SW 테스트 자동화 구현을 위한 핵심성공요인에 관한 연구

김성용,민대환,임성택,채봉수 한국정보기술응용학회 2020 Journal of information technology applications & m Vol.27 No.6

This study attempts to derive critical success factors and prioritize activities for implementing the automation of software test. Software testing proceeds in five steps of test plan, test case design, test scripting & test environment setup, test execution & evaluation, and test closure. From the literature, twenty influence factors in the five steps were identified. Focus Group Interviews with ten experts in software testing selected fourteen factors on the basis of importance and feasibility. Some factors were further divided to clarify their meanings and the number of influence factors finally became twenty one. A survey on the influence factors was conducted with 75 IT professionals. An importance-feasibility analysis was applied to the survey responses and classified the influence factors into four groups of essential factors, critical factors, low priority factors, and minimal factors. Essential factors include objectives for test automation, strategies for test automation, test automation training, test automation education, setting up test automation environment, setting up test environment, test automation tool selection. Critical factors include management's continued support, management's continued interest, role of automation engineers, and skills of automation engineers. This result suggests that a lot of efforts should be put into SW test plan for the successful SW test automation and SW automation should proceed in consideration with the priorities and resource consumption.

소스코드기반의 GUI 테스트 자동화 기법의 구현

문중희(Joong Hee Moon),이남용(Nam Yong Lee) 한국정보과학회 2009 정보과학회논문지 : 소프트웨어 및 응용 Vol.36 No.9

GUI 테스트의 자동화는 크게 두 가지로 분류하여 생각해 볼 수 있다. 즉, 회귀 테스트(Regression Test) 자동화와 테스트 자동화(Automated Test)이다. 전자는 테스트 케이스를 수동으로 생성하고 수행만을 자동화하는 의미를 가지는 반면, 후자는 테스트 케이스 생성 자체의 자동화도 포함한다. 점차 테스트에 소요되는 비용이 커지는 상황에서 테스트 자동화 방안을 계속적으로 모색하고 있으나 실제 적용되는 방법은 대부분 회귀 테스트에 한정되어 있다. 즉, 테스트를 처음 수행하는 단계에서는 직접 테스트 케이스를 생성하는 작업이 요구된다. 관련하여 기존의 많은 연구들이 상태 전이도를 기반으로 테스트 케이스를 자동으로 생성하는 방안을 제안하고 있으나 이 방법 역시 사람이 상태 전이도를 작성해야하는 문제를 남기게 된다. 본 논문에서는 자동화 범위를 보다 확대하여 소스코드를 기반으로 테스트 케이스를 자동으로 생성하고 수행하는 방안을 소개한다. 논문에서는 디지털 텔레비전에 탑재되는 셋탑 박스 기반의 어플리케이션 프로그램을 대상으로 연구하였으며 기존에 필요했던 수작업이 없이도 테스트 자동화를 진행하는 것이 가능하다는 것을 실제 적용 사례로 제시하였다. 물론 본 연구결과를 아직 일반화하여 적용할 수는 없을 것이다. 그러나 기존의 테스트 자동화 기법 및 연구들과 비교하여 본 연구결과는 수작업의 양을 보다 줄일 수 있었고 이후 완전한 테스트 자동화 또한 가능하다는 것을 보였다는데 그 의의가 있을 것이다. A GUI automated test can be divided into two areas. The first one is a regression test automation and the second one is an automated test. The former includes generating test cases manually and executing them automatically but the latter includes both generating test cases and executing them automatically. Costs of a software test are increasing more and more. Many companies are searching for a test automation method but most used things are limited to regression test automation. So, when testing at first, there should be test cases which are drawn up by a human. This paper explains to make test cases based on a source code and execute them automatically. In this paper, the study proceeds with a digital television set-top box application and explains to test without any effort of human. Of course, this study is far from a realization to industries. But this paper has a contribution at reducing more human efforts than the previous regression test automation and showing that later, fully automated test can be possible.

