Separation logic is an extension of the classical Hoare logic for reasoning about pointers and dynamic data structures, and has been extensively used in the formal analysis and verification of fundamental software, including operating system kernels. Automated constraint solving is one of the key means to automate the separation-logic based verification of these programs. The verification of programs manipulating dynamic data structures usually involves both the shape properties, e.g., singly or doubly linked lists and trees, and data constraints, e.g., sortedness and the invariance of data sets/multisets. This paper introduces COMPSPEN, a separation logic solver capable of simultaneously reasoning about the shape properties and data constraints of linear dynamic data structures. First, the theoretical foundations of COMPSPEN are introduced, including the definition of separation logic fragment SLID_data as well as the decision procedures of the satisfiability and entailment problems of SLID_data. Then, the implementation and the architecture of the COMPSPEN tool are presented. At last, the experimental results for COMPSEN are reported. 600 test cases are collected and the performance of COMPSPEN is compared with the state-of-the-art separation logic solvers, including Asterix, S2S, Songbird, and SPEN. The experimental results show that COMPSPEN is the only tool capable of solving separation logic formulae involving set data constraints, and in overall, it is able to efficiently solve the satisfiability problem of separation logic formulas involving both shape properties and linear arithmetic data constraints on linear dynamic data structures, and is also capable of solving the entailment problem.