Understanding Open Source Software Evolution Using Fuzzy Data Mining Algorithm for Time Series Data

Source code management systems (such as Concurrent Versions System (CVS), Subversion, and git) record changes to code repositories of open source software projects. This study explores a fuzzy data mining algorithm for time series data to generate the association rules for evaluating the existing trend and regularity in the evolution of open source software project. The idea to choose fuzzy data mining algorithm for time series data is due to the stochastic nature of the open source software development process. Commit activity of an open source project indicates the activeness of its development community. An active development community is a strong contributor to the success of an open source project. Therefore commit activity analysis along with the trend and regularity analysis for commit activity of open source software project acts as an important indicator to the project managers and analyst regarding the evolutionary prospects of the project in the future

Exploring Software Testing Strategies Used on Software Applications in the Government

Developing a defect-free software application is a challenging task. Despite many years of experience, the intense development of reliable software remains a challenge. For this reason, software defects identified at the end of the testing phase are more expensive than those detected sooner. The purpose of this multiple case study is to explore the testing strategies software developers use to ensure the reliability of software applications in the government contracting industry. The target population consisted of software developers from 3 government contracting organizations located along the East Coast region of the United States. Lehman’s laws of software evolution was the conceptual framework. The data collection process included semistructured interviews with software developers (n = 10), including a review of organizational documents (n = 77). Thematic analysis was used to identify patterns and codes from the interviews. Member checking activities were triangulated with organizational documents to produce 4 major themes: (a) communication and collaboration with all stakeholders, (b) development of well-defined requirements, (c) focus on thorough documentation, and (d) focus on automation testing. The results of this study may contribute to information about testing strategies that may help organizations improve or enhance their testing practices. The results of this study may serve as a foundation for positive social change by potentially improving citizens’ experience with government software applications as a result of potential improvement in software testing practice