39 research outputs found

    Industry-academia collaborations in software engineering: An empirical analysis of challenges, patterns and anti-patterns in research projects

    Get PDF
    Research collaboration between industry and academia supports improvement and innovation in industry and helps to ensure industrial relevance in academic research. However, many researchers and practitioners believe that the level of joint industry-academia collaboration (IAC) in software engineering (SE) research is still relatively low, compared to the amount of activity in each of the two communities. The goal of the empirical study reported in this paper is to exploratory characterize the state of IAC with respect to a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review study. To address the above goal, we gathered the opinions of researchers and practitioners w.r.t. their experiences in IAC projects. Our dataset includes 47 opinion data points related to a large set of projects conducted in 10 different countries. We aim to contribute to the body of evidence in the area of IAC, for the benefit of researchers and practitioners in conducting future successful IAC projects in SE. As an output, the study presents a set of empirical findings and evidence-based recommendations to increase the success of IAC projects.Supported by the National Research Fund, Luxembourg FNR/P10/03. Supported by FCT (Fundação para a Ciˆencia e Tecnologia) within the Project Scope UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

    How is Exploratory Testing Used? : A State-of-the-Practice Survey

    Get PDF
    Jufo_ID: 59031 ; lyhenne ESEM.Context: Exploratory Testing has experienced a rise in popularity in the industry with the emergence of agile development practices, yet it remains unclear, in which domains and how it is used in practice. Goal: To study how software engineers understand and apply the principles of exploratory testing, as well as the specific advantages and difficulties they experience. Method: We conducted an online survey in the period June to August 2013 among Estonian and Finnish software developers and testers. Results: Our main findings are that the majority of testers, developers, and test managers using ET, (1) apply ET to usability- critical, performance-critical, security-critical and safety-critical software to a high degree; (2) use ET very flexibly in all types of test levels, activities, and phases; (3) perceive ET as an approach that supports creativity during testing and that is effective and efficient; and (4) find that ET is not easy to use and has little tool support. Conclusions: The high degree of application of ET in critical domains is particularly interesting and indicates a need for future research to obtain a better understanding of the effects of ET in these domains. In addition, our findings suggest that more support to ET users should be given (guidance and tools).Peer reviewe

    Characterizing industry-academia collaborations in software engineering: evidence from 101 projects

    Get PDF
    Research collaboration between industry and academia supports improvement and innovation in industry and helps ensure the industrial relevance of academic research. However, many researchers and practitioners in the community believe that the level of joint industry-academia collaboration (IAC) projects in Software Engineering (SE) research is relatively low, creating a barrier between research and practice. The goal of the empirical study reported in this paper is to explore and characterize the state of IAC with respect to industrial needs, developed solutions, impacts of the projects and also a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review (SLR) study. To address the above goal, we conducted an opinion survey among researchers and practitioners with respect to their experience in IAC. Our dataset includes 101 data points from IAC projects conducted in 21 different countries. Our findings include: (1) the most popular topics of the IAC projects, in the dataset, are: software testing, quality, process, and project managements; (2) over 90% of IAC projects result in at least one publication; (3) almost 50% of IACs are initiated by industry, busting the myth that industry tends to avoid IACs; and (4) 61% of the IAC projects report having a positive impact on their industrial context, while 31% report no noticeable impacts or were “not sure”. To improve this situation, we present evidence-based recommendations to increase the success of IAC projects, such as the importance of testing pilot solutions before using them in industry. This study aims to contribute to the body of evidence in the area of IAC, and benefit researchers and practitioners. Using the data and evidence presented in this paper, they can conduct more successful IAC projects in SE by being aware of the challenges and how to overcome them, by applying best practices (patterns), and by preventing anti-patterns.The authors would like to thank the researchers and practitioners who participated in this survey. João M. Fernandes was supported by FCT (Fundação para a Ciência e Tecnologia) within the Project Scope UID/CEC/00319/2013. Dietmar Pfahl was supported by the institutional research grant IUT20-55 of the Estonian Research Council. Andrea Arcuri was supported by the Research Council of Norway (grant agreement No 274385). Mika Mäntylä was partially supported by Academy of Finland grant and ITEA3 / TEKES grant

    Are Test Cases Needed? Replicated Comparison between Exploratory and Test-Case-Based Software Testing

    No full text
    Manual software testing is a widely practiced verification and validation method that is unlikely to fade away despite the advances in test automation. In the domain of manual testing, many practitioners advocate exploratory testing (ET), i.e., creative, experience-based testing without predesigned test cases, and they claim that it is more efficient than testing with detailed test cases. This paper reports a replicated experiment comparing effectiveness, efficiency, and perceived differences between ET and test-case-based testing (TCT) using 51 students as subjects, who performed manual functional testing on the jEdit text editor. Our results confirm the findings of the original study: 1) there is no difference in the defect detection effectiveness between ET and TCT, 2) ET is more efficient by requiring less design effort, and 3) TCT produces more falsepositive defect reports than ET. Based on the small differences in the experimental design, we also put forward a hypothesis that the effectiveness of the TCT approach would suffer more than ET from time pressure. We also found that both approaches had distinctive issues: in TCT, the problems were related to correct abstraction levels of test cases, and the problems in ET were related to test design and logging of the test execution and results. Finally, we recognize that TCT has other benefits over ET in managing and controlling testing in large organizations

    Defect Detection Efficiency: Test Case Based vs. Exploratory Testing

    No full text
    This paper presents a controlled experiment comparing the defect detection efficiency of exploratory testing (ET) and test case based testing (TCT). While traditional testing literature emphasizes test cases, ET stresses the individual tester’s skills during test execution and does not rely upon predesigned test cases. In the experiment, 79 advanced software engineering students performed manual functional testing on an open-source application with actual and seeded defects. Each student participated in two 90-minute controlled sessions, using ET in one and TCT in the other. We found no significant differences in defect detection efficiency between TCT and ET. The distributions of detected defects did not differ significantly regarding technical type, detection difficulty, or severity. However, TCT produced significantly more false defect reports than ET. Surprisingly, our results show no benefit of using predesigned test cases in terms of defect detection efficiency, emphasizing the need for further studies of manual testing

    20-MAD:20 years of issues and commits of Mozilla and Apache development

    No full text
    Abstract Data of long-lived and high profile projects is valuable for research on successful software engineering in the wild. Having a dataset with different linked software repositories of such projects, enables deeper diving investigations. This paper presents 20-MAD, a dataset linking the commit and issue data of Mozilla and Apache projects. It includes over 20 years of information about 765 projects, 3.4M commits, 2.3M issues, and 17.3M issue comments, and its compressed size is over 6 GB. The data contains all the typical information about source code commits (e.g., lines added and removed, message and commit time) and issues (status, severity, votes, and summary). The issue comments have been pre-processed for natural language processing and sentiment analysis. This includes emoticons and valence and arousal scores. Linking code repository and issue tracker information, allows studying individuals in two types of repositories and provide more accurate time zone information for issue trackers as well. To our knowledge, this the largest linked dataset in size and in project lifetime that is not based on GitHub
    corecore