Impact Of Test-Driven Development Research Articles

The empirical study: encouraging students’ interest in software development using test-driven development

The supply is not matching the demand on the market for software developers. While the enrolment in undergraduate computer science courses is increasing, few students are interested in and committed to becoming software developers. It could be that students are overwhelmed by the software development methodology that they are taught. We are consequently looking for a constructivist approach to software engineering able to effectively engage learners. We empirically evaluated whether test-driven development (TDD) is able to improve the quality of both learning and of software development in the classroom. Although numerous studies have outlined the benefits and effects of TDD in the classroom, none of those studies have focused on measuring students' interest in and attitudes toward using TDD in the classroom. We present a study evaluating the impact of TDD on the engagement and focus of learners of software development in the classroom. The results illustrate that the use of TDD in the classroom encourages learners to engage and focus.

Impact of test-driven development on productivity, code and tests: A controlled experiment

Context Test-driven development is an approach to software development, where automated tests are written before production code in highly iterative cycles. Test-driven development attracts attention as well as followers in professional environment; however empirical evidence of its superiority regarding its effect on productivity, code and tests compared to test-last development is still fairly limited. Moreover, it is not clear if the supposed benefits come from writing tests before code or maybe from high iterativity/short development cycles. Objective This paper describes a family of controlled experiments comparing test-driven development to micro iterative test-last development with emphasis on productivity, code properties (external quality and complexity) and tests (code coverage and fault-finding capabilities). Method Subjects were randomly assigned to test-driven and test-last groups. Controlled experiments were conducted for two years, in an academic environment and in different developer contexts (pair programming and individual programming contexts). Number of successfully implemented stories, percentage of successful acceptance tests, McCabe’s code complexity, code coverage and mutation score indicator were measured. Results Experimental results and their selective meta-analysis show no statistically significant differences between test-driven development and iterative test-last development regarding productivity ( χ 2(6) = 4.799, p = 1.0, r = .107, 95% CI (confidence interval): −.149 to .349), code complexity ( χ 2(6) = 8.094, p = .46, r = .048, 95% CI: −.254 to .341), branch coverage ( χ 2(6) = 13.996, p = .059, r = .182, 95% CI: −.081 to .421), percentage of acceptance tests passed (one experiment, Mann–Whitney U = 125.0, p = .98, r = .066) and mutation score indicator ( χ 2(4) = 3.807, p = .87, r = .128, 95% CI: −.162 to .398). Conclusion According to our findings, the benefits of test-driven development compared to iterative test-last development are small and thus in practice relatively unimportant, although effects are positive. There is an indication of test-driven development endorsing better branch coverage, but effect size is considered small.