Online periodic testing of microprocessors is a valuable means to increase the reliability of a low-cost system, when neither hardware nor time redundant protection schemes can be applied. This is particularly valid for floating-point (FP) units, which are becoming more common in embedded systems and are usually protected from operational faults through costly hardware redundant approaches. In this paper, we present scalable instruction-based self-test program development for both single and double precision FP units considering different instruction sets (MIPS, PowerPC, and Alpha), different microprocessor architectures (32/64-bit architectures) and different memory configurations. Moreover, we introduce bit-level manipulation instruction sequences that are essential for the development of FP unit's self-test programs. We developed self-test programs for single and double precision FP units on 32-bit and 64-bit microprocessor architectures and evaluated them with respect to the requirements of low-cost online periodic self-testing: fault coverage, memory footprint, execution time, and power consumption, assuming different memory hierarchy configurations. Our comprehensive experimental evaluations reveal that the instruction set architecture plays a significant role in the development of self-test programs. Additionally, we suggest the most suitable self-test program development approach when memory footprint or low power consumption is of paramount importance.

High-speed datapaths in microprocessors and embedded processors contain complex floating-point (FP) arithmetic units which have a critical role in the processor's performance. Although the FP units' complex structure consists of classic integer arithmetic components, the embedded components encounter serious testability problems due to their limited accessibility from the FP unit ports and testability loss due to FP unit inherent operations, such as rounding and normalization. In this paper, we analyze the testability problems and present scalable test generation for FP units using as a demonstration vehicle the popular, high-speed, two-path architecture of the most complex unit, the FP adder. The key feature of the presented methodology is the identification of testability conditions that guarantee effective test pattern application and fault propagation for each of the components of the FP adder. The identified test conditions can be utilized with respect to any fault model and are independent of the internal structure and the size of the components. Thus, they can be applied to FP adders of various exponent and significant sizes (single, double, and custom precision), as well as to other types of FP units, which also consist of classic integer arithmetic components similarly interconnected

High performance real number operations in embedded processors' and microprocessors' datapaths are realized by floating point (FP) arithmetic units. FP units have a complex structure which although consisting of classic integer arithmetic components faces serious testability problems due to the limited accessibility of the components from the FP unit ports. In this paper we present a test generation methodology for FP adders based on the high-speed, two-path architecture. The key feature of the presented methodology is the identification of testability conditions that guarantee effective test pattern application and fault propagation for each of the components of the FP adder. According to our test methodology, the testability conditions guide test generation process. The identified test conditions are independent of the internal structure and the size of the components. Thus, they can be applied to floating point adders of various exponent and significand sizes built with components of different architectures.

Embedded processor testing techniques based on the execution of self-test programs have been recently proposed as an effective alternative to classic external tester-based testing and pure hardware built-in self-test (BIST) approaches. Software-based self-testing is a nonintrusive testing approach and provides at-speed testing capability without any hardware or-performance overheads. In this paper, we first present a high-level, functional component-oriented, software-based self-testing methodology for embedded processors. The proposed methodology aims at high structural fault coverage with low test development and test application cost. Then, we validate the effectiveness of the proposed methodology as a low-cost alternative over structural software-based self-testing methodologies based on automatic test pattern generation and pseudorandom testing. Finally, we demonstrate the effectiveness and efficiency of the proposed methodology by completely applying it on two different processor implementations of a popular RISC instruction set architecture including several gate-level implementations.

A comprehensive online test strategy requires both concurrent and non-concurrent fault detection capabilities to guarantee SoCs's successful normal operation in-field at any level of its life cycle. While concurrent fault detection is mainly achieved by hardware or software redundancy, like duplication, non-concurrent fault detection, particularly useful for periodic testing, is usually achieved through hardware BIST. Software-based self-test has been recently proposed as an effective alternative to hardware-based self-test allowing at-speed testing while eliminating area, performance and power consumption overheads. In this paper we focus on the applicability of software-based self-test to non-concurrent on-line testing of embedded processor cores. Low-cost in-field testing requirements, particularly small test execution time and low power consumption guide the development of self-test routines. We show how self-test programs with a limited number of memory references and based on compact test routines provide an efficient low-cost on-line test strategy.

Embedded processor testing techniques based on the execution of self-test routines, have been recently proposed as an effective alternative to classical hardware Built-In Self Test. Software-based self-testing provides atspeed testing capability and does not add hardware or performance penalties. It efficiently partitions the testing task between external testers and internal processor resources. In this paper we analyze the application of a softwarebased self-testing methodology to different implementations of a complex embedded processor architecture. We demonstrate that such a methodology provides high test quality in different processor implementations with low test development and low test application costs. 1