The identification of cohesive segments in execution traces is an important step in concept location which, in turns, is of paramount importance for many program-comprehension activities. In this paper, we reformulate concept location as a trace segmentation problem solved via dynamic programming. Differently to approaches based on genetic algorithms, dynamic programming can compute an exact solution with better performance than previous approaches, even on long traces. We describe the new problem formulation and the algorithmic details of our approach. We then compare the performances of dynamic programming with those of a genetic algorithm, showing that dynamic programming reduces dramatically the time required to segment traces, without sacrificing precision and recall; even slightly improving them. © 2011 Springer-Verlag.
CITATION STYLE
Medini, S., Galinier, P., Di Penta, M., Guéhéneuc, Y. G., & Antoniol, G. (2011). A fast algorithm to locate concepts in execution traces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6956 LNCS, pp. 252–266). https://doi.org/10.1007/978-3-642-23716-4_22
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