Pattern matching with gap constraints has important applications in many fields such as information retrieval, computational biology, and sequential pattern mining etc. This paper proposes a pattern matching problem named Strict Pattern Matching with General Gaps and Length Constraints (SPANGLO) which has four characteristics: It is strict exact pattern matching; Any position in the given sequence can be used more than once; The pattern can have more than one general gap constraint; Each matching substring has length constraints. An instance of SPANGLO can be transformed into an exponential number of matching instances with non-negative gaps in the worst case. In order to solve the problem effectively, an algorithm named SubnettreeSpanglo (SETS) is proposed based on Subnettree and its special concepts and properties. The correctness and completeness of the algorithm are given, and the space and time complexities of the algorithm are O(m×MaxLen×W) and O(MaxLen×W×m²×n) respectively, where n, m, MaxLen and W are the sequence length, the pattern length, the maximum length of the occurrence and the maximum gap of the pattern respectively. Experimental results validate the correctness of the transforming method of SPANGLO and the efficientiveness and correctness of SETS.