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Software could be diagnosed either manually or automatically. The two approaches are complementary: automated testing can perform a huge number of tests in short time or period, whereas manual testing uses the knowledge of the testing engineer to target testing to the parts of the system that are assumed to be more error-prone. Despite this contemporary, tools for manual and automatic testing are usually different, leading to decreased productivity and reliability of the testing process. AutoTest is a testing tool that provides a “best of both worlds” strategy: it integrates developers’ test cases into an automated process of systematic contract-driven testing. This allows it to combine the benefits of both approaches while keeping a simple interface, and to treat the two types of tests in a unified fashion: evaluation of results is the same, coverage measures are added up, and both types of tests can be saved in the same format. The objective of this paper is to discuss the Importance of Automation tool with associate to software testing techniques in software engineering. In this paper we provide introduction of software testing and describe the CASE tools. The solution of this problem leads to the new approach of software development known as software testing in the IT world. Software Test Automation is the process of automating the steps of manual test cases using an automation tool or utility to shorten the testing life cycle with respect to time.

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Cloud storage platform is a promising architecture provided by the Cloud Service. However, the use of these services raises many doubts and concerns about the security, confidentiality, reliability and integrity of users' data and information. Because the cloud is based on a per-user payment model, it will take longer to retrieve the required document, which raises the financial burden, and hence affects the satisfaction level of cloud users. This is the major point, where presented research comes to play. The proposed work takes advantage of multi-layered neural network architecture for secure cloud storage system along with the involvement of encryption and similarity approaches such as Cosine Similarity algorithm while encryption check engrosses AES and DSA approaches. Simulation analysis offers a secure cloud platform using cloudsim

Abstract-Data Science and Big Data have an important role among the modern science and emerging technology. Infact, we can say that these are the two side of the same coin. Data Science is establishing basic foundations to become a profession. The data science community can follow a road map for how data science can be more useful for various social and commercial sectors. Today we are surrounding by data like oxygen. The growth of data first presented challenges to cutting edge businesses such as Google, yahoo, Amazon, Microsoft, Face book, twitter etc.