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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The Pairwise Comparison technique is a general purpose estimation approach for capturing expert judgment. This approach can be generalized to a probabilistic version using Monte Carlo methods to produce estimates of size distributions.
This paper describes the approach and algorithms used to generalize the paired ratio comparison matrix technique to use information inherent in multiple estimates, multiple reference projects, and estimator range information to generate estimated effort and size distributions.
The Technology Implementation and Support Section at Martin Marietta Astronautics Group Denver is tasked with software development analysis, data collection, software productivity improvement and developing and applying various computerized software tools and models. The computerized tools are parametric models that reflect actuals taken from the large data base of completed software development projects. Martin Marietta's data base consists of over 300 completed projects and hundreds of cost estimating relationships (CERs) that are used in sizing, costing, scheduling and productivity improvement equations, studies, models and computerized tools.
This presentation has two parts: (a) Sizing the System and (b) Case Study.
The length, or size (in number of Source Lines of Code) of programs represented as state machines, it is demonstrated, can be reliably estimated in terms of the number of internal state machine variables.
A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.
As object-oriented software development methods come into more widespread use, basic questions of software quality assurance must be reconsidered. We will highlight efforts now underway at NASA's Jet Propulsion Laboratory to both assess the quality of software systems developed using object oriented technology and develop guidelines for future development of such systems. The current focus is on design and code reusability., and system size estimation. A number of metrics are proposed and two software systems measured and analyzed. The preliminary results reported here should be useful to software development and quality assurance personnel working in C++ implementation environment.
Method of estimating size and complexity of large computer program under development based on metric called "function mass." Simplification of Demarco's "function bang" metric. Size of completed program usually expressed in terms of number of lines of code (SLOC), shown in previous research to be highly correlated with amount of development effort and therefore important predictor of development cost. Proposed method of estimating ultimate size of program is intermediate product of continuing research on estimation of size and structured analysis of developmental software.
Estimates of the AP101 memory and central processing unit (CPU) requirements for the space shuttle orbiter are presented. The resource estimates reflect OASCAB approved change requests for Release 18 and Release 19. Memory sizes are presented in 32 bit full words, CPU loading is listed by percentage. Memory and CPU information was obtained from actual AP101 code where available, and from estimates provided by flight software development programmers.
This paper presents lessons learned by the Software Engineering Process Group (SEPG) from results of supporting two projects at NASA Ames using an Object Oriented Rapid Prototyping (OORP) approach supported by a full featured visual development environment. Supplemental lessons learned from a large project in progress and a requirements definition are also incorporated. The paper demonstrates how productivity gains can be made by leveraging the developer with a rich development environment, correct and early requirements definition using rapid prototyping, and earlier and better effort estimation and software sizing through object-oriented methods and metrics. Although the individual elements of OO methods, RP approach and OO metrics had been used on other separate projects, the reported projects were the first integrated usage supported by a rich development environment. Overall the approach used was twice as productive (measured by hours per OO Unit) as a C++ development.
The presentation will provide a brief overview of the SQI measurement program as well as describe each of these models and how they are currently being used in supporting JPL project, task and software managers to estimate and plan future software systems and subsystems.
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This slide presentation reviews the research project named N-Set. The goal of this project is to create a user friendly tool for estimating the cost and size of software development. Using the historical experience which NASA has desire is to create a tool that will give an early Rough Order Magnitude (ROM) estimate of the cost and size of a software development task without using the lines of code as a primary input value.
A substantial amount of software engineering research effort was focused on the development of software estimation models. A measure of lines of code was derived based on the origin of the delivered code, L sub dev = N + E + 0.2 (S + O) (where L sub dev = developed lines of code, N = newly implemented lines of code, E = extensively modified lines of code, S = slightly modified lines of code, and O = old unchanged lines of code) that is substituted in the following equation H sub s = aL sup b (where H sub s = staff-hours of effort, L = lines of code, a = a constant, and b = a constant). The limitations of this model are discussed and some alternative estimation models that can be used earlier in the development process are proposed.
Software Cost Estimation Model program, SOFTCOST, developed to provide consistent automated resource-and-schedule mathematical model more formalized than guesswork model. Combines several software-cost models found in open literature into one comprehensive set of algorithms compensating for nearly 50 implementation factors relative to size of task, inherited baseline, organizational and system environment, and difficulty of task. Produces mean and variance estimates of software size, implementation productivity, recommended staff level, probable duration, amount of computer resources required, and amount and cost of software documentation. Written in Microsoft BASIC.
A major effort within NASA's vehicle analysis discipline has been to automate structural analysis and sizing optimization during conceptual design studies of advanced spacecraft. Traditional spacecraft structural sizing has involved detailed finite element analysis (FEA) requiring large degree-of-freedom (DOF) finite element models (FEM). Creation and analysis of these models can be time consuming and limit model size during conceptual designs. The goal is to find an optimal design that meets the mission requirements but produces the lightest structure. A structural sizing tool called HyperSizer has been successfully used in the conceptual design phase of a reusable launch vehicle and planetary exploration spacecraft. The program couples with FEA to enable system level performance assessments and weight predictions including design optimization of material selections and sizing of spacecraft members. The software's analysis capabilities are based on established aerospace structural methods for strength, stability and stiffness that produce adequately sized members and reliable structural weight estimates. The software also helps to identify potential structural deficiencies early in the conceptual design so changes can be made without wasted time. HyperSizer's automated analysis and sizing optimization increases productivity and brings standardization to a systems study. These benefits will be illustrated in examining two different types of conceptual spacecraft designed using the software. A hypersonic air breathing, single stage to orbit (SSTO), reusable launch vehicle (RLV) will be highlighted as well as an aeroshell for a planetary exploration vehicle used for aerocapture at Mars. By showing the two different types of vehicles, the software's flexibility will be demonstrated with an emphasis on reducing aeroshell structural weight. Member sizes, concepts and material selections will be discussed as well as analysis methods used in optimizing the structure. Analysis based on the HyperSizer structural sizing software will be discussed. Design trades required to optimize structural weight will be presented.
In aerospace power systems, mass and volume are key considerations to produce a viable design. The utilization of fuel cells is being studied for a commercial aircraft electrical power unit. Based on preliminary analyses, a SOFC/gas turbine system may be a potential solution. This paper describes the parametric mass and volume models that are used to assess an aerospace hybrid system design. The design tool utilizes input from the thermodynamic system model and produces component sizing, performance, and mass estimates. The software is designed such that the thermodynamic model is linked to the mass and volume model to provide immediate feedback during the design process. It allows for automating an optimization process that accounts for mass and volume in its figure of merit. Each component in the system is modeled with a combination of theoretical and empirical approaches. A description of the assumptions and design analyses is presented.
The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.