We propose intensity constraint-based closed sequential pattern mining algorithm, called IC-BIDE, for a coding pattern extraction. Source code often contains frequent patterns of function calls or control flows, i.e., "coding patterns." Previous studies used sequential pattern mining to extract coding pattern; however, these algorithms have not been optimized for coding pattern extraction, which results in useless patterns as well as long execution times. We propose a new constraint, called "intensity constraint," in order to enhance closed sequential pattern mining and efficiently extract coding patterns. Our proposed algorithm is based on BI-Directional Execution (BIDE), an algorithm proposed expressly for closed sequential pattern mining. BIDE algorithm is not able to adapt to constraint-based closed sequential pattern mining. We extend BIDE algorithm and prove that our extended algorithm is able to adapt to intensity constraint-based closed sequential pattern mining. Our contributions are as follow; 1) We propose a new constraint, which we call "intensity"; 2) We propose intensity constraint-based closed sequential pattern mining algorithm, which we call "IC-BIDE" algorithm. Experimental results with open source software (Bullet Physics, MySQL, and OpenCV) show that IC-BIDE algorithm successfully excludes useless pattern effectively. Moreover, our proposed method is able to accelerate the extraction by a factor of 8.9 in comparison with the BIDE algorithm.