결함 내용에 비례하는 것으로 가정하여 모델을 비동차 포아송 과정으로 공식화하며, 이 모델을 이용하여 소프트웨어 신뢰도 척도에 대한 데이터 분석기법을 개발하도록 한다. 테스트 시간의 경과와 신뢰도와의 관계도 심도 있게 연구한다. 목표신뢰도를 만족시키는 최적발행시각을 정한다. 개발 후 테스트를 시작하기 전의 신뢰도가 어떠한 조건에 있는가를 검토하여 각 조건에 따른 최저 발행시각을 결정한다. 일정 테스트 노력 곡선과 웨이불 테스트 노력 곡선 모두에 대해서 그 조건은 목표 신뢰도를 초과하는 경우, 목표신뢰도를 초과하지는 못하지만 어느 조건 이상인 경우, 어느 조건 이하인 경우로 대별되며, 이 중에서 이상적인 경우는 두 번째 조건인 경우이다.

We propose a software-reliability growth model incoporating the amount of uniform and Weibull testing efforts during the software testing phase in this paper. The time-dependent behavior of testing effort is described by uniform and Weibull curves. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, the model is formulated by a nonhomogeneous Poisson process. Using this model the method the data analysis for software reliability measurement is developed. The optimum release time is determined by considering how the initial reliability R(x/0) would be. The conditions are R(x/0)＞Ro , Po ＞R(x/0)＞Rod and R(x/0)＜ Rod for uniform testing efforts. Ideal case is Ro ＞R(x/0)＞Rod. Likewise, it is R(x/0)≥Ro, Ro＞R(x/0)＞R(eqation omitted) and R(x/0)＜R(eqation omitted) for Weibull testing efforts. Ideal case is Ro＞R(x/0)＞R(eqation omitted).

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

산업용 시스템과 군용 무기체계에서 사용되는 임베디드 시스템들은 높은 신뢰성을 요구하며, 탑재 소프트웨어의 비중이 높아지면서 소프트웨어 품질확보를 위한 테스트의 중요성이 강화되고 있다. 임베디드 소프트웨어에 대한 테스트는 하드웨어와 소프트웨어의 결합력이 매우 높다는 특성 때문에 통합 테스트를 통해 검증되어야 한다. 기존의 통합 테스트에서는 결함이 발생하더라도 디버깅을 위한 정보를 제공해 줄 수 있는 방법이 고려되지 않아 디버깅을 수행하는 데에 많은 시간과 비용이 소모된다는 문제점이 있었다. 본 논문에서는 임베디드 소프트웨어의 통합 테스트단계에서 발생한 결함에 대해 시험 데이터와 소프트웨어 로그를 통합하여 수집하고 연관 규칙을 이용한 마이닝 기반의 분석 방법을 제공함으로써 임베디드 소프트웨어의 디버깅을 보다 원활하게 할 수 있는 방법을 제안한다. 그리고시험을 통해 제안한 방법이 단일 결함에 대해서 디버깅을 위한 정보의 식별이 가능함을 확인하였다.

The embedded systems used in industry systems and military weapon systems require high reliability, and increasing the proportion of the embedded software increases the importance of testing to ensure software quality. Testing for embedded software should be validated through integration testing because of the tight coupling of hardware and software. There was a problem with the existing integration tests that it was not considered a method to provide information for debugging, even if a defect occurred, so it was time consuming and costly to perform debugging. In this paper, we suggest a method to make debugging of embedded software more seamless by integrating test data and software logs for defects occurred in the integrated testing phase of embedded system, and by providing a mining-based analysis method using associative rules. Through the test, it is confirmed that the proposed method can identify information for debugging with respect to single defect.

Use case based Software testing concerned with testing an entire system’s functionality and its constraints. User’s requirements can be drawn in form of use cases to show the internal and external behaviour of a system. The use case has been used to test software system for different levels as well as through many ways according to nature of software. Rather than proposing a new technique, it is necessary to synthesize the existing techniques of Use case based software testing which is available in the literature. A Systematic Literature Review has been performed to investigate all the current approaches of Use case based software testing techniques. A question-wise analysis has also been presented for the researchers to investigate the effectiveness of these techniques. In results, we have discussed all the existing approaches of Use case based software testing along with its strengths & weaknesses and measure the characteristics of these approaches based on some key parameters. We have concluded the current state of the art of all the existing approaches of Use case based testing. Results are based on both types of analysis; Qualitative as well as Quantitative.

Combinatorial testing has been proved to be an efficient strategy in software testing. The research on automatic test case generation for system level based on components with constraints is a challenging but significant problem by using combinatorial testing. This paper focuses on the test case generation for system level based on components with sequential constraints. There are three main contributions: 1) the new test case generation strategy for system level is proposed based on IPOG (In-Parameter-Order-General) algorithm; 2) a filling strategy for don’t care positions is given to enhance the higher strength coverage for system level, which can improve the quality of the generated test suite; 3) a randomized post-optimization algorithm is applied to reduce the size of the test suite for system level. Experimental results show that the proposed filling strategy can improve the quality of the covering array, the post-optimization algorithm has a good optimization effect on reducing the size of the array, and trades off better between the size of the covering array and computational time than simulated annealing (SA).

