藉由分析程式碼解說影片來自動產生影片片段與程式碼之間的關聯

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姓名

江行之(XING-ZHI JIANG) 查詢紙本館藏

畢業系所

軟體工程研究所

論文名稱

藉由分析程式碼解說影片來自動產生影片片段與程式碼之間的關聯

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檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2028-7-28以後開放)

摘要(中)

此論文在於研究如何分析解說影片，自動將其真的有在講解程式
碼的部分，依據特性切成許多片段，並且將其關聯到特定檔案的對應
git 提交歷史版本的某段程式碼。來達到大量節省軟體開發人員製作
文件的時間。也能夠讓觀看程式解說影片的人，想要了解某段程式碼
的在做甚麼，只要看某幾支影片的某些片段即可，不用完整看完所有
影片，來達到更有效率的知識獲取效率。

摘要(英)

This paper focuses on researching how to analyze explanatory videos and automatically identify the parts where the code is being explained. Based on the characteristics, the videos are divided into multiple segments and associated with specific sections of code from the corresponding git commit history versions of the relevant files. This significantly saves the time of software developers in creating documentation. It also enables viewers of the code explanation videos to understand what a particular code segment is doing by simply watching specific segments of a few videos, without the need to watch all the videos in their entirety, thus achieving more efficient knowledge acquisition.

關鍵字(中)

★ 技術文件
★ 文件管理
★ 追蹤案例

關鍵字(英)

★ Technical Document
★ Document Management
★ Trace Case

論文目次

摘要 i
Abstract ii
目錄 iv
圖目錄 vi
一、緒論 1
二、研究背景 5
2-1 GeekyNote 5
2-1-1 GeekyNote 的文件過時性 5
2-1-2 GeekyNote 的追蹤案例 7
2-1-3 GeekyNote 的影片與多媒體文件 9
2-2 Feature Location 相關的論文 12
2-3 OpenCV 14
2-4 光學字符識別（OCR）16
三、問題描述與分析 19
四、系統架構與設計 22
4-1 動態佈局描述語言（dynamic layout description language）26
4-2 基於動態佈局描述語言的佈局分析演算法 31
4-3 影片片段切割分析 34
五、討論與評估 36
六、結論與未來展望 37
七、參考資料 38

參考文獻

[1] Y.-P. Cheng, "GeekyNote: a technical documentation tool with coverage, backtracking, traces, and couplings.," Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, 2020.
[2] A. Olszak, "Featureous: a tool for feature-centric analysis of java software," IEEE 2010.
[3] F. Warr, "Suade: Topology-based searches for software investigation," IEEE, 2008.
[4] D. Poshyvanyk, "Jiriss-an eclipse plug-in for source code exploration," IEEE, 2006.
[5] "opencv," [Online]. Available: https://opencv.org/.
[6] "aws ocr explanation," [Online]. Available: https://aws.amazon.com/what-is/ocr/.
[7] "gitlab issues," [Online]. Available: https://docs.gitlab.com/ee/user/project/issues/.
[8] "tesseract," [Online]. Available: https://tesseract-ocr.github.io/.
[9] "google vision api," [Online]. Available: https://cloud.google.com/vision.
[10] "google vision api price," [Online]. Available: https://cloud.google.com/vision/pricing.
[11] "opencv connected component," [Online]. Available: https://docs.opencv.org/3.4/d3/dc0/group__imgproc__shape.html#gac2718a64ade63475425558aa669a943a.
[12] J. Canny, "A computational approach to edge detection," IEEE Transactions on pattern analysis and machine intelligence, 1986.
[13] P. H. RO Duda, "Use of the Hough transformation to detect lines and curves in pictures," Communications of the ACM, 1972.
[14] "json schema," [Online]. Available: https://json-schema.org/.

指導教授

鄭永斌(Yung-Pin Cheng)

審核日期

2023-8-17

推文