206448594
Enhancing the Cocomo Estimation Models
In software engineering, team task assignments appear to have a significant potential impact on a project's overall success. The authors propose task assignment effort adjustment factors that can help tune existing estimation models. They show significant improvements in the predictive abilities of both Cocomo I and II by enhancing them with these factors.
2351489
An Empirical Study Using Task Assignment Patterns to Improve the Accuracy of Software Effort Estimation
In most software development organizations, there is seldom a one-to-one mapping between software developers and development tasks. It is frequently necessary to concurrently assign individuals to multiple tasks and to assign more than one individual to work cooperatively on a single task. A principal goal in making such assignments should be to minimize the effort required to complete each task. But what impact does the manner in which developers are assigned to tasks have on the effort requirements? This paper identifies four task assignment factors: team size, concurrency, intensity, and fragmentation. These four factors are shown to improve the predictive ability of the well-known intermediate COCOMO cost estimation model. A parsimonious effort estimation model is also derived that utilizes a subset of the task assignment factors and unadjusted function points. For the data examined, this parsimonious model is shown to have goodness of fit and quality of estimation superior to that of the COCOMO model, while utilizing fewer cost factors.
6086610
Security for fixed sensor networks
Sensor networks consist of resource-constrained sensors operating in a variety of environments. Given the severe constraints on these sensors, it is a particularly challenging problem to choose and design valid security protocols for such networks. This problem has recently given rise to new research addressing the security issues. This paper presents an overview of the important works, specifically the new mechanisms and protocols, which have been introduced or are still under development in this area.
11105386
Automated auditing of design principle adherence
Software design patterns and refactoring browsers are useful tools in developing high-quality software. Object-Oriented Oracle (OOO) is a tool that combines patterns and refactoring and extends them with the ability to recognize when the source-base doesn't adhere to software design principles. OOO relies on sophisticated compiler analyses and a set of heuristics to recognize characteristics of the code where a design principle is applicable, but is not being used. We present an example where the OOO can recognize noncompliance of design rules and the analyses and heuristics that are used to do the recognition. We also discuss other patterns where this approach applies and results from a prototype.
17812918
Acquiring and delivering lessons learned for NASA scientists and engineers: a dynamic approach
Web forms are a common mechanism for collecting information online. They pose some limitations which negatively affect ease and flexibility of user interaction. These limitations are more pronounced when collecting information that can not be broken down into well defined and agreed upon structures. Lessons Learned or any kind of 'knowledge' is an example of such information. In this paper we introduce a concept of 'Dynamic Forms' which is aimed at enhancing user interaction while collecting unstructured information, 'Lessons Learned' in particular.
44358582
Strategies to Improve Variable Selection Performance
36936116
Design of Knowledge-Based Systems with a Knowledge-Based Assistant
The authors propose a model for an intelligent assistant to aid in building knowledge-based systems (KBSs) and discuss a preliminary implementation. The assistant participates in KBS construction, including acquisition of an initial model of a problem domain, acquisition of control and task-specific inference knowledge, testing and validation, and long-term maintenance of encoded knowledge. The authors present a hypothetical scenario in which the assistant and a KBS designer cooperate to create an initial domain model and then discuss five categories of knowledge the assistant requires to offer such help. They discuss two software technologies on which the assistant is based: an object-oriented programming language, and a user-interface framework. >
33919116
The Fighter Aircraft LCS: A Case of Different LCS Goals and Techniques
A system employed by the authors to acquire novel fighter aircraft manoeuvres from combat simulation is more akin to the traditional LCS model than to more recent systems. Given the difficulties often experienced in LCS research on simple problems, one must ask how a relatively primitive LCS has had consistent success in the complex domain of fighter aircraft manoeuvring. This paper presents the fighter aircraft LCS, in greater detail than in previous publications. Positive results from the system are discussed. The paper then focuses on the primary reasons the fighter aircraft LCS has avoided the difficulties of the traditional LCS. The authors believe the system's success has three primary origins: differences in credit assignment, differences in action encoding, and (possibly most importantly) a difference in system goals. In the fighter aircraft system, the goal has been simply the discovery of innovative, novel tactics, rather than online control. The paper concludes by discussing the most salient features of the fighter aircraft learning system, and how those features may be profitably combined with other LCS developments.
3217704
Conceptual-Model-Based Data Extraction from Multiple-Record Web Pages
Abstract Electronically available data on the Web is exploding at an ever increasing pace. Much of this data is unstructured, which makes searching hard and traditional database querying impossible. Many Web documents, however, contain an abundance of recognizable constants that together describe the essence of a document's content. For these kinds of data-rich, multiple-record documents (e.g., advertisements, movie reviews, weather reports, travel information, sports summaries, financial statements, obituaries, and many others) we can apply a conceptual-modeling approach to extract and structure data automatically. The approach is based on an ontology – a conceptual model instance – that describes the data of interest, including relationships, lexical appearance, and context keywords. By parsing the ontology, we can automatically produce a database scheme and recognizers for constants and keywords, and then invoke routines to recognize and extract data from unstructured documents and structure it according to the generated database scheme. Experiments show that it is possible to achieve good recall and precision ratios for documents that are rich in recognizable constants and narrow in ontological breadth. Our approach is less labor-intensive than other approaches that manually or semiautomatically generate wrappers, and it is generally insensitive to changes in Web-page format.
27655269
Unobserved heterogeneity in panel time series models
Recently, the large T panel literature has emphasized unobserved, time-varying heterogeneity that may stem from omitted common variables or global shocks that affect each individual unit differently. These latent common factors induce cross-section dependence and may lead to inconsistent regression coefficient estimates if they are correlated with the explanatory variables. Moreover, if the process underlying these factors is nonstationary, the individual regressions will be spurious but pooling or averaging across individual estimates still permits consistent estimation of a long-run coefficient. The need to tackle both error cross-section dependence and persistent autocorrelation is motivated by the evidence of their pervasiveness found in three well-known, international finance and macroeconomic examples. A range of estimators is surveyed and their finite-sample properties are examined by means of Monte Carlo experiments. These reveal that a mean group version of the common-correlated-effects estimator stands out as the most robust since it is the preferred choice in rather general (non) stationary settings where regressors and errors share common factors and their factor loadings are possibly dependent. Other approaches which perform reasonably well include the two-way fixed effects, demeaned mean group and between estimators but they are less efficient than the common-correlated-effects estimator.
33698159
On the Development of Commercial Expert Systems
We use our experience with the Dipmeter Advisor system for well-log interpretation as a case study to examine the development of commercial expert system. We discuss the nature of these systems as we see them in the coming decade, characteristics of the evolution process, development methods, and skills required in the development team. We argue that the tools and ideas of rapid prototyping and successive refinement accelerate the development process. We note that different types of people are required at different stages of expert system development: Those who are primarily knowledgeable in the domain, but who can use the framework to expand the domain knowledge; and those who can actually design and build expert systems. Finally, we discuss the problem of technology transfer and compare our experience with some of the traditional wisdom of expert system development.