Large-Scale Dataset of Local Java Software Build Results

Sulír, Matúš; Bacikova, Michaela; Madeja, Matej; Chodarev, Sergej; Juhár, Ján

doi:10.3390/data5030086

Cited by 14 publications

(10 citation statements)

References 26 publications

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“…First aspect includes assistance in program understanding and the second one deals with mechanisms in knowledge usage. Most findings focus on eye-tracking observations [11], however, some studies are based on data collection [12].…”

Section: Discussionmentioning

confidence: 99%

Impact of Virtual Assistant on Programming Novices’ Performance, Behavior and Motivation

Biňas,

Pietriková

2022

Acta Electrotechnica Et Informatica

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In the following study, we deal with data-driven support for novice programmers – students, working in large groups. We introduce a virtual assistant, which aims to simplify communication and feedback, sending reports and advice during the programming course. We experiment with 134 students during one semester period, and we try to understand how the virtual assistant affects novices – students. In the introduction, we state 3 hypotheses, focusing on performance, behavior, and motivation. The experiment evaluation relies on data collected throughout the semester. The results reveal the impact of the virtual assistant on novice programmers in 2 of the studied aspects – performance and motivation. This can be perceived as potential towards efficient support in programming education, especially in large groups. We also believe the study is contributional to the areas of learning analytics and program comprehension.

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Section: Discussionmentioning

confidence: 99%

Impact of Virtual Assistant on Programming Novices’ Performance, Behavior and Motivation

Biňas,

Pietriková

2022

Acta Electrotechnica Et Informatica

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“…ant, maven, or gradle) and collect the number of tests. In that case, the issue is that building such open-source projects often fails [31] and we need to build every single project and run tests what is a time-consuming task. In this paper, we try to count and especially find the location of such test cases.…”

Section: Methodsmentioning

confidence: 99%

Automating Test Case Identification in Java Open Source Projects on GitHub

Madeja

Porubãn

Bacikova

et al. 2021

cai

Self Cite

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Software testing is one of the very important Quality Assurance (QA) components. A lot of researchers deal with the testing process in terms of tester motivation and how tests should or should not be written. However, it is not known from the recommendations how the tests are written in real projects. In this paper, the following was investigated: (i) the denotation of the word "test" in different natural languages; (ii) whether the number of occurrences of the word "test" correlates with the number of test cases; and (iii) what testing frameworks are mostly used. The analysis was performed on 38 GitHub open source repositories thoroughly selected from the set of 4.3 M GitHub projects. We analyzed 20 340 test cases in 803 classes manually and 170 k classes using an automated approach. The results show that: (i) there exists a weak correlation (r = 0.655) between the number of occurrences of the word "test" and the number of test cases in a class; (ii) the proposed algorithm using static file analysis correctly detected 97 % of test cases; (iii) 15 % of the analyzed classes used main() function whose represent regular Java programs that test the production code without using any third-party framework. The identification of such tests is very complex due to implementation diversity. The results may be leveraged to more quickly identify and locate test cases in a repository, to understand practices in customized testing solutions, and to mine tests to improve program comprehension in the future.

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“…ant, maven or gradle) and collect the number of tests. In that case, the issue is that building such open source projects often fail [31] and we need to build every single project and run tests what is a time consuming task. In this paper we try to count and especially find the location of such test cases.…”

Section: Methodsmentioning

confidence: 99%

Automating Test Case Identification in Java Open Source Projects on GitHub

Madeja,

Porubän,

Bačíková

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Software testing is one of the very important Quality Assurance (QA) components. A lot of researchers deal with the testing process in terms of tester motivation and how tests should or should not be written. However, it is not known from the recommendations how the tests are actually written in real projects. In this paper the following was investigated: (i) the denotation of the test word in different natural languages; (ii) whether the test word correlates with the presence of test cases; and (iii) what testing frameworks are mostly used. The analysis was performed on 38 GitHub open source repositories thoroughly selected from the set of 4.3M GitHub projects. We analyzed 20,340 test cases in 803 classes manually and 170k classes using an automated approach. The results show that: (i) there exists weak correlation (r = 0.655) between the word test and test cases presence in a class; (ii) the proposed algorithm using static file analysis correctly detected 95% of test cases; (iii) 15% of the analyzed classes used main() function whose represent regular Java programs that test the production code without using any third-party framework. The identification of such tests is very low due to implementation diversity. The results may be leveraged to more quickly identify and locate test cases in a repository, to understand practices in customized testing solutions and to mine tests to improve program comprehension in the future.

show abstract

Large-Scale Dataset of Local Java Software Build Results

Cited by 14 publications

References 26 publications

Impact of Virtual Assistant on Programming Novices’ Performance, Behavior and Motivation

Impact of Virtual Assistant on Programming Novices’ Performance, Behavior and Motivation

Automating Test Case Identification in Java Open Source Projects on GitHub

Automating Test Case Identification in Java Open Source Projects on GitHub

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