Test case prioritization is basically the process of prioritizing the execution order of test cases in order to increase the fault detection rate. If fault detection rate is being gradually improved during regression testing then it will provide faster feedback to system developers which ultimately deliver the software earlier. Many of the existing test case prioritization techniques illustrated that test cases can be executed in any order but the concept of functional dependency plays an important role between test cases. In this paper we have described about testing, its types, test case prioritization and its techniques. Regression testing is normally being used to retest the component of a system that verifies that defects are removed or not from the effected part of the software after modifications. This paper enhances the hill climbing approach for test case prioritization by using functional dependency technique. This prioritization approach schedules test cases based upon functional dependency technique .Our approach is quiet efficient as compare to any other technique. Regression testing is quite popular as it helps to make the system error free after modifications.

Deadlocks are serious runtime bugs and are difficult to expose, reproduce and diagnose. Once suffering from them, programs may be afflicted with increasing response time, decreasing throughputs, or even crashes. We present Mocklinter, a dynamic deadlock detection tool to capture a deadlock as soon as it happens and spit out enough information to support source-level debugging. Mocklinter tracks the synchronization state of the target program by dynamically constructing and maintaining a lock allocation graph. Mocklinter uses this graph to decide whether a deadlock is confronted or not. Mocklinter handles all types of pthread mutexes and can detect any number of deadlocks at a time. Each deadlock captured by Mocklinter can involve any number of threads. We implemented Mocklinter in Linux-3.2.0 and evaluated it with ten applications, including Dining-Philosophers, Sshfs, SQLite, OpenLDAP, MySQL and so on, whose sizes varies from 0.1K to 1021.0K in terms of LOC. The results demonstrate effectiveness against real or artificial deadlock bugs, while incurring modest performance overhead and scaling to more than one thousand of threads.

Software testing is a set of activities that typically consumes roughly 50% of the total time and cost of testers during the software development process. Developing an enhanced technique to test mobile application becomes a necessity considering the high demand of mobile applications, android specifically, hence the need for software quality assurance. Adapting software testing model would not only lessen the cost incurred in the process of mobile application development but also increase the reliability of the software under test. In this paper, we discuss mobile application testing and its challenges. The Reweb and Testweb frameworks are also discussed followed by an adaptation model from both frameworks to improve testing of android applications. Asides from adapting these web application testing frameworks, another major contribution of our approach is the refactoring the source code before generating test cases to reduce redundancy in the test case library thereby improving the generated test case. Keywords: Refactoring, Android Application, Software

We propose a local search based approach to generate automatically test cases for programs having floating point statements. The proposed approach, called MLFP (for Multi-precision arithmetic and Local search for Floating Point constraints), adopts a local search approach to solve constraints on floating point numbers. Compared to the classical integer domain, floating point numbers F have two particular properties: they have a huge cardinality (e.g., 252 numbers in the interval [0.5, 1.0] with the "double" format), huge values (e.g. 10300), and also tiny values (e.g. 10-300). This huge combinatorial nature of the search space motivates using a local search approach. In order to find test cases containing huge or tiny numbers, such as overflow or underflow exception errors, MLFP uses the multiple precision MPFR library. Our local search approach proceeds in two steps. The first step exploits a line search algorithm to converge quickly to an approximate solution on real numbers. The second step adopts a dedicated local search algorithm on floating point numbers in order to find an exact solution, by using specific neighborhood and evaluation functions. We have implemented the MLFP approach, and we have shown its usefulness on various non trivial programs having floating point statements.

Software defects prediction was introduced to support development and maintenance activities such as improving the software quality through finding errors or patterns of errors early in the software development process. Software defects prediction is playing the role of maintenance facilitation in terms of effort, time and more importantly the cost prediction for software maintenance and evolution activities. In this research, software call graph model is used to evaluate its ability to predict quality related attributes in developed software products. As a case study, the call graph model is generated for several applications in order to represent and reflect the degree of their complexity, especially in terms of understandability, testability and maintenance efforts. This call graph model is then used to collect some software product attributes, and formulate several call graph based metrics. The extracted metrics are investigated in relation or correlation with bugs collected from customers-bug reports for the evaluated applications. Those software related bugs are compiled into dataset files to be used as an input to a data miner for classification, prediction and association analysis. Finally, the results of the analysis are evaluated in terms of finding the correlation between call graph based metrics and software products’ bugs. In this research, we assert that call graph based metrics are appropriate to be used to detect and predict software defects so the activities of maintenance and testing stages after the delivery become easier to estimate or assess.

An Integrated Medical Information System (IMIS) requires continuous customization to cope with periodic government notifications, changes in customer needs, and changing customer preferences. These systems are also modified as part of internationalization efforts. An IMIS should adhere to these situations while retaining its ability to charge medical expenses to patients and to the National Health Insurance Corporation. It should also deal with medical information such as prescriptions, medical images or videos in a manner that avoids minor defects which can lead to legal battles. Thorough testing is therefore very important. However, it is not easy to standardize medical processes, and much tailoring of IMISs has been done as a result. Moreover, new notifications should be reflected in customized IMISs operating in the hospitals within one week. It is known that sufficient testing of these systems has not been carried out. Therefore, this paper describes observations and an examination of the improvements of the test capability of such a system at a SME-level company. The assessments use a lightweight test process based on the test capability level of the company.