Automated Identification and Application of Code Refactoring in Scratch to Promote the Culture Quality from the Ground up
| dc.contributor.author | Techapalokul, Peeratham | en |
| dc.contributor.committeechair | Tilevich, Eli | en |
| dc.contributor.committeemember | Edwards, Stephen H. | en |
| dc.contributor.committeemember | Servant Cortes, Francisco Javier | en |
| dc.contributor.committeemember | Hermans, Felienne | en |
| dc.contributor.committeemember | Kafura, Dennis G. | en |
| dc.contributor.department | Computer Science | en |
| dc.date.accessioned | 2020-06-05T08:01:45Z | en |
| dc.date.available | 2020-06-05T08:01:45Z | en |
| dc.date.issued | 2020-06-04 | en |
| dc.description.abstract | Much of software engineering research and practice is concerned with improving software quality. While enormous prior efforts have focused on improving the quality of programs, this dissertation instead provides the means to educate the next generation of programmers who care deeply about software quality. If they embrace the culture of quality, these programmers would be positioned to drastically improve the quality of the software ecosystem. This dissertation describes novel methodologies, techniques, and tools for introducing novice programmers to software quality and its systematic improvement. This research builds on the success of Scratch, a popular novice-oriented block-based programming language, to support the learning of code quality and its improvement. This dissertation improves the understanding of quality problems of novice programmers, creates analysis and quality improvement technologies, and develops instructional approaches for teaching quality improvement. The contributions of this dissertation are as follows. (1) We identify twelve code smells endemic to Scratch, show their prevalence in a large representative codebase, and demonstrate how they hinder project reuse and communal learning. (2) We introduce four new refactorings for Scratch, develop an infrastructure to support them in the Scratch programming environment, and evaluate their effectiveness for the target audience. (3) We study the impact of introducing code quality concepts alongside the fundamentals of programming with and without automated refactoring support. Our findings confirm that it is not only feasible but also advantageous to promote the culture of quality from the ground up. The contributions of this dissertation can benefit both novice programmers and introductory computing educators. | en |
| dc.description.abstractgeneral | Software remains one of the most defect-prone artifacts across all engineering disciplines. Much of software engineering research and practice is concerned with improving software quality. While enormous prior efforts have focused on improving the quality of programs, this dissertation instead provides the means to educate the next generation of programmers who care deeply about software quality. If they embrace the culture of quality, these programmers would be positioned to drastically improve the quality of the software ecosystem, akin to professionals in traditional engineering disciplines. This dissertation describes novel methodologies, techniques, and tools for introducing novice programmers to software quality and its systematic improvement. This research builds on the success of Scratch, a popular visual programming language for teaching introductory students, to support the learning of code quality and its improvement. This dissertation improves the understanding of quality problems of novice programmers, creates analysis and quality improvement technologies, and develops instructional approaches for teaching quality improvement. This dissertation contributes (1) a large-scale study of recurring quality problems in Scratch projects and how these problems hinder communal learning, (2) four new refactorings, quality improving behavior-preserving program transformations, as well as their implementation and evaluation, (3) a study of the impact of introducing code quality concepts alongside the fundamentals of programming with and without automated refactoring support. Our findings confirm that it is not only feasible but also advantageous to promote the culture of quality from the ground up. The contributions of this dissertation can benefit both novice programmers and introductory computing educators. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:25597 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/98756 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | code quality | en |
| dc.subject | code smells | en |
| dc.subject | refactoring | en |
| dc.subject | Scratch | en |
| dc.subject | block-based programming | en |
| dc.subject | introductory computing education | en |
| dc.subject | novice programmers | en |
| dc.title | Automated Identification and Application of Code Refactoring in Scratch to Promote the Culture Quality from the Ground up | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Computer Science and Applications | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
Files
Original bundle
1 - 1 of 1