Automated Software Engineering
The dataset is based on the latent faults detected by the popular OSS static code analysis tool, sonarQube Community Edition. The dataset is populated using the latent faults found in popular Java software from the open source repository GitHub . This dataset was specifically developed to identify the significant latent faults that affect the reliability of Java programs. This dataset can be used in its current form to conduct experiments with machine learning algorithms and to infer new reliability characteristics of Java programs. Please refer to the documents associated with sona
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This data set contains 120 text files describing the functional requirements written in natural language (English) for various software systems, such as educational, business, and hospitality settings. The dataset is ready for all text processing such as learning and extracting conceptual models.
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FARLEAD2 receives a test scenario from the developer, and verifies a related functional behavior by witnessing the test scenario in the Application Under Test, on a real mobile device. The 'results.zip' file contains 204 Comma-Separated Values (CSV) files and a Perl script 'createtable.pl' that generates Table 2 in the manuscript. Each CSV file contains the results of ten runs of a witness generator for a test scenario under a given level of information. The experimental test scenarios are located in the 'scenarios.zip' file.
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The dataset contains Software Development Effort Estimation (SDEE) metrics values extracted from around 1800 Open Source Software (OSS) repositories of GitHub.
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