Pragmatic Software Testing Education

Aniche, Maurício; Hermans, Felienne; Deursen, Arie van

doi:10.1145/3287324.3287461

Cited by 42 publications

(16 citation statements)

References 37 publications

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“…Throughout our software testing course, teams worked on JPacman [13], an educational implementation of the PacMan game in Java that contains several opportunities for different testing techniques to be applied. All assignments included the oretical and reflexive questions about software testing (which teams answered in a written report), as well as technical questions (which teams answered by submitting source code).…”

Section: A Teams and Assignmentsmentioning

confidence: 99%

“…The reader can find details of our lab assignments and rubrics in the online appendix [14]. We also refer the reader to another publication of ours that describes the educational methodology we follow in the course [13]. In a nutshell, our course is composed of 14-16 lectures, divided over 8-9 weeks, that mix theory (i.e., the different testing techniques, how they work, scientific evidence) and practice (i.e., where students see snippets of code and how to test it using state-of-the-art testing tools).…”

Section: A Teams and Assignmentsmentioning

confidence: 99%

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Grading 600+ Students: A Case Study on Peer and Self Grading

Aniche

Mulder

Hermans³

2021

2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)

Self Cite

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Grading large classes has become a challenging and expensive task for many universities. The Delft University of Technology (TU Delft), located in the Netherlands, has observed a large increase in student numbers over the past few years. Given the large growth of the student population, grading all the submissions results in high costs.We made use of self and peer grading in the 2018-2019 edition of our software testing course. Students worked in teams of two, and self and peer graded three assignments in our course. We ended up with 906 self and peer graded submissions, which we compared to 248 submissions that were graded by our TAs. In this paper, we report on the differences we observed between self, peer, and TA grading.Our findings show that: (i) self grades tend to be 8-10% higher than peer grades on average, (ii) peer grades seem to be a good approximator of TA grades; in cases where self and peer grade differ significantly, the TA grade seems to lie in between, and (iii) the gender and the nationality of the student do not seem to affect self and peer grading.

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Section: A Teams and Assignmentsmentioning

confidence: 99%

Section: A Teams and Assignmentsmentioning

confidence: 99%

Grading 600+ Students: A Case Study on Peer and Self Grading

Aniche

Mulder

Hermans³

2021

2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)

Self Cite

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“…Unfortunately, many software engineers have inadequate training in testing (Lethbridge, 2000;Carver and Kraft, 2011;Radermacher and Walia, 2013). To address this shortcoming, educators have begun to incorporate software testing into the software engineering curriculum (Jones, 2000;Aniche et al, 2019), including introductory programming courses (Edwards, 2004). These educators provide students with feedback not only about their software, but also about their test suites.…”

Section: Introductionmentioning

confidence: 99%

Fast and accurate incremental feedback for students’ software tests using selective mutation analysis

Kazerouni

Davis²,

Basak

et al. 2021

Journal of Systems and Software

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As incorporating software testing into programming assignments becomes routine, educators have begun to assess not only the correctness of students' software, but also the adequacy of their tests. In practice, educators rely on code coverage measures, though its shortcomings are widely known. Mutation analysis is a stronger measure of test adequacy, but it is too costly to be applied beyond the small programs developed in introductory programming courses. We demonstrate how to adapt mutation analysis to provide rapid automated feedback on software tests for complex projects in large programming courses. We study a dataset of 1389 student software projects ranging from trivial to complex. We begin by showing that although the state-of-the-art in mutation analysis is practical for providing rapid feedback on projects in introductory courses, it is prohibitively expensive for the more complex projects in subsequent courses. To reduce this cost, we use a statistical procedure to select a subset of mutation operators that maintains accuracy while minimizing cost. We show that with only 2 operators, costs can be reduced by a factor of 2-3 with negligible loss in accuracy. Finally, we evaluate our approach on open-source software and report that our findings may generalize beyond our educational context.

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“…Understanding how beginners work with a new programming language and the types of mistakes that they make can help instructors better tailor their lesson plans to avoid previous pitfalls [1], [2]. We consider SQL, a widely-used language for interacting with relational databases.…”

Section: Introductionmentioning

confidence: 99%

SQLRepair: Identifying and Repairing Mistakes in Student-Authored SQL Queries

Presler-Marshall

Heckman

Stolee

2021

2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)

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Computer science educators seek to understand the types of mistakes that students make when learning a new (programming) language so that they can help students avoid those mistakes in the future. While educators know what mistakes students regularly make in languages such as C and Python, students struggle with SQL and regularly make mistakes when working with it. We present an analysis of mistakes that students made when first working with SQL, classify the types of errors introduced, and provide suggestions on how to avoid them going forward. In addition, we present an automated tool, SQLRepair, that is capable of repairing errors introduced by undergraduate programmers when writing SQL queries. Our results show that students find repairs produced by our tool comparable in understandability to queries written by themselves or by other students, suggesting that SQL repair tools may be useful in an educational context. We also provide to the community a benchmark of SQL queries written by the students in our study that we used for evaluation of SQLRepair.

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Pragmatic Software Testing Education

Cited by 42 publications

References 37 publications

Grading 600+ Students: A Case Study on Peer and Self Grading

Grading 600+ Students: A Case Study on Peer and Self Grading

Fast and accurate incremental feedback for students’ software tests using selective mutation analysis

SQLRepair: Identifying and Repairing Mistakes in Student-Authored SQL Queries

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