3 research outputs found
An expert system for checking the correctness of memory systems using simulation and metamorphic testing
During the last few years, computer performance has reached a turning point where computing
power is no longer the only important concern. This way, the emphasis is shifting from an
exclusive focus on the optimisation of the computing system to optimising other systems, like
the memory system. Broadly speaking, testing memory systems entails two main challenges: the
oracle problem and the reliable test set problem. The former consists in deciding if the outputs
of a test suite are correct. The latter refers to providing an appropriate test suite for determining
the correctness of the system under test.
In this paper we propose an expert system for checking the correctness of memory systems.
In order to face these challenges, our proposed system combines two orthogonal techniques
– simulation and metamorphic testing – enabling the automatic generation of appropriate test
cases and deciding if their outputs are correct. In contrast to conventional expert systems, our
system includes a factual database containing the results of previous simulations, and a simulation
platform for computing the behaviour of memory systems. The knowledge of the expert is
represented in the form of metamorphic relations, which are properties of the analysed system
involving multiple inputs and their outputs. Thus, the main contribution of this work is two-fold:
a method to automatise the testing process of memory systems, and a novel expert system design
focusing on increasing the overall performance of the testing process.
To show the applicability of our system, we have performed a thorough evaluation using
500 memory configurations and 4 di erent memory management algorithms, which entailed
the execution of more than one million of simulations. The evaluation used mutation testing,
injecting faults in the memory management algorithms. The developed expert system was able
to detect over 99% of the critical injected faults, hence obtaining very promising results, and
outperforming other standard techniques like random testingThis work was supported by the Spanish Ministerio de EconomÃa, Industria y Competitividad, Gobierno de España/FEDER (grant numbers DArDOS, TIN2015-65845-C3-1-R and FAME, RTI2018-093608-B-C31) and the Comunidad de Madrid project FORTE under Grant S2018/TCS-4314. The first author is also supported by the Universidad Complutense de Madrid - Santander Universidades grant (CT17/17-CT18/17
A Comprehensive Test and Diagnostic Strategy for TCAMs
Content addressable memories (CAMs) are gaining popularity with computer networks. Testing costs of CAMs are extremely high owing to their unique configuration. In this thesis, a fault analysis is carried out on an industrial ternary CAM (TCAM) design, and search path test algorithms are designed. The proposed algorithms are able to test the TCAM array, multiple-match resolver (MMR), and match address encoder (MAE). The tests represent a 6x decrease in test complexity compared to existing algorithms, while dramatically improving fault coverage