Projects

CNS 1951411

National Science Foundation: NSF

Miroslav Tushev and Fahimeh Ebrahimi

The recent decade has witnessed a major shift in the way people deal services and goods. This shift has been enabled by the emergence of a new form of Peer-to-Peer (P2P) business exchange, known as Sharing Economy (SE). This on-demand, convenient, and sustainable form of resource consumption has attracted consumers and investors around the globe, providing unprecedented opportunities for individuals in low-income and marginalized communities to find employment, generate extra income, increase reciprocity, and access resources that are unattainable otherwise. This project will utilize SE as a vehicle for fostering economic growth, promoting ecological sustainability, and building social capital among disadvantaged communities in the city of Baton Rouge, the political capital of the State of Louisiana. According to the U.S. Census Bureau, the economic gap between rich and poor in Baton Rouge is the fourth-highest in the country, with close to 25% of Baton Rouge population living below the poverty line. To achieve our goals, we propose an integrative research and community engagement plan that will use methods of quantitative and qualitative research to, a) identify success factors of SE in our target communities, b) explore the landscape of underutilized services and assets, c) identify fundamental shortcomings and socio-technical barriers to adaptation, and d) investigate mitigation strategies for these problems. Based on this foundational information, the project will deliver novel systematic solutions to fundamental requirements engineering and software design problems in the context of SE. These solutions will enable software engineers to design SE systems that are optimized to help individuals in resource-constrained communities to overcome social barriers and move up the economic ladder. The project will further facilitate interdisciplinary research by providing researchers, across a broad range of disciplines (e.g., social, technical, economic, and legal), with automated frameworks for analyzing the complex and increasingly coupled relations between the human, market, and technology components of SE. The project will also foster community engagement by establishing partnerships between stakeholders from local communities, local organizations of social work, researchers from local minority-serving institutions (MSI), K-12, and undergraduate students from underrepresented groups.

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Economic Developement Enhancment

Grant Williams and Fahimeh Ebrahimi

This project seeks to utilize user feedback on app stores and social media to devise dynamic, self-organizing, and domain-specific software feature models. These models will enable app developers to track the shift in their end-users’ expectations and needs, systematically realize the tradeoffs of adding, altering, and dropping features, predict the impact of feature updates on their end-user acquisition and retention rates, and ultimately, survive in the highly volatile and competitive mobile app market.

LEQSF(2015-18)-RD-A-07

Louisiana Board of Regents RCS program

Saket Khatiwada and Nishant Jha

Contemporary software engineering tools employ Natural Language Processing (NLP) techniques and Information Retrieval (IR) methods for automated support. Such methods exploit the semantic and syntactic knowledge embedded in the textual content of source code to discover important information about the system. Such information can then be utilized in several essential software engineering activities such as traceability, refactoring, and reverse engineering. However, as software evolves, new and inconsistent terminology gradually finds its way into the project, leading the textual content of source code to drift to the unnatural side. Furthermore, source code is highly repetitive, often homogeneous, and suffers from data sparsity and vocabulary mismatch problems. Therefore, applying NLP and IR methods to source code without adjustment can be detrimental. Motivated by these observations, in this proposal we suggest a novel text-processing paradigm adjusted for software. Our main objectives are (1) to introduce an effective, scalable, and computationally-efficient paradigm for processing and analyzing the textual content of source code, and (2) to integrate the proposed paradigm in working prototypes that provide support for several essential software engineering activities. To achieve our objectives, we will conduct a series of analytical experiments, using industrial software systems, to establish the main constructs of our paradigm. Furthermore, sets of human studies will be conducted to assess the usability and effectiveness of our proposed tools. The broader significance of this research arises from the economical impact of the design and development of software engineering tools that enhance software developers’ productivity and ability to produce high-quality software.

CCF:1821525

National Science Foundation: NSF

Miroslav Tushev and Saket Khatiwada

The project explores a theory of open source software (OSS) evolution based on statistical natural language processing techniques. Based on the emerging recognition that software code is, in many ways, as "natural" as natural language (e.g., English), there is a trend to apply statistical models for software development tasks such as code analysis, comprehension, and programmer support. This grant extends the "naturalness of code" theory by studying how the code lexicon evolves in open source software as different developers work on a software project and features are added, modified, deleted. The goal is to learn the extent to which the evolution of a developer's lexicon follows the laws of natural language evolution. To create the needed demonstration, large datasets of code lexicons are being collected from a large number of OSS projects and their revisions (on GitHub and SourceForge). The main constructs of the frequency model of natural language evolution will be applied to track and identify the main patterns of language changes (e.g., birth, propagation, death of terms in the lexicon) throughout OSS projects life cycle. Part of the challenge is to better understand how events that instigate code evolution, such as maintenance activities and team formation, are fundamentally different from the events that instigate change in natural language, such as war and migration. The research should lead to new ways to predict software project outcomes and to improve software productivity and quality. The project will make available the data, tools, and algorithms that will be produced by the project, which will support future work to understand the dynamics of code evolution in open source software ecosystems.

PG 990011

LSU Emerging Research Grants

This project investigates the OSS movement and its potential contribution to the economic development of the State. In particular, the innovation of this project lies in building an infrastructure for establishing and sustaining an active relation between academia and the local software industry through the OSS link. This infrastructure will include training programs, course modules, and software tools that are designed to prepare the new generation of software developers in Louisiana.