A Program Model Based Regression Test Selection Technique For D Programming Language

Nitesh Chouhan,Dr. Maitreyee Dutta,Dr. Mayank Singh 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.6

Software testing can be stated as the process of validating and verifying that a computer program, application and product [1]. Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Software testing, depending on the testing method employed, can be implemented at any time in the development process. Traditionally most of the test effort occurs after the requirements have been defined and the coding process has been completed. Testing can never completely identify all the defects within software. A primary purpose of testing is to detect software failures so that defects may be discovered and corrected. Testing cannot establish that a product functions properly under all conditions but can only establish that it does not function properly under specific conditions. There are many approaches to software testing. Reviews, walkthroughs, or inspections are referred to as static testing, whereas actually executing programmed code with a given set of test cases is referred to as dynamic testing. Regression testing is an important but expensive software maintenance activity performed with the aim of providing confidence in modified software. Regression test selection techniques reduce the cost of regression testing by selecting test cases for a modified program from a previously existing test suite. Regression testing is done every time when a program is modified to ensure that the modifications do not introduce new bugs into previously validated code. Regressions Testing can be done by collectively perform Regression Test Selection, Test Minimization and Test Case Priotrization Technique. An important research problem, in this context, is the selection of a relevant subset of test cases from the initial test suite. Regression test selection (RTS) techniques minimize both the regression testing time and effort. Regression test selection (RTS) techniques select a subset of valid test cases from an initial test suite (T) to test that the affected but unmodified parts of a program continue to work correctly. Use of an effective regression test selection technique can help to reduce the testing costs in environments in which a program undergoes frequent modifications. D is a new programming language. This is an object-oriented, imperative, multi-paradigm system programming language. Regression testing on D programming language still untouched by researchers. Our research attempts to bridge this gap by introducing a techniques to revalidate D programs. A framework is proposed which automates both the regression test selection and regression testing processes for D programming language. As part of this approach, special consideration is given to the analysis of the source code of D language. In our approach system dependence graph representation will be used for regression test selection for analyzing and comparing the code changes of original and modified program. First we construct a system dependence graph of the original program from the source code. When some modification is executed in a program, the constructed graph is updated to reflect the changes. Our approach in addition to capturing control and data dependencies represents the dependencies arising from object-relations. The test cases that exercise the affected model elements in the program model are selected for regression testing. Empirical studies carried out by us show that our technique selects on an average of 26.36. % more fault-revealing test cases compared to a UML based technique while incurring about 37.34% increase in regression test suite size.

Regression Test Cases selection for Object-Oriented Programs based on Affected Statements

보안공학연구지원센터(IJSEIA) 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.10

One of the most important activities in software maintenance is Regression testing. The re-execution of all test cases during the regression testing is costly. And even though several of the code based proposed techniques address procedural programs, so many of them can’t be use directly on object-oriented programs. This paper presents modification-revealing test case selection for regression testing of object-oriented software using dependence graph model analysis of the source code. The experimental evaluation of our proposed approach was done using nine programs. We measured the performances of our selection approach using precision and inclusiveness metrics. It was observed from the results that our approach increase the efficiency and effectiveness of regression testing in term of precision and inclusiveness. It was concluded that selection of modification-revealing test cases based on affected statements provides considerably better results for precision and inclusiveness compared to retest-all and random technique, and reducing the cost of regression testing.

Automated code-based test selection for software product line regression testing

Jung, Pilsu,Kang, Sungwon,Lee, Jihyun Elsevier 2019 Journal of Systems and Software Vol.158 No.-

<P><B>Abstract</B></P> <P>Regression testing for software product lines (SPLs) is challenging and can be expensive because it must ensure that all the products of a product family are correct whenever changes are made. SPL regression testing can be made efficient through a test case selection method that selects only the test cases relevant to the changes. Some approaches for SPL test case selection have been proposed but either they were not efficient by requiring intervention from human experts or they cannot be used if requirements specifications, architecture and/or traceabilities for test cases are not available or partially eroded. To address these limitations, we propose an automated method of source code-based regression test selection for SPLs. Our method reduces the repetition of the selection procedure and minimizes the in-depth analysis effort for source code and test cases based on the commonality and variability of a product family. Evaluation results of our method using six product lines show that our method reduces the overall time to perform regression testing by 14.8% ∼ 49.1% on average compared to an approach of repetitively applying Ekstazi, which is the state-of-the-art regression test selection method for a single product, to each product of a product family.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The first code-based regression test selection method for SPLs is presented. </LI> <LI> A partition technique is developed to reduce code and test cases analysis effort. </LI> <LI> To reduce redundant work in selection procedure test results are reused. </LI> <LI> The proposed method does not miss any fault-revealing tests. </LI> <LI> End-to-end time evaluation is conducted for comparison with a non-SPL approach. </LI> </UL> </P>

가치기반 접근법을 통한 테스트 케이스 우선순위기법

박현철(Hyuncheol Park),류호연(Hoyeon Ryu),백종문(Jongmoon Baik) 한국정보과학회 2009 정보과학회논문지 : 소프트웨어 및 응용 Vol.36 No.5

