Automatic test pattern generation

About: Automatic test pattern generation is a research topic. Over the lifetime, 8214 publications have been published within this topic receiving 140773 citations. The topic is also known as: ATPG.

Automatic Test Data Generation for Data Flow Testing Using a Genetic Algorithm

Abstract: One of the major difficulties in software testing is the automatic generation of test data that satisfy a given adequacy criterion. This paper presents an automatic test data generation technique that uses a genetic algorithm (GA), which is guided by the data flow dependencies in the program, to search for test data to cover its def-use associations. The GA conducts its search by constructing new test data from previously generated test data that are evaluated as effective test data. The approach can be used in test data generation for programs with/without loops and procedures. The proposed GA accepts as input an instrumented version of the program to be tested, the list of def-use associations to be covered, the number of input variables, and the domain and precision of each input variable. The algorithm produces a set of test cases, the set of def-use associations covered by each test case, and a list of uncovered def- use associations, if any. In the parent selection process, the GA uses one of two methods: the roulette wheel method or a proposed method, called the random selection method, according to the user choice. Finally, the paper presents the results of the experiments that have been carried out to evaluate the effectiveness of the proposed GA compared to the random testing technique, and to compare the proposed random selection method to the roulette wheel method.

Speed binning with path delay test in 150-nm technology

Abstract: What would it take to reduce speed binning's dependency on functional testing? One answer is a structural at-speed test approach that can achieve the same effectiveness as functional testing. The authors of this article offer a formula to relate structural critical-path testing frequency to system operation frequency. They demonstrate that there can be a high correlation between frequencies resulting from structural testing and those resulting from functional testing.

Requirement-based automated black-box test generation

Abstract: Testing large software systems is very laborious and expensive. Model-based test generation techniques are used to automatically generate tests for large software systems. However, these techniques require manually created system models that are used for test generation. In addition, generated test cases are not associated with individual requirements. In this paper, we present a novel approach of requirement-based test generation. The approach accepts a software specification as a set of individual requirements expressed in textual and SDL formats (a common practice in the industry). From these requirements, system model is automatically created with requirement information mapped to the model. The system model is used to automatically generate test cases related to individual requirements. Several test generation strategies are presented. The approach is extended to requirement-based regression test generation related to changes on the requirement level. Our initial experience shows that this approach may provide significant benefits in terms of reduction in number of test cases and increase in quality of a test suite.

An Efficient Bist Scheme Based On Reseeding Of Multiple Polynomial Linear Feedback Shift Registers

Abstract: In this paper we describe an optimized BIST scheme based on reseeding of multiple polynomial Linear Feedback Shift Registers (LFSRs). The same LFSR that is used to generate pseudo-random patterns, is loaded with seeds from which it produces vectors that cover the testcubes of difficult to test faults. The scheme is compatible with scandesign and achieves full coverage as it is based on random patterns combined with a deterministic test set. A method for processing the test s et to allow for efficient encoding by the .scheme is described. Algorithms for Calculating LFSR seeds from the test set and for the selection and ordering of polynomials are described. Experimental results are provided for ISCAS-89 benchmark circuits to demonstrate the effectiveness of the scheme. The scheme allows an excellent trade-off between test data storage and test application time (number of test patterns) with a very small hardware overhead. We show the trade-off between test data storage and number of test patterns under the scheme.

Improved Test Pattern Generation for Hardware Trojan Detection Using Genetic Algorithm and Boolean Satisfiability

Abstract: Test generation for Hardware Trojan Horses (HTH) detection is extremely challenging, as Trojans are designed to be triggered by very rare logic conditions at internal nodes of the circuit. In this paper, we propose a Genetic Algorithm (GA) based Automatic Test Pattern Generation (ATPG) technique, enhanced by automated solution to an associated Boolean Satisfiability problem. The main insight is that given a specific internal trigger condition, it is not possible to attack an arbitrary node (payload) of the circuit, as the effect of the induced logic malfunction by the HTH might not get propagated to the output. Based on this observation, a fault simulation based framework has been proposed, which enumerates the feasible payload nodes for a specific triggering condition. Subsequently, a compact set of test vectors is selected based on their ability to detect the logic malfunction at the feasible payload nodes, thus increasing their effectiveness. Test vectors generated by the proposed scheme were found to achieve higher detection coverage over large population of HTH in ISCAS benchmark circuits, compared to a previously proposed logic testing based Trojan detection technique.