Spectral and meta-heuristic algorithms for software clustering

This paper presents evidence that Bunch's solutions are within a known factor of the optimal solution. We show this by applying spectral methods to the software clustering problem. The advantage of using spectral methods is that the results this technique produces are within a known factor of the optimal solution. Meta-heuristic search methods only guarantee local optimality, which may be far from the global optimum. In this paper, we apply the spectral methods to the software clustering problem and make comparisons to Bunch. We conducted a case study to draw our comparisons and to determine if an efficient clustering algorithm, one that guarantees a near-optimal solution, can be created.