Roland H. Untch

Bio: Roland H. Untch is an academic researcher from Middle Tennessee State University. The author has contributed to research in topics: Test case & Collaborative learning. The author has an hindex of 10, co-authored 15 publications receiving 2689 citations.

Prioritizing test cases for regression testing

Abstract: Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness at meeting some performance goal. Various goals are possible; one involves rate of fault detection, a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during testing can provide faster feedback on the system under test and let software engineers begin correcting faults earlier than might otherwise be possible. One application of prioritization techniques involves regression testing, the retesting of software following modifications; in this context, prioritization techniques can take advantage of information gathered about the previous execution of test cases to obtain test case orderings. We describe several techniques for using test execution information to prioritize test cases for regression testing, including: 1) techniques that order test cases based on their total coverage of code components; 2) techniques that order test cases based on their coverage of code components not previously covered; and 3) techniques that order test cases based on their estimated ability to reveal faults in the code components that they cover. We report the results of several experiments in which we applied these techniques to various test suites for various programs and measured the rates of fault detection achieved by the prioritized test suites, comparing those rates to the rates achieved by untreated, randomly ordered, and optimally ordered suites.

An experimental determination of sufficient mutant operators

Abstract: Mutation testing is a technique for unit-testing software that, although powerful, is computationally expensive, The principal expense of mutation is that many variants of the test program, called mutants, must be repeatedly executed. This article quantifies the expense of mutation in terms of the number of mutants that are created, then proposes and evaluates a technique that reduces the number of mutants by an order of magnitude. Selective mutation reduces. the cost of mutation testing by reducing the number of mutants, This article reports experimental results that compare selective mutation testing with standard, or nonselective, mutation testing, and results that quantify the savings achieved by selective mutation testing, The results support the hypothesis that selective mutation is almost as strong as nonselective mutation: in experimental trials selective mutation provides almost the same coverage as nonselective mutation. with a four-fold or more reduction in the number of mutants.

Test case prioritization: an empirical study

Abstract: Test case prioritization techniques schedule test cases for execution in an order that attempts to maximize some objective function. A variety of objective functions are applicable; one such function involves rate of fault detection-a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during regression testing can provide faster feedback on a system under regression test and let debuggers begin their work earlier than might otherwise be possible. In this paper we describe several techniques for prioritizing test cases and report our empirical results measuring the effectiveness of these techniques for improving rate of fault detection. The results provide insights into the tradeoffs among various techniques for test case prioritization.

Mutation analysis using mutant schemata

Abstract: Mutation analysis is a powerful technique for assessing and improving the quality of test data used to unit test software. Unfortunately, current automated mutation analysis systems suffer from severe performance problems. This paper presents a new method for performing mutation analysis that uses program schemata to encode all mutants for a program into one metaprogram, which is subsequently compiled and run at speeds substantially higher than achieved by previous interpretive systems. Preliminary performance improvements of over 300% are reported. This method has the additional advantages of being easier to implement than interpretive systems, being simpler to port across a wide range of hardware and software platforms, and using the same compiler and run-time support system that is used during development and/or deployment.

Engaging Computer Science Students through Gamification in an Online Social Network Based Collaborative Learning Environment

Abstract: voluntary and active as was hoped for. Even though there is a group of students actively participating social activities in PeerSpace by posting helpful, useful, and/or insightful posts, and join in discussions, there are also students who participate PeerSpace activities mainly because they are required as part of the class assignments. Analysis of data collected from controlled experiments show that there is a direct, positive relationship between the amount of usage of PeerSpace and the benefit gained from this learning community (4). The question for us is "How to better engage the students in PeerSpace social and learning activities?". This paper describes our approach to this question by introducing game mechanics to promote the students" learning by encouraging them to:  participate more in social and learning activities,  develop a stronger sense of community, and  be more willing to help each other on academic and social matters. The approach we took is called "gamification". Gamification uses game mechanics, dynamics, and frameworks to promote desired behaviors. Gamification attempts to harness the motivational power of games and apply it to real-world problems (5). It is a new concept but has received very warm welcome by many companies, such as Google, Groupon, Photoshop, Pandora, FourSquare, Zipcar, Steam, etc. These companies used gamification features in their web sites to better engage their loyal customers and to attract new customers to their sites (6)-(5). In this work, we present how gamification may be applied for education purposes to better engage Computer Science students to participate in social and learning activities in an online learning environment. A number of gamification features were added to PeerSpace to reward the students for performing social activities, help them make new friends by playing turn-based games with different students, and to engage in peer-learning and peer-tutoring activities. Section II presents the background information of PeerSpace and gamification used for education. Section III discusses the various gamification features that have been implemented in PeerSpace. Section IV discusses the preliminary experiments and results obtained in assessing the effects of the gamification features in engaging students. Section V presents the conclusions of this work.

An Analysis and Survey of the Development of Mutation Testing

Abstract: Mutation Testing is a fault-based software testing technique that has been widely studied for over three decades The literature on Mutation Testing has contributed a set of approaches, tools, developments, and empirical results This paper provides a comprehensive analysis and survey of Mutation Testing The paper also presents the results of several development trend analyses These analyses provide evidence that Mutation Testing techniques and tools are reaching a state of maturity and applicability, while the topic of Mutation Testing itself is the subject of increasing interest

Regression testing minimization, selection and prioritization: a survey

Abstract: Regression testing is a testing activity that is performed to provide confidence that changes do not harm the existing behaviour of the software. Test suites tend to grow in size as software evolves, often making it too costly to execute entire test suites. A number of different approaches have been studied to maximize the value of the accrued test suite: minimization, selection and prioritization. Test suite minimization seeks to eliminate redundant test cases in order to reduce the number of tests to run. Test case selection seeks to identify the test cases that are relevant to some set of recent changes. Test case prioritization seeks to order test cases in such a way that early fault detection is maximized. This paper surveys each area of minimization, selection and prioritization technique and discusses open problems and potential directions for future research. Copyright © 2010 John Wiley & Sons, Ltd.

Prioritizing test cases for regression testing

Abstract: Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness at meeting some performance goal. Various goals are possible; one involves rate of fault detection, a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during testing can provide faster feedback on the system under test and let software engineers begin correcting faults earlier than might otherwise be possible. One application of prioritization techniques involves regression testing, the retesting of software following modifications; in this context, prioritization techniques can take advantage of information gathered about the previous execution of test cases to obtain test case orderings. We describe several techniques for using test execution information to prioritize test cases for regression testing, including: 1) techniques that order test cases based on their total coverage of code components; 2) techniques that order test cases based on their coverage of code components not previously covered; and 3) techniques that order test cases based on their estimated ability to reveal faults in the code components that they cover. We report the results of several experiments in which we applied these techniques to various test suites for various programs and measured the rates of fault detection achieved by the prioritized test suites, comparing those rates to the rates achieved by untreated, randomly ordered, and optimally ordered suites.

Introduction to Software Testing

Abstract: Extensively class tested, this text takes an innovative approach to explaining the process of software testing: it defines testing as the process of applying a few well-defined, general-purpose test criteria to a structure or model of the software. The structure of the text directly reflects the pedagogical approach and incorporates the latest innovations in testing, including techniques to test modern types of software such as OO, web applications, and embedded software.