a b s t r a c tTo ensure an acceptable level of quality and reliability of a typical software product, it is desirable to test every possible combination of input data under various configurations. However, due to the combinatorial explosion problem, exhaustive testing is practically impossible. Resource constraints, cost factors, and strict time-to-market deadlines are some of the main factors that inhibit such a consideration. Earlier research has suggested that a sampling strategy (i.e., one that is based on a t-way parameter interaction) can be effective. As a result, many helpful t-way sampling strategies have been developed and can be found in the literature.Several advances have been achieved in the last 15 years, which have, in particular, served to facilitate the test planning process by systematically minimizing the test size required (based on certain t-way parameter interactions). Despite this significant progress, the integration and automation of strategies (from planning process to execution) are still lacking. Additionally, strategizing to sample (and construct) a minimum test set from the exhaustive test space is an NP-complete problem; that is, it is often unlikely that an efficient strategy exists that could regularly generate an optimal test set. Motivated by these challenges, this paper discusses the design, implementation, and validation of an efficient strategy for t-way testing, the GTWay strategy. The main contribution of GTWay is the integration of t-way test data generation with automated (concurrent) execution as part of its tool implementation. Unlike most previous methods, GTWay addresses the generation of test data for a high coverage strength (t > 6).

Combinatorial testing has been an active research area in recent years. One challenge in this area is dealing with the combinatorial explosion problem, which typically requires a very expensive computational process to find a good test set that covers all the combinations for a given interaction strength (t). Parallelization can be an effective approach to manage this computational cost, that is, by taking advantage of the recent advancement of multicore architectures. In line with such alluring prospects, this paper presents a new deterministic strategy, called multicore modified input parameter order (MC‐MIPOG) based on an earlier strategy, input parameter order generalized (IPOG). Unlike its predecessor strategy, MC‐MIPOG adopts a novel approach by removing control and data dependency to permit the harnessing of multicore systems. Experiments are undertaken to demonstrate speedup gain and to compare the proposed strategy with other strategies, including IPOG. The overall results demonstrate that MC‐MIPOG outperforms most existing strategies (IPOG, IPOF, IPOF2, IPOG‐D, ITCH, TConfig, Jenny, and TVG) in terms of test size within acceptable execution time. Unlike most strategies, MC‐MIPOG is also capable of supporting high interaction strengths of t > 6.

This paper focuses on the security and privacy threats being faced by the lowcost RFID communication system, the most challenging of which relate to eavesdropping, impersonation, and tag cloning problems. The security issues can be improved and solved by utilizing both prevention and detection strategies. Prevention technique is needed since it offers resistance capabilities toward eavesdroppers and impersonators. Detection technique is vital to minimize the negative effects of tag cloning threats. This paper proposes the use of both prevention and detection techniques to make RFID communication more secure. Lightweight cryptographic algorithm, which conforms to the EPC Class-1 Generation-2 standard, is used in the proposed mutual authentication protocol for RFID system to raise security levels. In addition, electronic fingerprinting system is deployed in the proposed solution as a detection method to distinguish counterfeit and legitimate tags.

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