Build-up of customized test automation solutions for efficient verification of chassis systems in vehicle HILS

Jae-Hoon Lim,Jae-Jeong Kim 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10

Chassis control system should be verified and analyzed with many test scenarios by test engineer within the given time period prior to real vehicle level testing. As a result, test automation plays very important role in testing of chassis ECUs. Test automation system by current software provider cannot be modified by user and has some restrictions. This paper describes newly customized test automation solutions and the proposed automation method is introduced. First of all, the management templates for test cases are designed and parsed by customized test automation tool. And then by using this tool, test scripts which are utilized to manage the test variations and to enable test automation are created. In addition, the generation of tailored test report is automatically or manually conducted right after the selected variations by the test engineer are carried out. Hence, proposed solutions show the efficiency and improvement for testing of chassis ECUs and save the verification time and resource.

Vehicle Software Validation & Testing Automation

Dukhyun (Dan) Lee 한국자동차공학회 2008 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-

Quality of an automobile heavily depends on reliability of the automotive system software which enables most of controllers in a vehicle to work and communicate each other. In the development of an automotive embedded system, it is important to determine if the software system meets its stated requirement, specification, and if its behavior is correct. Therefore, thorough validation of the software system is one of key factors to improve automobile quality. This paper is to address an effective automotive system software validation process not only to improve automobile quality but also to avoid high warranty cost. From the development phase to the production phase of a vehicle development, required activities from each validation phase is also discussed in detail. The automotive system software validation largely is executed in two major testing environments, system and subsystem level. Content and purpose of each testing environment is included in this paper. The software validation, however, requires experienced software test engineers and timely completion of required or planned testing. Therefore, the testing automation is a way to reduce required number of experienced test engineer and to meet a validation timing target. Two ideas of the testing automation are introduced in this paper. The first idea is to develop a modeling with MATLAB or Simulink to automatically perform testing on a system test bench or subsystem test bench. The second idea is to develop an automated testing tool within AUTOSAR (AUTomotive Open System ARchitecture) to verify automotive system software in the early phase of vehicle development life cycle.

수혈 전 일상검사에서 자동화 장비 Galileo System (Immucor)의 평가

주신영,한규섭,곽영국,박경운 대한수혈학회 2011 大韓輸血學會誌 Vol.22 No.2

Background: In spite of a trend of automation for conducting most clinical laboratory tests, many blood banks are still dependent on manual tests. The aim of this study was to evaluate a full automation system called the Galileo (Immucor, USA) for conducting pretransfusion tests. Methods: From August to October in 2009, a total of 3,002 cases of ABO-RhD typing and 1698 cases of antibody screening were compared between using manual tests and the Galileo system at Seoul National University Hospital, Seoul, Korea. For the manual tests, we used the slide method for ABO-RhD typing and the anti-human immunoglobulin treated microplate method for antibody screening. The Galileo system used the microplate method for ABO-RhD typing and the solid-phase red cell adherence (SPRCA) method for antibody screening. We calculated the overall concordance rate and the false positive or negative rates regarding the manual method as a standard test and the Galileo system as a comparative test. Results: When comparing 3,002 cases of ABO-RhD typing, 52 cases (1.7%) were retested. A discrepancy between the two tests remained in 17 cases (0.6%) after repetition, which led to a concordance rate of 99.4%(2,985/3,002). On the comparison of 1,698 cases of antibody screening, 54 cases (3.2%) were retested. A discrepancy between the two tests remained for 30 cases (1.8%) and the concordance rate was 98.2%(1,615/1,698). Among the 20 false negative cases (1.2%), nine were thought to be cold antibodies with no cases of confirmed warm antibody. Conclusion: The automated Galileo system and the preexisting manual tests showed very good concordance for ABO-RhD typing and antibody screening. The Galileo system can be used with confidence for routine pretransfusion tests.

