Sampson Gholston

Project Manager Skill Development: A Survey of Programs and Practitioners

Abstract: This article reviews project management education, from graduate and certificate programs to organizational programs. It includes survey results of current practitioners with regard to project management training. It has been found that there are both graduate and certificate programs that cover the recommended project knowledge areas. Less than half of the organizations in the survey had any type of project management training program and 41% of project managers felt their organizations prepared them for their role. From those project managers who had been trained, 73% felt the training prepared them for their role. Recommendations are provided for employees, employers, and academia to help bridge the gap between current training and skills necessary for project managers. An overview of one program that has been developed is provided.

A comparison of cohesion metrics for object-oriented systems

Abstract Cohesion is the degree to which the elements of a class or object belong together. Many different object-oriented cohesion metrics have been developed; many of them are based on the notion of degree of similarity of methods. No consensus has yet arisen as to which of these metrics best measures cohesion; this is a problem for software developers since there are so many suggested metrics, it is difficult to make an informed choice. This research compares various cohesion metrics with ratings of two separate teams of experts over two software packages, to determine which of these metrics best match human-oriented views of cohesion. Additionally, the metrics are compared statistically, to determine which tend to measure the same kinds of cohesion. Differences in results for different object-oriented metrics tools are discussed.

A semantic entropy metric

This paper presents a new semantically-based metric for object-oriented systems, called the Semantic Class Definition Entropy (SCDE) metric, which examines the implementation domain content of a class to measure class complexity. The domain content is determined using a knowledge-based program understanding system. The metrics examination of the domain content of a class provides a more direct mapping between the metric and common human complexity analysis than is possible with traditional complexity measures based on syntactic aspects (software aspects related to the format of the code). Additionally, this metric represents a true design metric that can measure complexity early in the life cycles of software maintenance and software development. The SCDE metric is correlated with analyses from a human expert team, and is also compared to syntactic complexity measures.

Semantic software metrics computed from natural language design specifications

An approach using semantic metrics to provide insight into software quality early in the design phase of software development by automatically analysing natural language (NL) design specifications for object-oriented systems is presented. Semantic metrics are based on the meaning of software within the problem domain. In this paper, we extend semantic metrics to analyse design specifications. Since semantic metrics can now be calculated from early in design through software maintenance, they provide a consistent and seamless type of metric that can be collected through the entire lifecycle. We discuss our semMet system, an NL-based program comprehension tool we have expanded to calculate semantic metrics from design specifications. To validate semantic metrics from design specifications and to illustrate their seamless nature across the software lifecycle, we compare semantic metrics from different phases of the lifecycle, and we also compare them to syntactically oriented metrics calculated from the source code. Results indicate semantic metrics calculated from design specifications can give insight into the quality of the source code based on that design. Also, these results illustrate that semantic metrics provide a consistent and seamless type of metric that can be collected through the entire lifecycle.

Direct Demand Forecasting Model for Small Urban Communities Using Multiple Linear Regression

Forecasting traffic volumes to support infrastructure decisions is the heart of the travel demand modeling process. The most commonly used methodology for obtaining these forecasted traffic volumes is the four-step process that considers generation, distribution, mode choice, and route assignment of trips. Each step of the process is performed independently, almost always through the use of computer software, to achieve the final traffic volumes. This paper examines the possibility of forecasting traffic volumes by using a multiple linear regression model to perform what is termed direct demand forecasting. The direct demand forecasting model generates traffic volumes for roadways through the development of a functional relationship between roadway characteristics and socioeconomic influences. A direct demand travel forecasting model has been developed and applied, with a small urban area as a case study community. Results are consistent with those obtained from the traditional four-step methodology.

Evaluating Technology Projections and Weight Prediction Method Uncertainty of Future Launch Vehicles

A process was developed for determining the impact of technology performance assumptions and weight predictionmethod uncertainty.Weight and performance uncertainties were defined for components from historical weight-estimating relationships that are typically used during the concept definition phase. A systems analysis model was developed that sizes vehicle geometry, propellant, and component weights to meet mission requirements. The uncertainties and system analysismodelwere integratedwith aMonteCarlo simulation to determine the uncertainty probability on system weight. These uncertainties were integrated into the analyses of single-stage and two-stage reusable launch concepts to demonstrate the technology uncertainty influence on concepts having different gross weight sensitivities to component weight changes. Finally, this process was extended as a model for measuring the progress of technology development programs.

SEMANTIC METRICS: METRICS BASED ON SEMANTIC ASPECTS OF SOFTWARE

Software practitioners need ways to assess their software, and metrics can provide an automated way to do that, providing valuable feedback with little effort earlier than the testing phase. Semantic metrics were proposed to quantify aspects of software quality based on the meaning of softwares task in the domain. Unlike traditional software metrics, semantic metrics do not rely on code syntax. Instead, semantic metrics are calculated from domain information, using the knowledge base of a program understanding system. Because semantic metrics do not rely on code syntax, they can be calculated before code is fully implemented. This article evaluates the semantic metrics theoretically and empirically. We find that the semantic metrics compare well to existing metrics and show promise as early indicators of software quality.

Considering Risk Within Net Present Value: Calculations for Government Projects

The vision for space includes Shuttle retirement by 2010 and development of new launch vehicles; however, budget increases are not projected. To control costs additional insight into cost factors early in the system life cycle is needed. This article reports on a new launch vehicle upper-stage engine trade study where insight into cost factors was gained by using net present value and applying a set of risk factors to incorporate the risks inherent to key system life cycle phases. A matrix is presented that provides a general framework for assessing these risk levels. This approach shows the effects of various cost factors on the system cost and requires modest resource expenditures for the analysis itself.

Investigation of domain effects on software

It has been stated that there is very less variability in cohesion, coupling and complexity of software packages within specific domains such as Graphical User Interface (GUI). This implies that software metrics show low variability within single domain and high variability between domains. This paper investigates the domain issue by creating hierarchical model of four different domains and two software packages within each domain. Metrics are collected on each package and compared against the domains and packages. Results confirm metrics are not domain centric.

Evaluation of Network Preloads on a Medium-Sized Urban Travel Forecast Model

Transportation engineers and planners attempt to understand urban travel characteristics to develop, formulate, and analyze problems and opportunities better. Transportation professionals use urban transportation models and typically implemented the four-step urban transportation planning process. This study examined a modified planning process that preassigned external trips to the transportation network before distributing and assigning internal trips. The preassignment, or preloading, of external trips helped to ensure that trips passing through the network were assigned to only the major through routes and that internal trips were modeled with the knowledge that external trips were present on the roadways before selecting destination or route. The study concluded that the preload methodology did not affect the validity of a travel model in a medium-sized urban travel forecast model and reduced assignment error on minor arterial roadways, which would not be the typical routes used by external travelers, to a level below the maximum deviation where an incorrect decision would be made regarding improvements to the roadway infrastructure.