Directed test suite augmentation: an empirical investigation

Test suite augmentation techniques are used in regression testing to identify code elements in a modified program that are not adequately tested and to generate test cases to cover those elements. A defining feature of test suite augmentation techniques is the potential for reusing existing regression test suites. Our preliminary work suggests that several factors influence the efficiency and effectiveness of augmentation techniques that perform such reuse. These include the order in which target code elements are considered while generating test cases, the manner in which existing regression test cases and newly generated test cases are used, and the algorithm used to generate test cases. In this work, we present the results of two empirical studies examining these factors, considering two test case generation algorithms (concolic and genetic). The results of our studies show that the primary factor affecting augmentation using these approaches is the test case generation algorithm utilized; this affects both cost and effectiveness. The manner in which existing and newly generated test cases are utilized also has a substantial effect on efficiency and in some cases a substantial effect on effectiveness. The order in which target code elements are considered turns out to have relatively few effects when using concolic test case generation but in some cases influences the efficiency of genetic test case generation. The results of our first study, on four relatively small programs using a large number of test suites, are supported by our second study of a much larger program available in multiple versions. Together, the studies reveal a potential opportunity for creating a more cost‐effective hybrid augmentation approach leveraging both concolic and genetic test case generation techniques, while appropriately utilizing our understanding of the factors that affect them. Copyright © 2014 John Wiley & Sons, Ltd.     

Prioritizing test cases with string distances

Test case prioritisation aims at finding an ordering which enhances a certain property of an ordered test suite. Traditional techniques rely on the availability of code or a specification of the program under test. We propose to use string distances on the text of test cases for their comparison and elaborate a prioritisation algorithm. Such a prioritisation does not require code or a specification and can be useful for initial testing and in cases when code is difficult to instrument. In this paper, we also report on experiments performed on the “Siemens Test Suite”, where the proposed prioritisation technique was compared with random permutations and four classical string distance metrics were evaluated. The obtained results, confirmed by a statistical analysis, indicate that prioritisation based on string distances is more efficient in finding defects than random ordering of the test suite: the test suites prioritized using string distances are more efficient in detecting the strongest mutants, and, on average, have a better APFD than randomly ordered test suites. The results suggest that string distances can be used for prioritisation purposes, and Manhattan distance could be the best choice.     

XML-manipulating test case prioritization for XML-manipulating services

A web service may evolve autonomously, making peer web services in the same service composition uncertain as to whether the evolved behaviors are compatible with its original collaborative agreement. Although peer services may wish to conduct regression testing to verify the agreed collaboration, the source code of the former service may be inaccessible to them. Owing to the black-box nature of peer services, traditional code-based approaches to regression testing are inapplicable. In addition, traditional techniques assume that a regression test suite for verifying a web service is available. The location to store a regression test suite is also a problem. On the other hand, we note that the rich interface specifications of a web service provide peer services with a means to formulate black-box testing strategies. In this paper, we provide a strategy for black-box service-oriented testing. We also formulate new test case prioritization strategies using tags embedded in XML messages to reorder regression test cases, and reveal how the test cases use the interface specifications of web services. We experimentally evaluate the effectiveness of these black-box strategies in revealing regression faults in modified WS-BPEL programs. The results show that the new techniques can have a high chance of outperforming random ordering. Moreover, our experiment shows that prioritizing test cases based on WSDL tag coverage can achieve a smaller variance than that based on the number of tags in XML messages in regression test cases, even though their overall fault detection rates are similar.     

