Massive Open Online Collaboration Testing
Based on the MOOCTEST platform, a multilingual online integrated development environment provides an online development and test learning environment for all users who have access to the system platform. Users can create the workspace of the project through WebIDE for online development, operation, submission and other operations. Users can use it anytime, anywhere, conveniently and quickly when they need, which greatly reduces the learning cost.
FEAT allow the users to access their automated testing techniques by implement some interface. So far, we access three automated techniques which have good compatibility: Monkey, AppCrawler and Appium.You can use FEAT to instrument and compile the Android source code, then use the techniques have been accessed to test them to get a test result, for evaluating the ability of these techniques.
BugHunter is a platform to solve the problem of low-quality and duplicate bug reports of crowdsourced testing. With the help of BugHunter, the crowdsourced workers can efficiently capture screenshot, write short description and create bug report. A series of bug reports are aggregated online and then recommended to the other workers in real time. The crowdsourced workers can (1) help review, verify and enrich each others' bug reports; (2) escape duplicate bug reports; (3) be guided to conduct more professional testing with the help of collective intelligence. BugHunter can improve the quality of the final report and reduce the test costs.
Crowdsourcing has been widely adopted to solve various software-engineering testing tasks. With a large workforce, crowdsourced testing is capable of detecting various bugs and simulating real usage scenarios. Such benefits come with the challenge of inspecting and triaging the overwhelming number of crowdsourced test reports, which is a time-consuming yet inevitable task. Conventional test-report processing tools, such as the widely used Bugzilla, Mantis and JIRA, have provided keyword search based interfaces to assist users in finding duplicate test reports. However, due to many technical and social factors of crowdsourced testing, such as the overwhelming number of test reports and the potentially lower quality of those reports, such conventional manual method of duplicate detection become less effective. In this paper, we present CTRAS, a tool for automatically aggregating and summarizing duplicate crowdsourced test reports on the fly. CTRAS is capable of automatically detecting duplicates based on both textual information and the screenshots, and further aggregates and summarizes the duplicate test reports. CTRAS provides the end users a comprehensive and comprehensible understanding of all duplicates by identifying the main topics across the group of aggregated test reports and highlighting supplementary topics that are mentioned in subgroups of test reports. Also, it provides the classic tool of issue tracking systems, such as the project-report dashboard and keyword searching, and automates their classic functionalities, such as bug triaging and best fixer recommendation, to assist end users in managing and diagnosing test reports.