Improving test compression by retaining non-pivot free variables in sequential linear decompressors

Sequential linear decompressors are inherently efficient and attractive for compressing test cubes with many don't cares. The test cubes are encoded by solving a system of linear equations. In continuous decompression, typically a fixed number of free variables are used to encode each test cube in a “one-size-fits-all” manner. The non-pivot free variables used in Gaussian elimination are wasted when the decompressor is reset before decompressing the next test cube. This paper explores techniques for retaining the non-pivot free variables for a test cube and using them to help encode subsequent test cubes and hence improve encoding efficiency. This approach retains most of the non-pivot free variables with only a minimal increase in runtime for solving the equations and no added control information. Experimental results are presented showing that the encoding efficiency, and hence compression, can be significantly boosted.