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Curating GitHub for engineered software projects
- Nuthan Munaiah, S. Kroh, Craig Cabrey, M. Nagappan
- Computer ScienceEmpirical Software Engineering
- 1 December 2017
This work proposes a framework, and presents a reference implementation of the framework as a tool called reaper, to enable researchers to select GitHub repositories that contain evidence of an engineered software project and identifies software engineering practices (called dimensions) and proposes means for validating their existence in a GitHub repository.
What Do Mobile App Users Complain About?
Insight is provided into the user-reported issues of iOS apps, along with their frequency and impact, which can help developers better prioritize their limited quality assurance resources.
Understanding reuse in the Android Market
- Israel J. Mojica Ruiz, M. Nagappan, B. Adams, A. Hassan
- Computer Science20th IEEE International Conference on Program…
- 11 June 2012
This paper intends to analyze software reuse in the Android mobile app market along two dimensions: (a) reuse by inheritance, and (b) class reuse.
The Impact of Classifier Configuration and Classifier Combination on Bug Localization
- S. W. Thomas, M. Nagappan, D. Blostein, A. Hassan
- Computer ScienceIEEE Transactions on Software Engineering
- 1 October 2013
It is shown that the parameters of a classifier have a significant impact on its performance, and that combining multiple classifiers--whether those classifiers are hand-picked or randomly chosen relative to intelligently defined subspaces of classifier--improves the performance of even the best individual classifiers.
What are the characteristics of high-rated apps? A case study on free Android Applications
- Yuan Tian, M. Nagappan, D. Lo, A. Hassan
- Computer ScienceIEEE International Conference on Software…
- 29 September 2015
It is found that high-rated apps are statistically significantly different in 17 out of the 28 factors that are considered, which shows that the size of an app, the number of promotional images that the app displays on its web store page, and the target SDK version of an application are the most influential factors.
Think locally, act globally: Improving defect and effort prediction models
- Nicolas Bettenburg, M. Nagappan, A. Hassan
- Computer Science9th IEEE Working Conference on Mining Software…
- 2 June 2012
A comparison of three different approaches for creating statistical regression models to model and predict software defects and development effort finds that for both types of data, local models show a significantly increased fit to the data compared to global models.
Diversity in software engineering research
This paper introduces algorithms to compute the sample coverage for a given set of projects and introduces a measure called sample coverage, defined as the percentage of projects in a population that are similar to the given sample.
A Large-Scale Empirical Study on Software Reuse in Mobile Apps
- Israel J. Mojica Ruiz, B. Adams, M. Nagappan, Steffen Dienst, T. Berger, A. Hassan
- Computer ScienceIEEE Software
- 1 March 2014
A study of hundreds of thousands of Android apps across 30 different categories found substantial software reuse, indicating that while these apps benefit from increased productivity, they're also more dependent on the quality of the apps and libraries that they reuse.
Studying the relationship between logging characteristics and the code quality of platform software
Inspired by prior studies on code quality, log-related metrics can complement traditional product and process metrics resulting in up to 40 % improvement in explanatory power of defect proneness and are found to provide strong indicators of defect-prone source code files.
Truth in Advertising: The Hidden Cost of Mobile Ads for Software Developers
- Jiaping Gui, Stuart McIlroy, M. Nagappan, William G. J. Halfond
- Computer ScienceIEEE/ACM 37th IEEE International Conference on…
- 16 May 2015
A study of 21 real world Android apps shows that the use of ads leads to mobile apps that consume significantly more network data, have increased energy consumption, and require repeated changes to ad related code.