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1. #ERROR WHILE FETCHING FROM DOI JABREF GENERATOR#
2. #ERROR WHILE FETCHING FROM DOI JABREF MANUAL#
3. #ERROR WHILE FETCHING FROM DOI JABREF ANDROID#
4. #ERROR WHILE FETCHING FROM DOI JABREF SOFTWARE#
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Old techniques in the area of test-case generation are not fully-automated or dependent on human inputs.

#ERROR WHILE FETCHING FROM DOI JABREF SOFTWARE#

It lacks in capturing all different cases and takes a huge time from the software tester to plan, design and re-design the testing suites in case of UI change.

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Manual testing for GUIs has its problems. Most software errors are captured and detected through the software GUI layer.

GUI testing is one of the most important and significant testing approaches among all different software testing techniques. The paper overviews the state of the art in GUI testing, discusses differences, similarities and complementarities among the different techniques, experimentally compares strengths and weaknesses, and pinpoints the open problems that deserve further investigation. In this paper we comparatively evaluate the state-of-the-art for automatic GUI test cases generation for desktop applications, by presenting a set of experimental results obtained with the main GUI testing tools for desktop applications available. Although GUI test case generation techniques for desktop applications were the first to be investigated, this area is still actively researched and its state of the art is continuously expanding.

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Recent attempts to automate GUI testing have produced several techniques that address the problem from different perspectives, sometimes focusing only on some specific platforms, such as Android or Web, and sometimes targeting only some aspects of GUI testing, like test case generation or execution. Testing software applications interacting with their graphical user interface, in short GUI testing, is both important, since it can reveal subtle and annoying bugs, and expensive, due to myriads of possible GUI interactions. This paper presents the new features of ABT2.0, and discusses how these new features address the issues that we faced.

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In particular, the paper discusses the problems of automating the generation of test cases by referring to a customised ERP application that the medium-size company developed for a third party multinational company, and presents ABT2.0, the test case generator that we developed by tailoring ABT, a research state-of-the-art GUI test generator, to their industrial environment. We describe the technical and organisational obstacles that we faced when introducing automatic test case generation in the development process of the company, and present the solutions that we successfully experienced in that context. This paper reports our experience in introducing techniques for automatically generating system test suites in a medium-size company. However, generating system test cases in small and medium-size software companies is still largely a manual, inefficient and ad-hoc activity. Proprietary tools for automatically generating test cases are becoming common practice in large software organisations, and commercial tools are becoming available for some application domains and testing levels. While costs and benefits of automating many testing activities in industrial practice (including managing the quality process, executing large test suites, and managing regression test suites) are well understood and documented, the benefits and obstacles of automatically generating system test suites in industrial practice are not well reported yet, despite the recent progresses of automated test case generation tools. The level and quality of automation dramatically affects software testing activities, determines costs and effectiveness of the testing process, and largely impacts on the quality of the final product. Using our approach we are able to find previously undetected bugs. With the specific choice of a lightweight static analysis, the approach scales to large applications and, at the same time, leads to an informed selection of event sequences. We evaluate the approach on four open source GUI applications. We have implemented our approach in a new tool. We use the EDG together with a black-box model to construct a set of relevant event sequences among the executable ones. This allows us to infer a dependency graph, which we call Event Dependency Graph (EDG).

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Departing from a pure black-box approach we apply a static analysis to the byte code of the application. We express the relevance of an event sequence by a precisely defined dependency between a fixed number of events in the event sequence. In this paper we propose a new approach to select relevant event sequences among the event sequences generated by a black-box model. The black-box model can be, e.g., an Event Flow Graph (EFG) or an Event Sequence Graph (ESG).

A major advance in this direction is the use of a black-box model to systematically generate event sequences that are executable on the GUI. The open challenge is the judicious generation of event sequences (an event sequence encodes a user interaction).