In this paper, we describe the basis of EuGne, a gene nder for eucaryotic organisms applied to Arabidopsis thaliana. The specicity of EuGne, compared to existing gene nding software, is that EuGne combines the output of several information sources, including output of other software, in a weighted directed acyclic graph (DAG) designed in such a way that a shortest path in this graph represents the most likely gene structure of the underlying ADN sequence. The usual simple Bellman linear time shortest path algorithm for DAG has been replaced by a shortest path with constraints algorithm. The constraints express minimum length of introns or intergenic regions. The specicity of the constraints leads to an algorithm which is still linear both in time and space. EuGne eectiveness has been assessed on Araset, a recent dataset of Arabidopsis thaliana sequences used to evaluate several existing gene nding software. It appears that, despite its simplicity, EuGne gives results..