Improving Fault Detection Capability by Selectively Retaining Test Cases during Test Suite Reduction

Software testing is a critical part of software development. As new test cases are generated over time due to software modifications, test suite sizes may grow significantly. Because of time and resource constraints for testing, test suite minimization techniques are needed to remove those test cases from a suite that, due to code modifications over time, have become redundant with respect to the coverage of testing requirements for which they were generated. Prior work has shown that test suite minimization with respect to a given testing criterion can significantly diminish the fault detection effectiveness (FDE) of suites. We present a new approach for test suite reduction that attempts to use additional coverage information of test cases to selectively keep some additional test cases in the reduced suites that are redundant with respect to the testing criteria used for suite minimization, with the goal of improving the FDE retention of the reduced suites. We implemented our approach by modifying an existing heuristic for test suite minimization. Our experiments show that our approach can significantly improve the FDE of reduced test suites without severely affecting the extent of suite size reduction     

回归测试中的测试用例优先排序技术述评

测试用例优先排序(test case prioritization,简称TCP)问题是回归测试研究中的一个热点.通过设定特定排序准则,对测试用例进行排序以优化其执行次序,旨在最大化排序目标,例如最大化测试用例集的早期缺陷检测速率.TCP问题尤其适用于因测试预算不足以致不能执行完所有测试用例的测试场景.首先对TCP问题进行描述,并依次从源代码、需求和模型这3个角度出发对已有的TCP技术进行分类;然后对一类特殊的TCP问题(即测试资源感知的TCP问题)的已有研究成果进行总结;随后依次总结实证研究中常用的评测指标、评测数据集和缺陷类型对实证研究结论的影响;接着依次介绍TCP技术在一些特定测试领域中的应用,包括组合测试、事件驱动型应用测试、Web服务测试和缺陷定位等;最后对下一步工作进行展望.     

B-Refactoring: Automatic test code refactoring to improve dynamic analysis

Context: Developers design test suites to verify that software meets its expected behaviors. Many dynamic analysis techniques are performed on the exploitation of execution traces from test cases. In practice, one test case may imply various behaviors. However, the execution of a test case only yields one trace, which can hide the others.Objective: In this article, we propose a new technique of test code refactoring, called B-Refactoring. The idea behind B-Refactoring is to split a test case into small test fragments, which cover a simpler part of the control flow to provide better support for dynamic analysis.Method: For a given dynamic analysis technique, B-Refactoring monitors the execution of test cases and constructs small test cases without loss of the testability. We apply B-Refactoring to assist two existing analysis tasks: automatic repair of if-condition bugs and automatic analysis of exception contracts.Results: Experimental results show that B-Refactoring can effectively improve the execution traces of the test suite. Real-world bugs that could not be previously fixed with the original test suites are fixed after applying B-Refactoring; meanwhile, exception contracts are better verified via applying B-Refactoring to original test suites.Conclusions: We conclude that applying B-Refactoring improves the execution traces of test cases for dynamic analysis. This improvement can enhance existing dynamic analysis tasks.     

Analysis of test suite reduction with enhanced tie-breaking techniques

Test suite minimization techniques try to remove redundant test cases of a test suite. However, reducing the size of a test suite might reduce its ability to reveal faults. In this paper, we present a novel approach for test suite reduction that uses an additional testing criterion to break the ties in the minimization process. We integrated the proposed approach with two existing algorithms and conducted experiments for evaluation. The experiment results show that our approach can improve the fault detection effectiveness of reduced suites with a negligible increase in the size of the suites. Besides, under specific conditions, the proposed approach can also accelerate the process of minimization.     

Test case selection for black-box regression testing of database applications

ContextThis paper presents an approach for selecting regression test cases in the context of large-scale database applications. We focus on a black-box (specification-based) approach, relying on classification tree models to model the input domain of the system under test (SUT), in order to obtain a more practical and scalable solution. We perform an experiment in an industrial setting where the SUT is a large database application in Norway’s tax department.ObjectiveWe investigate the use of similarity-based test case selection for supporting black box regression testing of database applications. We have developed a practical approach and tool (DART) for functional black-box regression testing of database applications. In order to make the regression test approach scalable for large database applications, we needed a test case selection strategy that reduces the test execution costs and analysis effort. We used classification tree models to partition the input domain of the SUT in order to then select test cases. Rather than selecting test cases at random from each partition, we incorporated a similarity-based test case selection, hypothesizing that it would yield a higher fault detection rate.MethodAn experiment was conducted to determine which similarity-based selection algorithm was the most suitable in selecting test cases in large regression test suites, and whether similarity-based selection was a worthwhile and practical alternative to simpler solutions.ResultsThe results show that combining similarity measurement with partition-based test case selection, by using similarity-based test case selection within each partition, can provide improved fault detection rates over simpler solutions when specific conditions are met regarding the partitions.ConclusionsUnder the conditions present in the experiment the improvements were marginal. However, a detailed analysis concludes that the similarity-based selection strategy should be applied when a large number of test cases are contained in each partition and there is significant variability within partitions. If these conditions are not present, incorporating similarity measures is not worthwhile, since the gain is negligible over a random selection within each partition.     

