National Science Foundation

Code Decay in Legacy Software Systems: Measurement, Models, and Statistical Strategies

Case Study

Challenges

Solutions


Research Project

One of the main features of the evolution of large software systems is that change-which is necessary to add new functionality, accommodate new hardware, and repair faults-becomes increasingly difficult over time. This phenomenon, which NISS called code decay, was studied by the team. They proposed a number of measurements (code decay indices) on software and on the organizations that produce it, that serve as symptoms, risk factors, and predictors of decay.

Synthetic Longitudinal Business Database

Research Project

The Longitudinal Business Database (LBD) is a census of business establishments in the U.S. with paid employees that was developed by the Center for Economic Studies at the U.S. Bureau of the Census. It supports an active research agenda focusing on business entry and exit, gross employment flows, employment volatility, industrial organization, and other topics that cannot be adequately addressed with establishment-level data.

NSF-Census Research Network

Research Project

NISS and Duke University are collaborating on the Triangle Census Research Network (TCRN), one of eight research nodes that are working on the National Census Research Network (NCRN). NISS and Duke are looking at ways to improve how federal statistical (“FedStats”) agencies disseminate data to the public and to researchers.

World's Simplest Survey Microsimulator (WSSM)

Research Project

Official statistics surveys face a constant tradeoff between data quality and cost, which is dictated by current and anticipated budget pressures.   The World’s Simplest Survey Microsimulator (WSSM) was developed to work as a laboratory for survey scientists so they can try various scenarios out in order to make decisions.NISS sponsored an interdisciplinary Workshop on Microsimulation Models for Surveys. Simulation to explore three issues: need, utility and feasibility—surrounding simulation models for Federal surveys.

Postdoctoral Research in Support of the National Center for Science and Engineering Statistics

Case Study

Challenges

Solutions

Outcomes & Results


Research Project

Two postdoctoral fellows will work on research aspects of longitudinal analyses using the Survey of Doctoral Recipients and small domain estimation for several SRS surveys.According to the NSF website, "The Survey of Doctorate Recipients is a longitudinal biennial survey conducted since 1973 that provides demographic and career history information about individuals with a research doctoral degree in a science, engineering, or health (SEH) field from a U.S. academic institution.

Dynamics for Social Networks Processes: Comparing Statistical Models with Intelligent Agents

Case Study

Challenges

Solutions


Research Project

The goal of this project is to reconcile two methods for modeling change in social networks over time: a class of statistical models and intelligent agent models. The research contrasts the roperties of these two approaches, exploring what qualitative dynamic behaviors in social networks are captured usefully and interpretably by each. The primary tools are latent variable representations and dynamical systems analysis.

Collaborative Research: Acquiring Accurate Dynamic Field Data Using Lightweight Instrumentation

Research Project

Software engineering researchers use machine learning techniques to model and predict program execution behaviors. NISS helped software engineers by designing, implementing and evaluating light weight instrumentation for software testing and profiling to best optimize their performance.

Digital Government II: Data Confidentiality, Data Quality and Data Integration For Federal Databases: Foundations to Software Prototypes

Research Project

NISS conducted research in data confidentiality, data quality, and data integration. Prototypes were built which could scale to operate on large sets of Federally held data. Researchers partnered with several large Federal Government statistical agencies. This topic was of particular importance given the balance of these agencies must strive for, in terms of their dual missions to collect and keep private confidential data, while at the same time making that data accessible for research and policy issues.

Computer Model Evaluation

Research Project

Though inherently statistical, model evaluation lacks a unifying statistical framework. NISS was hired to help find a overlying system to help with model evaluation. The research team used Bayesian techniques to measure the degree to which a model captures the underlying reality; theory and methods that allowed dual use of data in both estimation of model inputs and evaluation of outputs. SFCME also involved selection of evaluation functions by which a model and reality are compared. It also looked at design for determining what field or computer simulation data to collect.

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