This thesis proposes an approach to improve test compression using sequential linear decompressors by using retained free variables. Sequential linear decompressors are inherently efficient and attractive for encoding test vectors with high percentages of don't cares (i.e., test cubes). The encoding of these test cubes is done by solving a system of linear equations. In streaming decompression, a fixed number of free variables are used to encode each test cube. The non-pivot free variables used in Gaussian Elimination are wasted when the decompressor is reset before encoding the next test cube which is conventionally done to keep computational complexity manageable. In this thesis, a technique for retaining the non-pivot free variables when encoding one test cube and using them in encoding the subsequent test cubes is explored. This approach retains most of the non-pivot free variables with a minimal increase in runtime for solving the equations. Also, no additional control information is needed. Experimental results are presented showing that the encoding efficiency and hence compression, can be significantly boosted. / text

Sequential linear decompressors are widely used to implement test compression. Bits stored on the tester (called free variables) are assigned values to encode the test vectors such that when the tester data is decompressed, it reproduces the care bits in the test cube losslessly. In order to do this, the free variable dependence of the scan cells is obtained by symbolic simulation and a system of linear equations, one equation per care bit in a test cube, is solved to obtain the tester data. Existing techniques reset the decompressor after every test cube to avoid accumulating too many free variables, to keep the computation for encoding manageable. This leads to wastage of unused free variables and reduces the efficiency in encoding. Moreover, existing techniques preload the decompressor with free variables before scan shifting, which increases test time to help encode the early scan cells. This dissertation presents new approaches that improve the efficiency of the decompression process, achieving greater test compression and reducing test costs. The contributions of this dissertation include a low cost method to retain unused free variables while encoding a test cube and reuse them while encoding other test cubes with a minor increase in computational complexity. In addition, a test scheduling mechanism is described for system on chip (SoC) architectures that implements retaining unused free variables for SoCs without any hardware overhead and with little additional control. For testing 3D-ICs, a novel daisy-chain architecture for the sequential linear decompressor is proposed for sharing unused free variables across layers with a reduced number of TSVs (through silicon via) needed to transport test data (also called test elevators) to non-bottom layers. A scan feedforward technique is proposed which improves the free variable dependence of the scan cells, thereby increasing the probability of encoding of test cubes, especially when the early scan cells have a lot of specified bits, thereby avoiding the need for preloading the decompressor. Lastly, a feedforward/feedback mechanism in the scan chains for combinational linear decompressors is proposed which improves encoding flexibility and reduces tester data without pipelining the decompressor like the conventional methods, thereby reducing the test time. / text