Satrio, Christopher Dimas (2017) Perbandingan Test Case Generation Dengan Pendekatan Genetic Algorithm Mutation Analysis Dan Sampling. Sarjana thesis, Universitas Brawijaya.
Abstract
Pengujian perangkat lunak memiliki peranan penting dalam mengetahui dan menjaga kualitas suatu perangkat lunak. Dalam proses pengujian perangkat lunak sangat diperlukan adanya test case. Namun, pembuatan test case membutuhkan waktu yang relatif lama sehingga dilakukan pembuatan test case secara otomatis menggunakan algoritma tertentu. Salah satu algoritma yang sering digunakan adalah genetic algorithm. Banyak pendekatan genetic algoritm yang telah dikembangkan. Namun, belum ada penelitian yang membandingkan pendekatan genetic algorithm yang lebih baik. Penelitian ini akan membandingkan pendekatan genetic algorithm mutation analysis dan sampling. Kedua pendekatan tersebut akan diimplementasikan dan dianalisis hasilnya. Dari segi hasil akhir akan dilihat jumlah pengurangan test case yang terjadi. Banyaknya iterasi, akumulasi jumlah individual, banyaknya evaluasi fitness yang terjadi, dan ukuran dari test suites akan menjadi variabel pembanding diantara kedua pendekatan tersebut. Kesimpulan dari penelitian ini adalah pendekatan genetic algorithm mutation analysis lebih baik dibanding genetic algorithm sampling pada jumlah pengurangan test case dan semua variabel pembanding yang diterapkan.
English Abstract
Software testing has an important role to knowing and maintaining the quality of a software. In software testing process, test case is necessary. However, test case generation require a relatively long time, so automatic test case generation with a certain algorithm are conduct. The purpose of this research are to compare genetic algorithm mutation analysis and genetic algorithm sampling approach. That’s two approach wil be implemented and the result will be analyzed. In terms of the final result, will be revealed the reduction of the number of test case that occurs. Number of iteration, cumulative number of individuals, number of fitness evaluation, and size of the resulting test suites will be variable comparison between that’s two approach. The conclusion of this research are the genetic algorithm mutation analysis approach is better than genetic algorithm sampling approach in terms of the reduction number of test case and for all comparison variable that applied.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2017/407/051706754 |
| Uncontrolled Keywords: | test case, genetic algorithm, mutation analysis, sampling, test suite |
| Subjects: | 000 Computer science, information and general works > 004 Computer science > 004.2 System analysis and design, computer architecture, performance evaluation |
| Divisions: | Fakultas Ilmu Komputer > Sistem Informasi |
| Depositing User: | Budi Wahyono Wahyono |
| Date Deposited: | 22 Aug 2017 03:50 |
| Last Modified: | 01 Oct 2020 04:42 |
| URI: | http://repository.ub.ac.id/id/eprint/1501 |
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