本論文提出以繞線為考量之多掃描樹合成演算法。多掃描樹(Multiple Scan Tree)測試架構可有效地降低SoC 測試所需之測試資料量(Test Data Volume)與測試時間(Test Application Time)。然而，在過去與多掃描樹合成演算法相關的研究中卻鮮少考量掃描樹所需耗費之繞線距離，使合成之掃描樹耗費過長的繞線距離。本論文提出之多掃描樹合成演算法有效地將測試資料之壓縮率與繞線距離同時納入考量，使合成之多掃描樹與過去相比有著較佳的繞線結果。在演算法中，首先以提出之密度導向叢集演算法動態地決定每個掃描細胞所在之掃描樹。接著利用樹狀搜尋(Tree Search)演算法找尋相容群。最後利用Voronoi diagram 建立掃描細胞之間的連接。與過去的研究相比，提出之演算法成功地提升1.4 到2.1 倍之測試資料壓縮率，並且節省15.9 到24.6 倍之測試時間。更重要的是本論文提出之演算法成功地
節省了1.3 到3.2 倍之繞線長度。

An interconnect-driven layout-aware multiple scan tree synthesis methodology is proposed in this paper. Multiple scan trees, also known as a scan forest, greatly reduce test data volume and test application time in SOC testing. However, previous researches
on scan tree synthesis rarely considered routing length issues, and hence create scan trees with excessively long routing paths. The proposed algorithm effectively considers both test compression rate and routing length and hence produces better results than all
previous known methods in both regards. In this method, a density-driven dynamic clustering algorithm is applied to determine scan cells in each scan tree. A compatibility based clique partition algorithm is used to determine tree topology, and then a Voronoi diagram is used to establish physical connections. Compared with previous works on
scan tree synthesis, the proposed method reduces test data volume by 1.4X to 2.1X, while the reduction in test application time ranges from 15.9X to 24.6X. The significant improvement in test application time is mainly due to the multiple scan trees architecture. The final routing structure is also better, as 1.3X to 3.2X reduction in routing length is achieved.

CHAPTER 1. Introduction ........................................................................................ 1
1.1 MOTIVATION ............................................................................................................................1
1.2 OUTLINE OF THE THESIS .........................................................................................................3
CHAPTER 2. Preliminaries ....................................................................................... 4
2.1 TEST VECTOR COMPATIBILITY IN SINGLE SCAN CHAIN ........................................................4
2.2 TEST VECTOR COMPATIBILITY IN SCAN TREE ARCHITECTURE............................................6
2.3 SCAN TREE WITH INVERSE COMPATIBILITY ..........................................................................7
2.4 STRUCTURAL COMPATIBILITY ................................................................................................8
2.5 A COMPLETE AND BALANCED SCAN TREE .............................................................................9
CHAPTER 3. A Five-Phase Multiple Scan Tree Construction Algorithm for Test
Compression, Application Time and Routing ........................................... 11
3.1 DENSITY-BASED ADAPTIVE CLUSTERING (DAC) ................................................................. 11
3.2 COMPATIBILITY GROUP CONSTRUCTION ALGORITHM (CGC ALGORITHM) ..................... 14
3.3 COMPATIBILITY CLIQUE ASSIGNMENT ALGORITHM (CCA ALGORITHM) ......................... 18
3.4 VORONOI SCAN TREE CONSTRUCTION (VSTC) ALGORITHM ............................................. 21
3.5 GLOBAL BALANCING VIA SCAN SEGMENT INSERTION ......................................................... 27
3.6 LAYOUT-AWARE SCAN TREE CONSTRUCTION FLOW .......................................................... 31
CHAPTER 4. Experimental Results ....................................................................... 33
CHAPTER 5. Conclusions ....................................................................................... 39
References ...................................................................................................................... 40

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