한번 개발된 소프트웨어는 긴 수명을 가지며, 결함이나 사용자 요구사항의 변경, 환경의 변화 등의 원인으로 인한 수많은 모듈의 수정을 통해 진화한다. 소프트웨어의 진화와 더불어, 이러한 많은 모듈의 추가와 수정에 의한 소프트웨어의 다양한 버전의 생성은 소프트웨어 품질 향상을 가로막는 주요 요인중의 하나이다. 한편 회귀테스트는 이러한 소프트웨어의 변경에 따른 초점을 둔 테스트이지만, 소프트웨어가 여러 버전을 거쳐 진화함에 따라 많은 수의 테스트 케이스의 추가 및 수정과 더불어 테스트 케이스의 전체 숫자가 급격히 증가함에 따라 비용이 많이 들기에 쉽게 수행하지 못하는 테스트이다. 이에 테스트케이스 우선순위화 기법이 등장하여 회귀테스트의 수행을 지원하였다. 그러나, 테스트 케이스 우선순위화기법에서 사용되는 우선순위의 기준이 가치중립적이거나 가치를 고려하더라도 특정한 단일 요인만을 고려하여 그 활용이 제한적이었다. 논문에서, 우리는 비용과 결함 심각도에 기반한 히스토리컬 가치 기반의 접근법을 제시하며, 이는 기존의 비용 인식 테스트 케이스 우선순위화 기법에서의 현재의 비용 및 결함 심각도를 예측하기 위하여 히스토리컬 정보를 사용하는 접근법이다. 본 논문의 공헌으로서, 제안된 접근법은 테스트의 이해관계자들이 어떻게 히스토리컬 가치가 가치의 관점에서 테스트 효과성의 향상을 위해 사용되고 있는가를 알 수 있도록 돕는다는데 있다. 결과적으로, 회귀 테스트를 수행하는 소프트웨어 테스터들은 그들의 테스트 케이스를 보다 더 효과적으로 우선순위화할 수 있기에 그들의 테스트를 통한 테스트 효과성은 향상될 수 있다. Software, once developed, has a long life and evolves through numerous additions and modifications because of the faults, the changes in user requirements, the changes in environments, and so forth. With the evolution of the software, assuring the quality of the software is getting more difficult because of numerous versions of the software. Meanwhile, regression testing has been used to support the software testing activities and assure acquiring appropriate quality through several versions of software. Regression testing, however, is too expensive because it requires lots of test cases executions and the number of test cases increases sharply as the software evolves. For this reason, several techniques are suggested to help conducting regression testing then test case prioritization technique is understood the most effective and efficient technique to support regression testing. In this paper, we propose an approach, Historical Value-Based Approach, which is based on the use of historical information to estimate the current cost and fault severity for cost-cognizant test case prioritization. As a result of the proposed approach, software testers who perform regression testing prioritize their test cases more effectively so that the test effectiveness of them can be improved in terms of APFDc.

Multiple deletion measures of test statistics inmultivariate regression

Kang-Mo Jung 한국전산응용수학회 2008 Journal of applied mathematics & informatics Vol.26 No.3-4

In multivariate regression analysis there exist many influence measures on the regression estimates. However it seems to be few of influence diagnostics on test statistics in hypothesis testing. Case-deletion approach is fundamental for investigating influence of observations on estimates or statistics. Tang and Fung (1997) derived single case-deletion of the Wilks’ ratio, Lawley-Hotelling trace, Pillai’s trace for testing a general linear hypothesis of the regression coefficients in multivariate regression. In this paper we derived more extended form of those measures to deal with joint influence among observations. A numerical example is given to illustrate the effect of joint influence on the test statistics. In multivariate regression analysis there exist many influence measures on the regression estimates. However it seems to be few of influence diagnostics on test statistics in hypothesis testing. Case-deletion approach is fundamental for investigating influence of observations on estimates or statistics. Tang and Fung (1997) derived single case-deletion of the Wilks’ ratio, Lawley-Hotelling trace, Pillai’s trace for testing a general linear hypothesis of the regression coefficients in multivariate regression. In this paper we derived more extended form of those measures to deal with joint influence among observations. A numerical example is given to illustrate the effect of joint influence on the test statistics.

RT-Selection : 텍스트 차이점과 변경 영향 분석을 이용한 회귀 테스트 선택 기법

김의섭(Eui-Sub Kim),이동아(Dong-Ah Lee),유준범(Junbeom Yoo) 한국정보과학회 2014 정보과학회논문지 : 소프트웨어 및 응용 Vol.41 No.6

