Dependency distance minimization (DDM) is found as a universal quantitative property of natural languages. To investigate whether second language learners develop their interlanguage system under the pressure of DDM, we selected 367 Chinese EFL learners of nine consecutive grades, built one second language dependency treebank and two corresponding random treebanks and fitted different probability distribution models to dependency distances. It was found that: (1) The mean dependency distance (MDD) of interlanguage increases significantly across nine grades and the MDD of high-level learners doesn't reach the level of English native speakers. (2) The MDDs of interlanguage at different learning phases are significantly lower than their corresponding random languages (RL1 and RL2), indicating that learners develop their English proficiency under the pressure of DDM. (3) The distribution of dependency distances of RL1 cannot fit the Zipf-Alekseev distribution, but that of RL2 can. The parameters in the Zipf-Alekseev distribution of RL2 have no correlation with learners' language proficiency.