![]() ![]() The proposed generation algorithm based on SSO has proved its effectiveness by evaluating it against other algorithms. The proposed strategy also manages and repairs the test suites by deleting the unnecessary event sequences that are not applicable. The SSO is used to generate an optimized test suite with the help of Event-Interaction Graph (EIG). In this paper, a strategy for GUI functional testing using Simplified Swarm Optimization (SSO) is proposed. In contrast to non-functional testing, function testing of GUI insures a proper interaction between the user and the application interface without dealing with the coding internals. With this emergence of different types of GUIs, they become an essential component to be tested (if available in the software) to ensure that the software meets the required quality by the user. This interaction uses different tools and programming objects like images, text, buttons, checkboxes, etc. It is been used in different aspects ranging from normal computers, mobile device, to even very small device nowadays like watches. Graphical User Interface (GUI) is the outer skin of programs that facilitate the interaction between the user and different type of computing devices. Annotations significantly reduced human cost after 20% test scripts had been repaired. An experiment using QTP test scripts suggests that SITAR is effective in that 41–89% unusable test scripts were repaired. SITAR amortizes the cost of human intervention across multiple scripts by accumulating the human knowledge as annotations on the EFG. During this process, SITAR also repairs the reference to the GUI objects used in the checkpoints yielding a final test script that can be executed automatically to validate the revised software. SITAR uses reverse engineering techniques to create an abstract test for each script, maps it to an annotated event-flow graph (EFG), uses repairing transformations and human input to repair the test, and synthesizes a new " repaired " test script. We present ScrIpT repAireR (SITAR), a technique to automatically repair unusable low-level test scripts. Moreover, because the software's output may have changed, their test oracles-assertions and checkpoints-encoded in the scripts may no longer correctly check the intended GUI objects. Whenever the GUI changes-widgets get moved around, windows get merged-some scripts become unusable because they no longer encode valid input sequences. To enable automated re-testing, such test cases are increasingly being coded as low-level test scripts, to be replayed automatically using test harnesses. System testing of a GUI-based application requires that test cases, consisting of sequences of user actions/events, be executed and the software's output be verified. The proposed strategy has produced competitive experimental results against the basic TLBO and other test case generation algorithms. ATLBO utilizes Event-Interaction Graph (EIG) for the generation of quality test cases. In this paper, a strategy based on fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm, a variant of the basic Teaching Learning-based Optimization (TLBO) algorithm, for GUI functional testing is proposed. For the quality assurance, GUI functional testing of a software validates proper interaction between the interface and the user without considering any coding details. GUI testing is a critical part of software testing as it is the door to the actual functionality of software. for the effective communication of users with a software system. Unlike command based interaction, GUI uses images, labels, push buttons, radio buttons, etc. Today's computers, smart phones and even small devices such as watches are equipped with GUIs. Graphical User Interface (GUI) visualizes computer programs for the purpose of facilitating interaction between users and various computing devices.
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