An Optimized technique for Test Case Generation and Prioritization Using “Tabu” Search and “Data Clustering” Source available on DBLP and SCOUPS Praveen Ranjan Srivastava 1 , Aditya Vijay 2 , Bhupesh Barukha 2 , Prashant Singh Sengar 2 , Rajat Sharma 2 Computer Science & Information System Group, BITS PILANI – 333031 (INDIA) {praveenrsrivastava, adityavijay88, bbarukha, prashant06457, rajat091}@gmail.com Abstract: In practice, an available testing budget limits the number of test cases that can be executed over particular software. This paper presents a ―Tabu‖ search algorithm for the automatic generation of software test cases and their prioritization through clustering technique of data mining. The developed test case generator has a cost function for intensifying the search and another for diversifying the search, used when the intensification is not successful. It also combines the use of memory with a backtracking process to avoid getting stuck in local minima. Test case prioritization technique schedules test cases in an order that increases their effectiveness in meeting some performance goal. Keywords: Tabu Search; Dynamic test case generation; Test case prioritization; Clustering. 1 Introduction Software engineering is the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software, and the study of these approaches; that is, the application of engineering to software. A part of Software Engineering is to do Software Testing which consists of a set of activities conducted with the aim of finding errors in software. As the number of test cases needed for fully testing a software program is a huge number, therefore in practice, exhaustive testing is infeasible except for trivial cases. It has been estimated that software testing entails 50 percent of software development [1], thus, a subset of all