자료유형 | 학위논문 |
---|---|
서명/저자사항 | Broadening the Applicability of Software Complexity Metrics with Biological Analogues. |
개인저자 | Hathaway, Charles. |
단체저자명 | Rensselaer Polytechnic Institute. Computer Science. |
발행사항 | [S.l.]: Rensselaer Polytechnic Institute., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 149 p. |
기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
ISBN | 9780438206472 |
학위논문주기 | Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Advisers: Ron Eglash |
요약 | Software metrics represent an application of conventional computer science to itself in an attempt to quantify the complexity of software systems. Many of the conventional metrics proposed in academia and industry find their roots in a top-down |
요약 | Chapters 5 and 6 compare taint analysis, measured using standard complexity metrics, with an ecosystem approach that examines interactive complexity. Chapter 3 examines the use of traditional complexity metrics to measure student comprehension o |
요약 | Combining these bio-inspired and traditional metrics utilizing machine learning techniques, also inspired by biology and neurology, chapter 7 demonstrates that greater results can be achieved with both angles than a single perspective. |
일반주제명 | Computer science. |
언어 | 영어 |
바로가기 |
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |