Manual Testing Execution Time Estimation

Abstract

In software development practices of software industry. Testing plays a crucial role in the software development life cycle and it does so by verifying and validating the software’s quality. Since testing is thought to be a high-cost process in software development and the fact that the budget for testing the product is limited, finding the execution time needed for software testing activities like the prioritization, scheduling and progress monitoring of test cases is of significant importance. Manual testing remains a prevailing and significant approach to validating software applications, particularly in certain areas such as domain-specific testing. To carry out test planning, prioritization and progress tracking, it is essential to know the execution time of test instances. In this work, we apply, assess and present on the basis of the specifications of test for execution time estimation and prediction of manual test-cases. Our method operates by extracting timing data in manual test specification for different steps. This data is then utilized for prediction of maximum time for those test steps that were not executed. An approach for time of execution prediction and estimation for manual test-cases is suggested in this thesis. The technique utilizes test specifications and historical information accessible from test instances that were previously performed. Our strategy works by acquiring timing data from each and every step of test instances earlier carried out. The gathered data is used from their test specifications to predict the execution period for nonexecuted test instances. Classification test case scores are extracted from the test specification contained in the Test Manager Tool and plotted with the acquired timing information. Classification is used on Test Cases to estimate the execution period of non-executed sample instances after estimating the time from this mapping. LMKR performed a case survey where the suggested technique is applied and the outcomes are validated. The results obtained show that the predicted time of execution of studied test cases is close to their actual time of execution.