Modified Selective Huffman Coding for Optimization of Test Data Compression, Test Application Time and Area Overhead

Mehta, Usha; Dasgupta, K. S.; Devashrayee, N. M.

doi:10.1007/s10836-010-5183-6

Cited by 12 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [7] modified selective Huffman coding gives better compression ratio compare to another methods . In this paper for finding compression ratio we use selective Huffman ,optimal selective Huffman and modified selective Huffman coding then compare compression ratio.…”

Section: Estimation Of Compression Ratiomentioning

confidence: 98%

Analysis of Dont Care Bit Filling Techniques for Optimization of Compression and Scan Power

Bhavsar¹,

Mehta²

2011

IJCA

View full text Add to dashboard Cite

Test power and test time have been the major issues for current scenario of VLSI testing. The test data compression is the well known method used to reduce the test time. The don't care bit filling method can be used for effective test data compression as well as reduction in scan power. In this paper we describe the algorithm for don't care assignment like MT(Minimum Transition)-fill technique and hamming distance based technique.The selective Huffman ,optimal Huffman and modified selective Huffman coding are applied on the mapping set to give the optimum Compression and weighted transition matrix is used for scan power Using these techniques find compression and scan power parameters like average power and peak power and conclude that MT-fill technique gives low peak and average powers and Hamming distance based modified selective Huffman coding technique gives higher compression ratio compare to another methods like selective and optimal Huffman coding.

show abstract

Section: Estimation Of Compression Ratiomentioning

confidence: 98%

Analysis of Dont Care Bit Filling Techniques for Optimization of Compression and Scan Power

Bhavsar¹,

Mehta²

2011

IJCA

View full text Add to dashboard Cite

show abstract

“…al. 2003;Mehta, et al 2010), Run-Length (RL) Huffman encoding (Nourani, Tehranipour, 2005) and optimal selective Huffman encoding (Kavousianos et al 2007) compress the data depending upon the rate of occurrence of various patterns. Run length code based techniques exploit the various combinations of test bits to shrink the overall test data length.…”

Section: Analysis Of Existing Literaturementioning

confidence: 99%

An innovative two-stage data compression scheme using adaptive block merging technique

2020

View full text Add to dashboard Cite

Test data has increased enormously owing to the rising on-chip complexity of integrated circuits. It further increases the test data transportation time and tester memory. The non-correlated test bits increase the issue of the test power. This paper presents a two-stage block merging based test data minimization scheme which reduces the test bits, test time and test power. A test data is partitioned into blocks of fixed sizes which are compressed using two-stage encoding technique. In stage one, successive blocks are merged to retain a representative block. In stage two, the retained pattern block is further encoding based on the existence of ten different subcases between the sub-block formed by splitting the retained pattern block into two halves. Noncompatible blocks are also split into two sub-blocks and tried for encoded using lesser bits. Decompression architecture to retrieve the original test data is presented. Simulation results obtained corresponding to different ISCAS'89 benchmarks circuits reflect its effectiveness in achieving better compression.

show abstract

“…For instance, the patterns having a higher frequency of occurrence are encoded using lesser number of bits (codes) as compared with the one's having a lesser frequency. Huffman coding and its extended techniques such as variable input Huffman coding [11], selective Huffman coding [12], run length (RL) Huffman coding [13], optimal selective Huffman [14] and modified selective [15] coding techniques are all examples of such statistical coding techniques. The statistical techniques help in achieving a good amount of average compression, but the need of look‐up table makes the decoding process to be test data dependent.…”

Section: Related Work Of Code‐based Test Compressionmentioning

confidence: 99%

Test data compression using hierarchical block merging technique

Vohra

Singh

2018

IET Computers & Digital Techniques

View full text Add to dashboard Cite

Manufacturing of semiconductor devices at the sub-micron level has led to the introduction of huge number of faults. To ensure the quality of integrated circuits (ICs), enormous amount of test data is needed which, in turn, increases the overall test cost of the ICs. This study presents a hierarchical block-merging-based technique (HBMT) for test data compression, which appropriately encodes the test pattern blocks of fixed sizes at inter-and intra-block levels using lesser number of bits. The proposed technique works in four steps: segmentation of the entire length of test data into equal length blocks; categorisation of test blocks as compatible blocks and unique blocks; merging of compatible blocks to form representative pattern block, which is further merged at sub-block level; and compression of the non-compatible (unique) blocks using different encoding cases. Experimental results performed on various international symposium for circuits and systems (ISCAS)' 89 benchmark circuits demonstrate the effectiveness of the proposed test data compression technique. It is found that application of HBMT can improve the compression efficiency by an average of 73% along with a reduction in the test application time. This study also presents the decoder architecture.

show abstract

Modified Selective Huffman Coding for Optimization of Test Data Compression, Test Application Time and Area Overhead

Cited by 12 publications

References 15 publications

Analysis of Dont Care Bit Filling Techniques for Optimization of Compression and Scan Power

Analysis of Dont Care Bit Filling Techniques for Optimization of Compression and Scan Power

An innovative two-stage data compression scheme using adaptive block merging technique

Test data compression using hierarchical block merging technique

Contact Info

Product

Resources

About