Using Genetic Algorithm as Test Data Generator for Stored PL/SQL Program Units

Abstract

PL/SQL is the most common language for ORACLE database application. It allows the developer to create stored program units (Procedures, Functions, and Packages) to improve software reusability and hide the complexity of the execution of a specific operation behind a name. Also, it acts as an interface between SQL database and DEVELOPER. Therefore, it is important to test these modules that consist of procedures and functions. In this paper, a new genetic algorithm (GA), as search technique, is used in order to find the required test data according to branch criteria to test stored PL/SQL program units. The experimental results show that this was not fully achieved, such that the test target in some branches is not reached and the coverage percentage is 98%. A problem rises when target branch is depending on data retrieved from tables; in this case, GA is not able to generate test cases for this branch.

Sea Lion Optimization Algorithm

“…Metaheuristic optimization algorithms are introduced in order to solve optimization problems by imitating physical or biological phenomena [6][7][8][9][10][11]. Therefore, these algorithms are categorized into three classes; evolution-based, physicsbased, and swarm-based methods [1,2,[12][13].…”

“…Metaheuristic algorithms that based on population share popular features regardless of their nature. The search operation has two main phases; exploration and exploitation [9][10]. The operators should always be part of the optimizer in order to globally explore the search space.…”

Applying Genetic Algorithms to Test JUH DBs Exceptions

“…'); [22] elsifp_error_no = 5 then [23] raise_application_error ( -20006, 'Pricing datais incompleteforthis patient!! '); [24] elsifp_error_no = 11 then [25] raise_application_error( -20001, '11'); [26] elsifp_error_no = 21 then [27] raise_application_error ( -20003, '21'); [28] elsifp_error_no = 31 then [29] raise_application_error ( -20004 …”

“…Search-based software testing is a dynamic method of test data generation in which search methods or optimization techniques are used to generate tests and have been successfully applied in structural testing [[24] [25 [23] [26] [27][28] [29]]. As with all search methods, search based software testing relies crucially on an evaluation or cost function to compare candidate test cases.…”

Model Based Test Case Generation and Optimization Using Intelligent Optimization Agent

“…Simultaneously it reduced testing cost and improved the cycle time. Different techniques for optimization are Genetic Algorithm (GA) [1], Particle Swarm Optimization (PSO) [2], Intelligent Search Engine (ISA) [5], Intelligent Test Case Optimization Agent (ITOA) [6], Artificial Bee Colony (ABC) algorithm etc. [9][10][11].…”