Using simulated annealing for locating array construction

TL;DR

This paper introduces a simulated annealing-based algorithm for constructing small locating arrays, which are crucial for efficient combinatorial interaction testing and fault localization in computing systems.

Contribution

It presents a novel meta-heuristic approach that effectively generates small locating arrays for large problem instances, improving over existing methods.

Findings

Successfully constructs locating arrays for large problem sizes

Often finds smaller locating arrays than known solutions

Scales to practical, real-world problems

Abstract

Context: Combinatorial interaction testing is known to be an efficient testing strategy for computing and information systems. Locating arrays are mathematical objects that are useful for this testing strategy, as they can be used as a test suite that enables fault localization as well as fault detection. In this application, each row of an array is used as an individual test. Objective: This paper proposes an algorithm for constructing locating arrays with a small number of rows. Testing cost increases as the number of tests increases; thus the problem of finding locating arrays of small sizes is of practical importance. Method: The proposed algorithm uses simulation annealing, a meta-heuristic algorithm, to find locating array of a given size. The whole algorithm repeatedly executes the simulated annealing algorithm by dynamically varying the input array size. Results: Experimental results show 1) that the proposed algorithm is able to construct locating arrays for problem instances of large sizes and 2) that, for problem instances for which nontrivial locating arrays are known, the algorithm is often able to generate locating arrays that are smaller than or at least equal to the known arrays. Conclusion: Based on the results, it is concluded that the proposed algorithm can produce small locating arrays and scale to practical problems.