For integers \( k \geq 1 \), a \((p,q)\)-graph \( G = (V, E) \) is said to admit an AL(\(k\))-traversal if there exists a sequence of vertices \((v_1, v_2, \ldots, v_p)\) such that for each \( i = 1, 2, \ldots, p-1 \), the distance between \( v_i \) and \( v_{i+1} \) is \( k \). We call a graph \( k \)-step Hamiltonian (or say it admits a \( k \)-step Hamiltonian tour) if it has an AL(\(k\))-traversal and \( d(v_1, v_p) = k \). In this paper, we investigate the \( k \)-step Hamiltonicity of graphs. In particular, we show that every graph is an induced subgraph of a \( k \)-step Hamiltonian graph for all \( k \geq 2 \).

A difference system of sets (DSS) is any collection of subsets of \(\mathbb{Z}_n\) with the property that the differences from distinct sets cover \(\mathbb{Z}_n\). That is, every non-zero class in \(\mathbb{Z}_n\) can be written as a difference of classes in at least one way. DSS were introduced by Levenstein in 1971 only for finite fields but the case for just 2 subsets had been previously considered by Clauge. Their work emphasized an application to synchronizable codes. A DSS is triangular if its sets contain only triangular numbers mod \(n\). We show that a triangular DSS cannot exist in \(\mathbb{Z}_{2^k}\) for \(k > 3\).

In testing web applications, details of user visits may be recorded in a web log and converted to test cases. This is called user-session-based testing and studies have shown that such tests may be effective at revealing faults. However, for popular web applications with a larger user base, many user-sessions may build up and test suite management techniques are needed. In this paper, we focus on the problem of test suite prioritization. That is, given a large test suite, reorder the test cases according to a criterion that is hypothesized to increase the rate of fault detection. Previous work shows that 2-way combinatorial-based prioritization is an effective prioritization criterion. We develop a greedy algorithm where we consider memory usage and the time that it takes to prioritize test suites. We represent software tests in a graph by storing unique parameters as vertices and \( n \)-way sets as edges or series of edges. Our experiments demonstrate the efficiency of this approach.

The lattice-simplex covering density problem aims to determine the minimal density by which lattice translates of the \( n \)-simplex cover \( n \)-space. Currently, the problem is completely solved in \( 2 \) dimensions. A computer search on the problem in three dimensions gives experimental evidence that for the simplex \( D \) (the convex hull of the unit basis vectors), the most effective lattice corresponds to the tile known as the \( 84 \)-shape. The \( 84 \)-shape tile has been shown to be a local minimum of the density function. We explain the mechanics behind an algorithm which determines the most efficient lattice in the interior of an arbitrary combinatorial type.

An efficient conditional expectation algorithm for generating covering arrays has established a number of the best known upper bounds on covering array numbers. Despite its theoretical efficiency, the method requires a large amount of storage and time. In order to extend the range of its application, we generalize the method to find covering arrays that are invariant under the action of a group, reducing the search to consider only orbit representatives of interactions to be covered. At the same time, we extend the method to construct a generalization of covering arrays called quilting arrays. The extended conditional expectation algorithm, as expected, provides a technique for generating covering and quilting arrays that reduces the time and storage required. Remarkably, it also improves on the best known bounds on covering array numbers in a variety of parameter situations.

Historically, a number of problems and puzzles have been introduced that initially appeared to have no connection to graph colorings but, upon further analysis, suggested graph colorings problems. In this paper, we discuss two combinatorial problems and several graph colorings problems that are inspired by these two problems. We survey recent results and open questions in this area of research as well as some relationships among these coloring parameters and well-known colorings and labelings.

Let \( G \) be a graph with vertex set \( V(G) \) and edge set \( E(G) \), and let \( A \) be an abelian group. A labeling \( f: V(G) \to A \) induces an edge labeling \( f^*: E(G) \to A \) defined by \( f^*(xy) = f(x) + f(y) \) for each edge \( xy \in E(G) \). For \( i \in A \), let \( v_f(i) = |\{v \in V(G) : f(v) = i\}| \), and \( e_f(i) = |\{e \in E(G) : f^*(e) = i\}| \). Define \( c(f) = \{ |e_f(i) – e_f(j)| : (i, j) \in A \times A \} \).A labeling \( f \) of a graph \( G \) is said to be A-friendly if \( |\text{v}_f(i) – \text{v}_f(j)| \leq 1 \) for all \( (i, j) \in A \times A \). If \( c(f) \) is a \( (0,1) \)-matrix for an A-friendly labeling \( f \), then \( f \) is said to be A-cordial.When \( A = \mathbb{Z}_2 \), the friendly index set of the graph \( G \), denoted \( FI(G) \), is defined as \( \{ |e_f(0) – e_f(1)| : \text{the vertex labeling } f \text{ is } \mathbb{Z}_2\text{-friendly} \} \).In this paper, we completely determine the friendly index sets for two classes of cubic graphs, prisms and Möbius ladders , are completely determined.

A vertex \( x \) in a graph \( G \) strongly resolves a pair of vertices \( v \) and \( w \) if there exists a shortest path from \( x \) to \( w \) that contains \( v \), or a shortest path from \( x \) to \( v \) that contains \( w \) in \( G \). A set of vertices \( S \subseteq V(G) \) is a strong resolving set of \( G \) if every pair of distinct vertices in \( G \) is strongly resolved by some vertex in \( S \). The strong metric dimension \( sdim(G) \) of a graph \( G \) is the minimum cardinality of a strong resolving set of \( G \).

Given two disjoint copies of a graph \( G \), denoted \( G_1 \) and \( G_2 \), and a permutation \( \sigma : V(G_1) \to V(G_2) \), the permutation graph \( G_\sigma = (V, E) \) is defined with vertex set \( V = V(G_1) \cup V(G_2) \) and edge set \( E = E(G_1) \cup E(G_2) \cup \{uv \mid v = \sigma(u)\} \).

We show that for a connected graph \( G \) of order \( n \geq 3 \), the strong metric dimension of \( G_\sigma \) satisfies \( 2 \leq sdim(G_\sigma) \leq 2n – 2 \). We also provide an example demonstrating that there is no function \( f \) such that \( f(sdim(G)) > sdim(G_\sigma) \) for all pairs \( (G, \sigma) \). Additionally, we prove that \( sdim(G_{\sigma_o}) \leq 2sdim(G) \) when \( \sigma_o \) is the identity permutation.

Further, we characterize permutation graphs \( G_\sigma \) that satisfy \( sdim(G_\sigma) = 2n – 2 \) or \( 2n – 3 \) when \( G \) is a complete \( k \)-partite graph, a cycle, or a path on \( n \) vertices.

In a recent paper, E. Gelman provided an exact formula for the number of subgroups of a given index for the Baumslag-Solitar groups \( \text{BS}(p, q) \) when \( p \) and \( q \) are coprime. We use Gelman’s proof as the basis for an algorithm that computes a maximal set of inequivalent permutation representations of \( \text{BS}(p, q) \) with degree \( n \). The computational complexity of this algorithm is linear in both space and time with respect to the index. We compare the performance of this algorithm with the Todd-Coxeter procedure, which generally lacks a polynomial bound on the number of cosets used during the enumeration process.

An \( H_2 \) graph is a multigraph on three vertices with a double edge between one pair of distinct vertices and a single edge between the other two pairs. The problem of decomposing a complete multigraph \( 3K_{8t} \) into \( H_2 \) graphs has been completely solved. In this paper, we describe some new procedures for such decompositions and pose the following question: Can these procedures be adapted or extended to provide a unified proof of the existence of \( H_2(8t, \lambda) \)’s?