Generating Event Sequence-Based Test Cases Using GUI Runtime State Feedback

This paper presents a fully automatic model-driven technique to generate test cases for Graphical user interfaces (GUIs)-based applications. The technique uses feedback from the execution of a “seed test suite,” which is generated automatically using an existing structural event interaction graph model of the GUI. During its execution, the runtime effect of each GUI event on all other events pinpoints event semantic interaction (ESI) relationships, which are used to automatically generate new test cases. Two studies on eight applications demonstrate that the feedback-based technique 1) is able to significantly improve existing techniques and helps identify serious problems in the software and 2) the ESI relationships captured via GUI state yield test suites that most often detect more faults than their code, event, and event-interaction-coverage equivalent counterparts.     

Call-Stack Coverage for GUI Test Suite Reduction

Graphical user interfaces (GUIs) are used as front ends to most of today's software applications. The event-driven nature of GUIs presents new challenges for testing. One important challenge is test suite reduction. Conventional reduction techniques/tools based on static analysis are not easily applicable due to the increased use of multilanguage GUI implementations, callbacks for event handlers, virtual function calls, reflection, and multithreading. Moreover, many existing techniques ignore code in libraries and fail to consider the context in which event handlers execute. Consequently, they yield GUI test suites with seriously impaired fault-detection abilities. This paper presents a reduction technique based on the call-stack coverage criterion. Call stacks may be collected for any executing program with very little overhead. Empirical studies in this paper compare reduction based on call-stack coverage to reduction based on line, method, and event coverage, including variations that control for the size and optional consideration of library methods. These studies show that call-stack-based reduction provides unique trade-offs between the reduction in test suite size and the loss of fault detection effectiveness, which may be valuable in practice. Additionally, an analysis of the relationship between coverage requirements and fault-revealing test cases is presented.     

Test suite reduction methods that decrease regression testing costs by identifying irreplaceable tests

ContextIn software development and maintenance, a software system may frequently be updated to meet rapidly changing user requirements. New test cases will be designed to ensure the correctness of new or modified functions, thus gradually increasing the test suite’s size. Test suite reduction techniques aim to decrease the cost of regression testing by removing the redundant test cases from the test suite and then obtaining a representative set of test cases that still yield a high level of code coverage.ObjectiveMost of the existing reduction algorithms focus on decreasing the test suite’s size. Yet, the differences in execution costs among test cases are usually significant and it may take a lot of execution time to run a test suite consisting of a few long-running test cases. This paper presents and empirically evaluates cost-aware algorithms that can produce the representative sets with lower execution costs.MethodWe first use a cost-aware test case metric, called Irreplaceability, and its enhanced version, called EIrreplaceability, to evaluate the possibility that each test case can be replaced by others during test suite reduction. Furthermore, we construct a cost-aware framework that incorporates the concept of test irreplaceability into some well-known test suite reduction algorithms.ResultsThe effectiveness of the cost-aware framework is evaluated via the subject programs and test suites collected from the Software-artifact Infrastructure Repository — frequently chosen benchmarks for experimentally evaluating test suite reduction methods. The empirical results reveal that the presented algorithms produce representative sets that normally incur a low cost to yield a high level of test coverage.ConclusionThe presented techniques indeed enhance the capability of the traditional reduction algorithms to reduce the execution cost of a test suite. Especially for the additional Greedy algorithm, the presented techniques decrease the costs of the representative sets by 8.10–46.57%.     

