Automated assessment of students' testing skills for improving correctness of their code
| Autor: | Zalia Shams |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Smoke testing (software)
business.industry Computer science White-box testing Risk-based testing Test-driven development Machine learning computer.software_genre Keyword-driven testing Acceptance testing Regression testing ComputingMilieux_COMPUTERSANDEDUCATION Artificial intelligence business computer Simulation Dynamic testing |
| Zdroj: | SPLASH (Companion Volume) |
| Popis: | Although software testing is included as a regular part of many programming courses, current assessment techniques used in automated grading tools for evaluating student-written software tests are imperfect. Code coverage measures are typically used in practice, but that approach does not assess how much of the expected behavior is checked by the tests and sometimes, overestimates the true quality of the tests. Two robust and thorough measures for evaluating student-written tests are running each students' tests against others' solutions(known as all-pairs testing) and injecting artificial bugs to determine if tests can detect them (also known as mutation analysis). Even though they are better indicators of test quality, both of them posed a number of practical obstacles to classroom use. This proposal describes technical obstacles behind using these two approaches in automated grading. We propose novel and practical solutions to apply all-pairs testing and mutation analysis of student-written tests, especially in the context of classroom grading tools. Experimental results of applying our techniques in eight CS1 and CS2 assignments submitted by 147 students show the feasibility of our solution. Finally, we discuss our plan to combine the approaches to evaluate tests of assignments having variable amounts of design freedom and explain their evaluation method. |
| Databáze: | OpenAIRE |
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