회귀 테스팅은 소프트웨어의 변경이 기존 기능에 피해를 주지 않았다는 신뢰를 제공하기 위해 수행하는 테스팅 활동이다. 가장 간단하고 기본적인 방법은 기존의 모든 테스트 케이스를 이용해 다시 테스팅을 수행하는 것이지만 이 방법은 많은 시간과 비용을 필요로 한다. 회기 테스팅 중 회귀 테스트 선택(Regression test selection) 방법은 기존 테스트 케이스 중 변경을 테스트할 수 있는 테스트 케이스만을 선택하여 다시 수행하는 방법이다. 다시 수행하는 테스트 케이스의 수를 줄임으로써 비용 절감 효과를 얻을 수 있다. 본 논문은 회귀 테스트 선택의 효과적인 수행을 지원하는 기법으로 RT-Selection을 제안한다. RT-Selection은 두 가지 접근법으로 구성되어 있다. 첫째, 변경을 식별하기 위해 텍스트 차이점을 사용한다. 둘째, 테스트 케이스에 의해 실행되는 소프트웨어의 부분을 식별하기 위해 변경 영향 분석을 사용한다. 본 논문은 RT-Selection의 모든 과정과 이를 지원하는 가이드라인, 추론 규칙을 보여 주고, RT-Selection을 이용해 수행한 케이스 스터디를 보여준다. Regression testing is a testing activity that is performed to provide confidence that changes do not harm. One of simple and basic regression testing techniques is retest-all, however, it requires a lot of time and cost. The regression test selection technique identifies changes and selects a subset of previous test cases to retest the changed software. The technique reduces the number of test cases, so that it is able to reduce the time and cost for the regression testing. This paper proposes the RT-Selection that effectively performs the regression test selection. This technique consists of two approaches. First, it uses text differencing to fine the changes. Second, it uses change impact analysis to fine the software riffle that is a trace of test case in the software. This paper shows the overall process of RT-Selection and guidelines and inference rule and then it shows the case study with RT-Selection to show the feasibility of RT-Selection.

An Intelligent Framework for Test Case Prioritization Using Evolutionary Algorithm

( Mojtaba Raeisi Nejad Dobuneh ),( Dayang N. A. Jawawi ) 한국인터넷정보학회 2016 인터넷정보학회논문지 Vol.17 No.5

In a software testing domain, test case prioritization techniques improve the performance of regression testing, and arrange test cases in such a way that maximum available faults be detected in a shorter time. User-sessions and cookies are unique features of web applications that are useful in regression testing because they have precious information about the application state before and after making changes to software code. This approach is in fact a user-session based technique. The user session will collect from the database on the server side, and test cases are released by the small change configuration of a user session data. The main challenges are the effectiveness of Average Percentage Fault Detection rate (APFD) and time constraint in the existing techniques, so in this paper developed an intelligent framework which has three new techniques use to manage and put test cases in group by applying useful criteria for test case prioritization in web application regression testing. In dynamic weighting approach the hybrid criteria which set the initial weight to each criterion determines optimal weight of combination criteria by evolutionary algorithms. The weight of each criterion is based on the effectiveness of finding faults in the application. In this research the priority is given to test cases that are performed based on most common http requests in pages, the length of http request chains, and the dependency of http requests. To verify the new technique some fault has been seeded in subject application, then applying the prioritization criteria on test cases for comparing the effectiveness of APFD rate with existing techniques..

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.

A Hybrid Approach of Clustering and Time-Aware Based Novel Test Case Prioritization Technique

Geetanjali Chaurasia,Sonali Agarwal 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.4

Regression testing is an activity during the maintenance phase to validate the changes made to the software and to ensure that these changes would not affect the previously verified code or functionality. Often, regression testing is performed with limited computing resources and time budget. So, fully comprehensive testing is not possible at this stage. Test-case prioritization techniques are applied to ensure the execution of test cases in some prioritized order and to achieve some specific goals in minimum possible time like, increasing the rate of fault detection, detecting the most critical faults as early as possible etc. The main objective of this paper is to achieve higher value of average percentage of faults detected, execute the higher priority test cases before lower priority test cases and also we target to decrease the execution time for achieving the maximum value of average percentage of faults detected. We proposed a new prioritization technique that uses a clustering approach and also considers various factors like, execution time of every test case, code coverage metric, fault detection ratio, test case failure rate and code complexity metric to reorder the execution of test cases. The results of this research work will show the importance of clustering technique and various factors taken into consideration, for achieving effective prioritization of test cases. The results of implementation will subsequently show that the proposed approach is more effective than the existing coverage and clustering based prioritization techniques. From the experimental results, we found that our proposed approach achieved higher value of average percentage of faults detected than other clustering based and coverage based techniques. Also, this approach reduces the execution time taken by the prioritized test cases.

Bi-objective Test Case Selection using Abstract Snytax Tree and Tree Matching

R. Beena,S. Sarala 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.4

Software testing is a vital activity during software production to detect faults and to guarantee that the software is working properly as per the requirements.Regression testing is an activity that is carried out during the maintenance phase to ensure the quality and reliability after altering the existing version of the software. There are many techniques for performing regression testing. They are re-test all, test case minimization, test case selection and test case prioritization.The aim of this paper is to select a subset of test cases which should be run when there are siginificant changes in the original program. To extract the subset of test cases, a novel method is adopted in this research which uses executable backward static slicing.The program slices are converted into abstract syntax tree and then compared using modified simple tree matching algorithm to obtain the subset of test cases.It is clear from the result obtained that this method is very significant.