A Literature Review on Automation Testing Using Selenium+Sikuli

Automation testing is a methodology that uses an application to implement the entire life cycle of the software in less time and provides efficiency and effectiveness to the testing software. In automation testing, the tester writes scripts and uses any suitable application software to test the software application. Automation is basically an automated process that is comprised of lots of manual activities. In other words, automation testing uses automation tools like Selenium, Sikuli, Appium, etc., to write test script and execute test cases, with no or minimal manual involvement required while executing an automated test suite. Usually, automation testers write test scripts and test cases using any of the automation tool and then groups test several cases. Here, we will discuss a neat case study explaining the automation testing using a hybrid test script.

Intelligent Test Platform for Power Metering System Software

In order to meet the requirements of the operation and maintenance personnel for the power metering system software, when updating the software version, they can independently, quickly and effectively control the quality of the software, an intelligent test platform is designed. Based on the platform, the software operation and maintenance personnel can simply select the corresponding records from the test scripts, test cases and automatic test tools in database debugged by the third-party test team, create the test plan, click the execute button, the platform will automatically connect the selected test tool, intelligently generate a set of executable command lines, to complete the functionality or performance test of the software using the selected test script and test case, and to create the reports of software defects, then a software development team repairs the defects and then the personnel performs regression testing until the new version meets the requirements.

On the Use of Generative Deep Learning Approaches for Generating Hidden Test Scripts

With the advent of web 2.0, web application architectures have been evolved, and their complexity has grown enormously. Due to the complexity, testing of web applications is getting time-consuming and intensive process. In today’s web applications, users can achieve the same goal by performing different actions. To ensure that the entire system is safe and robust, developers try to test all possible user action sequences in the testing phase. Since the space of all the possibilities is enormous, covering all user action sequences can be impossible. To automate the test script generation task and reduce the space of the possible user action sequences, we propose a novel method based on long short-term memory (LSTM) network for generating test scripts from user clickstream data. The experiment results clearly show that generated hidden test sequences are user-like sequences, and the process of generating test scripts with the proposed model is less time-consuming than writing them manually.

A GUI TESTING STRATEGY AND TOOL FOR ANDROID APPS

The increasing popularity of Android and the GUI-driven nature of its apps have motivated the need for applicable automated GUI testing techniques. This paper presents a proposed strategy and a supporting tool for GUI testing of Android apps. The strategy employs a model-based approach to capture the event-driven nature of Android apps. It includes two phases: Modeling Phase and Test Evaluation Phase. In the modeling phase, an event sequence diagram (ESD) is created for each activity in the app under test (AUT), which depicts its events and possible transitions between them, and used to generate event sequences (test cases). In the test evaluation phase, certain event-based coverage criteria are employed to measure the adequacy of the generated test cases. The proposed tool analyses the AUT, creates an ESD for each activity, and generates event sequences. It handles the event sequences explosion problem and ensures the event sequences feasibility. For each event sequence, the tool generates a test script and a corresponding Robotium test class, adds it to the AUT and executes it. The paper also presents a case study that illustrates the use of the proposed strategy and tool for testing a simple Android app.

Linguistic Evidence for Script Relativity

Using the universal grammar of reading and the system accommodation hypothesis (Perfetti, 2003) as theoretical frameworks, this chapter reviews a wide range of linguistic evidence that supports script relativity. Universality and specificity found according to script features are discussed with respect to the operating principle (alphabet vs. logography), psycholinguistic gran size (phoneme vs. syllable), graph configuration (linearity vs. block), symbolic representation (arbitrariness vs. iconic quality), graph complexity (traditional characters vs. simplified characters), and multi-script representation (phonogram Kana vs. Ideogram Kanji). Linguistic skills associated with reading in terms of orthography, phonology, morphology as well as cross-linguistic and cross-scriptal transfer are reviewed. Next, based on the reviewed literature, each criterion for causality from script to cognition through reading as a multifaceted cognitive activity is checked. Although the existing literature did not aim to directly test script relativity, research findings collectively suggest script effects on readers’ thought and cognition.