An Efficient VLSI Test Data Compression Scheme for Circular Scan Architecture Based on Modified Ant Colony Meta-heuristic

Mitra, Sourav; Das, Debaprasad

doi:10.1007/s10836-020-05880-7

Cited by 7 publications

(3 citation statements)

References 33 publications

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“…Liu et al [28] proposed a niching particle swarm optimization algorithm based on Euclidean distance and hierarchical clustering for multimodal optimization and applied it to solve the TSP. Mitra et al [29] reinterpreted the data compression problem as a TSP and introduced a modified ant colony algorithm in combination with a mutation operator to resolve the problem. Moreover, new intelligent search algorithms, such as the spider algorithm [30], chicken swarm optimization [31], and whale optimization algorithm [32], have also been used to solve the TSP and its variants.…”

Section: Complexitymentioning

confidence: 99%

A Test Procedure Optimization Method for an Industrial Robot Servo System on an Integrated Testing Platform

et al. 2020

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A test procedure optimization method was proposed in this paper to improve the test efficiency of the industrial robot servo system (IRSS) to be tested on the IRSS integrated testing platform (IITP). First, an ordered sequence was used to define the IRSS test project when tested on the IITP. The ordered sequence consisted of execution subelements, which were a combination of control variable parameters of the IITP. Second, the optimization relationships among the IRSS test projects were dug out according to the IRSS test project sequences. Finally, by using the traveling salesmen problem (TSP), an optimization model was established based on the optimization relationships of the IRSS test projects, and the optimal test order of the IRSS test projects to be tested on the IITP was obtained by solving the model. A case analysis showed that the proposed method optimized the test procedure on the IITP effectively, and the test time when implementing the test on the IITP according to the optimized order was nearly 50% shorter than before optimization. The optimization effect was thus found to be significant.

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Section: Complexitymentioning

confidence: 99%

A Test Procedure Optimization Method for an Industrial Robot Servo System on an Integrated Testing Platform

et al. 2020

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“…While keeping the testing efficiency unchanged, the above methods generate MTV by using intelligent iterative algorithm and reduce the misjudgment rate and confusion rate of MTV to some extent. However, the improper design of particle iteration and the difficulty to determine the search direction of these intelligent algorithms leads to the fast convergence in the optimization of misjudgment rate and confusion rate, the result is always trapped in the local optimal solution [20][21][22][23][24][25]. With the increase in the network size of the circuit under test, the local optimal solution of misjudgment rate and confusion rate will lead to a serious decline in the fault detection accuracy of the boundary scan [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

A Boundary Scan Test Vectors Optimization Method Based on Improved GA-AO* Approach Considering Fault Probability Model

Su,

Guo,

Luo

et al. 2024

Applied Sciences

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The generation of test vectors is a key technique that affects the efficiency and fault detection rate of the boundary scan test. Aiming at the local optimal solution problem of the current common test vectors generation algorithm, this paper proposes a test vectors generation algorithm based on improved GA-AO* model, through which the test vectors are generated by using the idea of heuristic search and backtracking correction. In order to speed up the heuristic search, this paper designed a heuristic function with both prior and posterior parameters to describe the influence of typical faults on the failure probability index of the test vectors. At the same time, this paper used a genetic algorithm (GA) to determine the specific values of the posterior parameters iteratively. Finally, through theoretical analysis and physical verification, compared with the test vector generated by the traditional method, the test vector generated by this method is optimized on the prior failure probability index and performs better in the physical experiment.

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“…The TDV depends on numerous parameters, such as the amount of test pattern for input data, an amount of stimulus, response of bits per pattern. Therefore, the TDV is restricted by employing several test data compression schemes [11].…”

Section: Introductionmentioning

confidence: 99%

On Reducing Test Data Volume for Circular Scan Architecture Using Modified Shuffled Shepherd Optimization

et al. 2021

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In this manuscript, a novel test data compression (TDC) system is proposes for reducing a test data volume (TDV) for circular scan (CS) architecture. A modified version of meta-heuristic population based optimization approach, hence it is called shuffled shepherd optimization (SSO) and it is used to optimize the conflicting bit minimization (CBM) problem. In CS framework, TDC is reached by upgrading only the conflicting bits among template pattern, real test pattern. Reduced test data volume and test application time are achieved by diminishing the Hamming distance between the currently captured response and the subsequent test vector. The CBM issue is formulated by a traveling salesman problem (TSP). Here, the test vectors are assumed by cities, the HD among test vectors a pair is assumed by distance of interurban. A modified version of the SSO algorithm called as MSSO is applied in combination using mutation operator for solving the issue of CBM. Experimental outcomes display the proposed TDC method using MSSO achieves an average development of 8.36% in compression ratio (CR) as well as 6.77% in TAT is attained by reducing a TDV. This proposed approach outperforms other state-of-art test data compression schemes by providing improved CR, TAT reduction and TDV reduction.

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An Efficient VLSI Test Data Compression Scheme for Circular Scan Architecture Based on Modified Ant Colony Meta-heuristic

Cited by 7 publications

References 33 publications

A Test Procedure Optimization Method for an Industrial Robot Servo System on an Integrated Testing Platform

A Test Procedure Optimization Method for an Industrial Robot Servo System on an Integrated Testing Platform

A Boundary Scan Test Vectors Optimization Method Based on Improved GA-AO* Approach Considering Fault Probability Model

On Reducing Test Data Volume for Circular Scan Architecture Using Modified Shuffled Shepherd Optimization

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