전사적 응용시스템 테스트를 위한 DB이미지 생성에 관한 연구

권오승(Ohseung Kwon),홍사능(Saneung Hong) 한국지능정보시스템학회 2011 지능정보연구 Vol.17 No.4

In general, testing DB applications is much more difficult than testing other types of software. The fact that the DB states as much as the input data influence and determine the procedures and results of program testing is one of the decisive reasons for the difficulties. In order to create and maintain proper DB states for testing, it not only takes a lot of time and efforts, but also requires extensive IT expertise and business knowledge. Despite the difficulties, there are not enough research and tools for the needed help. This article reports the result of research on automatic creation and maintenance of DB states for testing DB applications. As its core, this investigation develops an automation tool which collects relevant information from a variety of sources such as log, schema, tables and messages, combines collected information intelligently, and creates pre- and post-Images of database tables proper for application tests. The proposed procedures and tool are expected to be greatly helpful for overcoming inefficiencies and difficulties in not just unit and integration tests but including regression tests. Practically, the tool and procedures proposed in this research allows developers to improve their productivity by reducing time and effort required for creating and maintaining appropriate DB sates, and enhances the quality of DB applications since they are conducive to a wider variety of test cases and support regression tests. Academically, this research deepens our understanding and introduces new approach to testing enterprise systems by analyzing patterns of SQL usages and defining a grammar to express and process the patterns.

모델 기반 평가 방법을 이용한 지능형자동차 기능의 평가 자동화에 관한 연구

한갑수(Kab-Su Han),강호준(Ho-joon Kang),정승환(Seung-Hwan Chung),권성진(Seong-Jin Kwon),이봉현(Bong-Hyun Lee) 한국자동차공학회 2013 한국자동차공학회 부문종합 학술대회 Vol.2013 No.5

Model-based testing is a kind of black box testing that test suites are derived from behavioral model of SUT through test case generation and execute test suites automatically by model-based testing tool. A model-based testing tool uses various test generation algorithms and criteria to generate test cases. The behavioral model of SUT has to be concise enough to write and validate. Also, be precise enough to specify the behavior which is to be tested. Test cases can be generated automatically from the model and test engineer can control testing and maintain test cases easily. The abstract test cases have to be transformed into executable test cases with more specific information about SUT. Test selection criteria and lots of test generation strategies are commonly used in model-based testing. The complementary of these are key point of model-based testing. For this purpose, several state-based models are developed and test suites which derived from various test generation strategies, especially focused on transition coverage, are performed. Also, testing performances are discussed for test coverage of each test suite.

Machine Learning Frameworks for Automated Software Testing Tools : A Study

Kim, Jungho,Ryu, Joung Woo,Shin, Hyun-Jeong,Song, Jin-Hee The Korea Contents Association 2017 International Journal of Contents Vol.13 No.1

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

Machine Learning Frameworks for Automated Software Testing Tools : A Study

김정호,류정우,신현정,송진희 한국콘텐츠학회 2017 International Journal of Contents Vol.13 No.1

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

자동채점 기반 영어 말하기 시험 현황 분석

이진화,최윤덕,성민창,김혜영 한국영어교육학회 2023 ENGLISH TEACHING(영어교육) Vol.78 No.2

This study investigated the feasibility of adopting an automatic scoring system (ASS) in a domestic English-speaking education context. Scope, test items, assessment criteria, scoring methods, and reporting strategies of six overseas English-speaking tests utilizing ASSs were examined. Moreover, a comparative analysis was conducted to identify disparities between ASS-based and non-ASS-based speaking tests. Findings were: 1) some ASS-based tests utilized ASS technology throughout the assessment, while others adopted a hybrid scoring system involving human raters; 2) compared to non-ASS-based tests, ASS-based tests used more test items targeting low-level skills such as sound and forms but fewer test items targeting conversation and discourse level skills; 3) pronunciation, fluency, and vocabulary were widely employed as evaluation criteria with sparse use of organization, content, and task completion in most ASS-based tests; 4) differences were minimal in assessment criteria application and score calculation between ASS-based and non-ASS-based tests; and 5) some ASS-based tests provided criteria-specific results and feedback with total scores and proficiency levels.