On the adoption of MC/DC and control-flow adequacy for a tight integration of program testing and statistical fault localization

ContextTesting and debugging consume a significant portion of software development effort. Both processes are usually conducted independently despite their close relationship with each other. Test adequacy is vital for developers to assure that sufficient testing effort has been made, while finding all the faults in a program as soon as possible is equally important. A tight integration between testing and debugging activities is essential.ObjectiveThe paper aims at finding whether three factors, namely, the adequacy criterion to gauge a test suite, the size of a prioritized test suite, and the percentage of such a test suite used in fault localization, have significant impacts on integrating test case prioritization techniques with statistical fault localization techniques.MethodWe conduct a controlled experiment to investigate the effectiveness of applying adequate test suites to locate faults in a benchmark suite of seven Siemens programs and four real-life UNIX utility programs using three adequacy criteria, 16 test case prioritization techniques, and four statistical fault localization techniques. We measure the proportion of code needed to be examined in order to locate a fault as the effectiveness of statistical fault localization techniques. We also investigate the integration of test case prioritization and statistical fault localization with postmortem analysis.ResultThe main result shows that on average, it is more effective for a statistical fault localization technique to utilize the execution results of a MC/DC-adequate test suite than those of a branch-adequate test suite, and is in turn more effective to utilize the execution results of a branch-adequate test suite than those of a statement-adequate test suite. On the other hand, we find that none of the fault localization techniques studied can be sufficiently effective in suggesting fault-relevant statements that can fit easily into one debug window of a typical IDE.ConclusionWe find that the adequacy criterion and the percentage of a prioritized test suite utilized are major factors affecting the effectiveness of statistical fault localization techniques. In our experiment, the adoption of a stronger adequacy criterion can lead to more effective integration of testing and debugging.     

Regression testing minimization,selection and prioritization: a survey

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.     

A systematic literature review on the detection of smells and their evolution in object-oriented and service-oriented systems

This systematic literature review paper investigates the key techniques employed to identify smells in different paradigms of software engineering from object-oriented (OO) to service-oriented (SO). In this review, we want to identify commonalities and differences in the identification of smells in OO and SO systems. Our research method relies on an automatic search from the relevant digital libraries to find the studies published since January 2000 on smells until December 2017. We have conducted a pilot and author-based search that allows us to select the 78 most relevant studies after applying inclusion and exclusion criteria. We evaluated the studies based on the smell detection techniques and the evolution of different methodologies in OO and SO. Among the 78 relevant studies selected, we have identified six different studies in which linguistic source code analysis received less attention from the researchers as compared to the static source code analysis. Smells like the yo-yo problem, unnamed coupling, intensive coupling, and interface bloat received considerably less attention in the literature. We also identified a catalog of 30 smells infrequently reported for SO systems and that require further attention. Moreover, a suite of 20 smells reported for SO systems can also be detected using static source code metrics in OO. Finally, our review highlighted three major research trends that are further subdivided into 20 research patterns initiating the detection of smells toward their correction.     

Improving the effectiveness of test suite reduction for user-session-based testing of web applications

ContextTest suite reduction is the problem of creating and executing a set of test cases that are smaller in size but equivalent in effectiveness to an original test suite. However, reduced suites can still be large and executing all the tests in a reduced test suite can be time consuming.ObjectiveWe propose ordering the tests in a reduced suite to increase its rate of fault detection. The ordered reduced test suite can be executed in time constrained situations, where, even if test execution is stopped early, the best test cases from the reduced suite will already be executed.MethodIn this paper, we present several approaches to order reduced test suites using experimentally verified prioritization criteria for the domain of web applications. We conduct an empirical study with three subject applications and user-session-based test cases to demonstrate how ordered reduced test suites often make a practical contribution. To enable comparison between test suites of different sizes, we develop Mod_APFD_C, a modification of the traditional prioritization effectiveness measure.ResultsWe find that by ordering the reduced suites, we create test suites that are more effective than unordered reduced suites. In each of our subject applications, there is at least one ordered reduced suite that outperforms the best unordered reduced suite and the best prioritized original suite.ConclusionsOur results show that when a tester does not have enough time to execute the entire reduced suite, executing an ordered reduced suite often improves the rate of fault detection. By coupling the underlying system’s characteristics with observations from our study on the criteria that produce the best ordered reduced suites, a tester can order their reduced test suites to obtain increased testing effectiveness.     

