Research On Test Task Scheduling Strategy Based On Cloud Platform

With the rapid development of software industry,the importance of the development cycle and costs has been increasingly emphasized,software testing is an important part of the software development process,not only to provide quality control for software products,but also reduce the risk of human duplication of investment,so as to shorten the development cycle and reduce the costs.With the development of cloud computing,provides a new direction for the software testing technology,test task being migrated to the cloud platform,and being executed,it not only can save the allocation of environmental cost,but also greatly improves the test task execution efficiency,reduce test time and reduce redundant work testing personnel in the same time.Efficient task scheduling algorithms are essential for performing test tasks on a cloud platform.Outstanding scheduling algorithm can improve the resource utilization of the whole system and shorten the execution time of tasks.The current scheduling algorithm in cloud environment generally exists some limitations,can't fully meet the test task,because the test task is different from the general task,the test tasks not only has a different priority level,but also has a dependency relationships between each other.Especially in the implementation of regression testing tasks,scheduling algorithm becomes more important.Therefore,in this paper,we study the task scheduling problem in the cloud platform,and make a deep research on the scheduling strategy.Aimed at the characteristics of different priorities,this paper proposes a scheduling algorithm based on weight called Weight Scheduler,the algorithm not only considers the initial priority of the test task,but also can manage the tasks according to the specific resource usage of the cluster,in order to avoid the phenomenon of hunger,the test task which waiting for a long time will be given appropriate growth weight,so that the scheduling as fair as possible.The experimental results show that the Weight Scheduler scheduling algorithm is more efficient than the Capacity Scheduler scheduling algorithm in Hadoop.Aimed at the inter task dependencies,the first step is to preprocess the test tasks,and then abstract the DAG graph according to the test task.The path is divided from the DAG graph,the nodes in each path are have dependency relationships,tasks between different paths can be executed in parallel.Then,according to the path in the DAG diagram,integrate test cases and modify test scripts.The cost of script maintenance is considered,and the test script is parameterized.Finally,the test scripts and test cases are uploaded to the HDFS Hadoop file system.Combined with MapReduce programming model,the map function and reduce function are designed for the modified test script,in which the automatic test tool statement is added,the test is carried out automatically,and the test results are recovered.The implementation of MapReduce calls the Weight Scheduler scheduling algorithm,the algorithm based on the Hadoop cloud platform state to scheduling the test tasks.Combined with the automated test tool Selenium to build the cloud test task management platform,the test was carried out on the campus web site as a test target.The experimental results show that the algorithm is efficient and the scheduling strategy is effective.Compared with the single machine,the test time is saved and the testing speed is accelerated.