ASCoT R2: A Web-Based Version of the NASA Analogy Software Costing Tool Goodbye Excel
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Engineering topics
Publications and source records attributed to Hihn, Jairus.
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Estimators and analysts are increasingly being tasked to develop better models and reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods for cost estimation, there is very little focus on the use of cost models based on analogy and clustering algorithms. In this paper we summarize the results of our research in developing an analogy method for estimating NASA spacecraft flight software using spectral clustering on system characteristics (symbolic nonnumerical data) and evaluate its performance by comparing it to a number of the most commonly used estimation methods. The strengths and weaknesses of each method based on their performance are also discussed. The paper concludes with an overview of the analogy estimation tool (ASCoT) developed for use within NASA that implements the recommended analogy algorithm.
The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K- nearest neighbor prediction model performance on the same data set.
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The software industry repeatedly observes cost growth of well over 100% even after decades of cost estimation research and well-known best practices, so “What’s the problem?” In this paper we will provide an overview of the current state of software cost estimation best practice. We then explore whether applying some of the methods used in software assurance might improve the quality of software cost estimates. This paper especially focuses on issues associated with model calibration, estimate review, and the development and documentation of estimates as part of an integrated plan.
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Over the past sixteen years, government aerospace agencies and aerospace industry have developed and evolved operational concurrent design teams to create novel spaceflight mission concepts and designs. These capabilities and teams, however, have evolved largely independently. In today's environment of increasingly complex missions with limited budgets it is becoming readily apparent that both implementing organizations and today's concurrent engineering teams will need to interact more often than they have in the past. This will require significant changes in the current state of practice. This paper documents the findings from a concurrent engineering workshop held in August 2010 to identify the key near term improvement areas for concurrent engineering capabilities and challenges to the long-term advancement of concurrent engineering practice. The paper concludes with a discussion of a proposed vision for the evolution of these teams over the next decade.
As aerospace missions grow larger and more technically complex in the face of ever tighter budgets, it will become increasingly important to use concurrent engineering methods in the development of early conceptual designs because of their ability to facilitate rapid assessments and trades in a cost-efficient manner. To successfully accomplish these complex missions with limited funding, it is also essential to effectively leverage the strengths of individuals and teams across government, industry, academia, and international agencies by increased cooperation between organizations. As a result, the existing concurrent engineering teams will need to increasingly engage in distributed collaborative concurrent design. This paper is an extension of a recent white paper written by the Concurrent Engineering Working Group, which details the unique challenges of distributed collaborative concurrent engineering. This paper includes a short history of aerospace concurrent engineering, and defines the terms 'concurrent', 'collaborative' and 'distributed' in the context of aerospace concurrent engineering. In addition, a model for the levels of complexity of concurrent engineering teams is presented to provide a way to conceptualize information and data flow within these types of teams.
This presentation has two parts: (a) Sizing the System and (b) Case Study.
This presentation is about cost risk identification and estimation which is only a part of risk management. The purpose of this step is to identify common software risks, to assess their impact on the cost estimate, and to make revisions to the estimate based on these impacts.
As aerospace missions grow larger and more technically complex in the face of ever tighter budgets, it will become increasingly important to use concurrent engineering methods in the development of early conceptual designs because of their ability to facilitate rapid assessments and trades of performance, cost and schedule. To successfully accomplish these complex missions with limited funding, it is essential to effectively leverage the strengths of individuals and teams across government, industry, academia, and international agencies by increased cooperation between organizations. As a result, the existing concurrent engineering teams will need to increasingly engage in distributed collaborative concurrent design. The purpose of this white paper is to identify a near-term vision for the future of distributed collaborative concurrent engineering design for aerospace missions as well as discuss the challenges to achieving that vision. The white paper also documents the advantages of creating a working group to investigate how to engage the expertise of different teams in joint design sessions while enabling organizations to maintain their organizations competitive advantage.
The objectives of this work are: To improve risk assessment practices as used during the mission design process by JPL's concurrent engineering teams. (1) Developing effective ways to identify and assess mission risks (2) Providing a process for more effective dialog between stakeholders about the existence and severity of mission risks (3) Enabling the analysis of interactions of risks across concurrent engineering roles.