Improving MC/DC and Fault Detection Strength Using Combinatorial Testing

Dong, Li; Hu, Linghuan; Gao, Ruizhi; Wong, W. Eric; Kuhn, D. Richard; Kacker, Raghu N.

doi:10.1109/qrs-c.2017.131

Cited by 10 publications

(2 citation statements)

References 15 publications

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“…In [12] automatic test data generation for testing of C programs at white box level for obtaining multiple coverage criteria including MCDC is covered. In [13], the authors have discussed about the extent of statement/branch and MC/DC coverage and the Fault Detection Rate (FDR) that can be achieved by executing CIT cases with strength varying from 2 to 5 on two subjects taken from SIR. They have taken original implementation and number of mutants of the subjects to study the effectiveness of CIT.…”

Section: B Mc/dc Coverage With Citmentioning

confidence: 99%

Automation of Combinatorial Interaction Test (CIT) Case Generation and Execution for Requirements based Testing (RBT) of Complex Avionics Systems

Sarla¹,

Ramadoss²

2018

ijacsa

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In the field of avionics, most of the software systems are either safety critical or mission critical. These systems are developed with high quality standards strictly following the relevant guidelines and procedures. Due to the high criticality of the systems, it is mandatory that the verification and validation of these systems are done with utmost importance and only then any system is cleared for flight trials. The verification and validation activities need to be very exhaustive and hence take a considerable amount of time in the software development lifecycle. This paper describes about the innovative approach towards automation of Combinatorial Interaction Test case generation and execution for Requirements Based Testing of complex avionics systems for achieving test adequacy in a highly time efficient and cost efficient manner.

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Section: B Mc/dc Coverage With Citmentioning

confidence: 99%

Automation of Combinatorial Interaction Test (CIT) Case Generation and Execution for Requirements based Testing (RBT) of Complex Avionics Systems

Sarla¹,

Ramadoss²

2018

ijacsa

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“…Though MCDC is a structural coverage criterion, researchers have been using MCDC definitions to generate test cases from a Boolean expression to detect faults in that expression 15,16,18‐20 . Furthermore, researchers have been working on improving the fault detection strength of MCDC using different strategies 21 . A recent study 9 has redefined the fault classes of Boolean expressions based on their abstract syntax tree (AST) representations to overcome a number of confusing issues related to the fault classes.…”

Section: Introductionmentioning

confidence: 99%

A new disjunctive literal insertion fault detection strategy in boolean specifications

Paul

Chowdhury

Lau

2021

J Software Evolu Process

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In fault‐based Boolean expression testing, the main challenge is to generate effective test cases that can detect faults within expressions. Previous studies show that it is hard to detect literal insertion faults, more specifically Disjunctive literal insertion fault (LIF[+]) compared with other faults in Boolean expressions. Researchers have been using different strategies such as multiple near false point coverage (MNFP) and modified condition decision coverage (MCDC) to detect LIF[+] faults. However, these strategies have their own limitations. For example, MNFP can only be applied when the expression is in irredundant disjunctive normal form (IDNF), and MCDC detects a low percentage of LIF[+] faults. In this paper, we propose an abstract syntax tree (AST)‐based test case generation strategy for LIF[+] fault detection that overcomes these limitations. Furthermore, our experimental results indicate that, on average, the test suites satisfying the proposed strategy can detect approximately 97.3% of LIF[+] faults for general form expressions and 89.7% of LIF[+] faults for IDNF expressions, which are 15.6% and 13.8% improvement, respectively, compared to the MCDC test suites. Moreover, the size of the required test suite is smaller than that of MCDC test suite.

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Search‐Based MC/DC Test Data Generation With OCL Constraints

Sartaj,

Zohaib Iqbal,

Ahmed Jilani

et al. 2024

Software Testing Verif & Rel

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System‐level testing of avionics software systems requires compliance with different international safety standards such as DO‐178C. An important consideration of the avionics industry is automated test data generation according to the criteria suggested by safety standards. One of the recommended criteria by DO‐178C is the modified condition/decision coverage (MC/DC) criterion. Current model‐based test data generation approaches use constraints written in Object Constraint Language (OCL) and apply search techniques to generate test data. These approaches either do not support MC/DC criterion or suffer from performance issues while generating test data for large‐scale avionics systems. In this paper, we propose an effective way to automate MC/DC test data generation during model‐based testing. We develop a strategy that utilizes case‐based reasoning (CBR) and range reduction heuristics designed to solve MC/DC‐tailored OCL constraints. We performed an empirical study to compare our proposed strategy for MC/DC test data generation using CBR, range reduction, both CBR and range reduction, with an original search algorithm, and random search. We also empirically compared our strategy with existing constraint‐solving approaches. The results show that both CBR and range reduction for MC/DC test data generation outperform the baseline approach. Moreover, the combination of both CBR and range reduction for MC/DC test data generation is an effective approach compared to existing constraint solvers.

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Improving MC/DC and Fault Detection Strength Using Combinatorial Testing

Cited by 10 publications

References 15 publications

Automation of Combinatorial Interaction Test (CIT) Case Generation and Execution for Requirements based Testing (RBT) of Complex Avionics Systems

Automation of Combinatorial Interaction Test (CIT) Case Generation and Execution for Requirements based Testing (RBT) of Complex Avionics Systems

A new disjunctive literal insertion fault detection strategy in boolean specifications

Search‐Based MC/DC Test Data Generation With OCL Constraints

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