Most companies are under heavy time and resource constraints when it comes to testing a software system. Test prioritization technique(s) allows the most useful tests to be executed first, exposing faults earlier in the testing process. Thus makes software testing more efficient and cost effective by covering maximum faults in minimum time. But test case prioritization is not an easy and straightforward process and it requires huge efforts and time. Number of approaches is available with their proclaimed advantages and limitations, but accessibility of any one of them is a subject dependent. In this paper, artificial Cuscuta search algorithm (CSA) inspired by real Cuscuta parasitism is used to solve time constraint prioritization problem. We have applied CSA for prioritizing test cases in an order of maximum fault coverage with minimum test suite execution and compare its effectiveness with different prioritization ordering. Taking into account the experimental results, we conclude that (i) The average percentage of faults detection (APFD) is 82.5% using our proposed CSA ordering which is equal to the APFD of optimal and ant colony based ordering whereas No ordering, Random ordering and Reverse ordering has 76.25%, 75%, 68.75% of APFD respectively.