Prioritizing test cases for regression testing

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     

Empirical studies of a safe regression test selection technique

Regression testing is an expensive testing procedure utilized to validate modified software. Regression test selection techniques attempt to reduce the cost of regression testing by selecting a subset of a program's existing test suite. Safe regression test selection techniques select subsets that, under certain well-defined conditions, exclude no tests (from the original test suite) that if executed would reveal faults in the modified software. Many regression test selection techniques, including several safe techniques, have been proposed, but few have been subjected to empirical validation. This paper reports empirical studies on a particular safe regression test selection technique, in which the technique is compared to the alternative regression testing strategy of running all tests. The results indicate that safe regression test selection can be cost-effective, but that its costs and benefits vary widely based on a number of factors. In particular, test suite design can significantly affect the effectiveness of test selection, and coverage-based test suites may provide test selection results superior to those provided by test suites that are not coverage-based     

基于冗余测试用例的最小测试用例集生成方法

提出一种最小测试用例集的生成方法。保留在某个测试标准下冗余,但在其他测试标准下不冗余的测试用例,即在测试用例集简化期间通过有选择性地保留测试用例来生成一个测试用例集。与已有方法相比,该方法能在不影响测试组大小范围的情况下有效提高错误检测效率。     

On similarity-awareness in testing-based fault localization

In the process of software development and maintenance, software debugging is an inevitable and time-consuming task. To accelerate software debugging, various approaches have been proposed to automate fault localization. Among them, testing-based fault-localization approaches are most promising, which use the execution information of many test cases to localize the faults. However, these existing testing-based fault-localization approaches ignore the similarity between test cases, which may harm the effectiveness of these approaches according to our previous research. Therefore, in this paper we propose a similarity-aware fault-localization approach, which takes each test case as a fuzzy set to deal with the similarity between test cases and calculates statements’ suspicions based on the probability theory. To investigate whether SAFL can address the similarity issue effectively, we manually injected redundant test cases in a test suite and performed an experimental study on the original test suite and the test suite with redundancy, respectively. The experimental results demonstrate that in our experiments SAFL is an effective fault-localization approach, whether there is manually injected redundancy in the test suite. To compare SAFL with most existing testing-based fault-localization approaches, we performed another experimental study on Siemens program suite, which is extensively used in the evaluation of many other testing-based fault-localization approaches. This experimental study confirms the effectiveness of SAFL. Based on the two experimental studies, it seems that in our experiments SAFL cannot only deal with test suites containing much redundancy effectively but also perform effectively for test suites without much redundancy. A preliminary version of this paper appears in (Hao et al. 2005a).     

Testing from a stochastic timed system with a fault model

In this paper we present a method for testing a system against a non-deterministic stochastic finite state machine. As usual, we assume that the functional behaviour of the system under test (SUT) is deterministic but we allow the timing to be non-deterministic. We extend the state counting method of deriving tests, adapting it to the presence of temporal requirements represented by means of random variables. The notion of conformance is introduced using an implementation relation considering temporal aspects and the limitations imposed by a black-box framework. We propose a new group of implementation relations and an algorithm for generating a test suite that determines the conformance of a deterministic SUT with respect to a non-deterministic specification. We show how previous work on testing from stochastic systems can be encoded into the framework presented in this paper as an instantiation of our parameterized implementation relation. In this setting, we use a notion of conformance up to a given confidence level.