The Experts below are selected from a list of 630693 Experts worldwide ranked by ideXlab platform
Torgeir Dingsøyr - One of the best experts on this subject based on the ideXlab platform.
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Software Process Improvement - Software Process Improvement
Lecture Notes in Computer Science, 2004Co-Authors: Torgeir DingsøyrAbstract:One of the challenges for software engineering is collecting meaningful data from industrial projects. Software Process Improvement depends on measurement to provide baseline status and confirming evidence of the effect of Process changes. Without data, any conclusions rely on intuition and guessing. The Team Software ProcessSM (TSPSM) provides a powerful framework for data collection and analysis, in addition to its primary goal as a basis for highly effective software development. In this paper, we describe the experiences of, and benefits realized by, a team using the TSP for the first time. By reviewing how this particular team collected and used data, we show features of the TSP that make it a powerful foundation for software Process Improvement
James R. Armstrong - One of the best experts on this subject based on the ideXlab platform.
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Overcoming barriers to systems engineering Process Improvement
Systems Engineering, 2000Co-Authors: Sarah Sheard, Howard Lykins, James R. ArmstrongAbstract:Neither systems engineering nor Process Improvement is new. Since 1992, INCOSE papers and others have been reporting success in documenting and improving Processes. A considerable body of Process Improvement literature is available, particularly related to Improvement of software development Processes. Even systems engineering Process Improvement is gaining in popularity, judging from the increasing number of INCOSE papers detailing various efforts. Yet the nature of systems engineering poses challenges over and above those seen in other Process Improvement efforts. This paper focuses on identifying and resolving typical barriers to improving the systems engineering Process. © 2000 John Wiley & Sons, Inc. Syst Eng 3: 59–67, 2000
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4 Overcoming Barriers to Systems Engineering Process Improvement
INCOSE International Symposium, 1999Co-Authors: Sarah A. Sheard, Howard Lykins, James R. ArmstrongAbstract:Neither systems engineering nor Process Improvement is new. Since 1992, INCOSE papers and others have been reporting success in documenting and improving Processes. A considerable body of Process Improvement literature is available, particularly related to Improvement of software development Processes. Even systems engineering Process Improvement is gaining in popularity, judging from the increasing number of INCOSE papers detailing various efforts. Yet the nature of systems engineering poses challenges over and above those seen in other Process Improvement efforts. This paper focuses on identifying and resolving typical barriers to improving the systems engineering Process.
Sampath Rajagopalan - One of the best experts on this subject based on the ideXlab platform.
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Process Improvement, Learning, and Real Options
Production and Operations Management, 2008Co-Authors: Sampath RajagopalanAbstract:We use a real-options approach to analyze investments in Process Improvement. We develop a simple, stochastic model of a firm making investment decisions in Process Improvement. Our analysis offers several interesting insights into investments in Process Improvement. First, early investment in Process Improvement results in valuable knowledge, which helps increase the value of the option to invest in Process Improvement in future periods. This may motivate a firm to invest in Process Improvements as early as possible. Second, it may be optimal for a firm to stop investing when such investments do not create enough value in the later stages of the investment horizon. Third, although one would expect the state of a firm's Process relative to that of other firms to impact a firm's decision to invest in Process Improvement, this study finds that the impetus is conditional and identifies these conditions. Finally, in such an environment, the delay of investment in Process Improvement incurs an opportunity cost for a firm, and we show that the traditional net present value rule must incorporate this opportunity cost and the knowledge-induced change in future option values to lead to a correct investment decision.
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Process Improvement, Learning and Real Options
2007Co-Authors: Sampath RajagopalanAbstract:This paper uses a real options approach to analyze investments in Process Improvement. We develop a simple, stochastic model of a firm making investment decisions in Process Improvement. Our analysis offers several interesting insights into investments in Process Improvement. First, early investment in Process Improvement results in valuable knowledge, which helps increase the value of the option to invest in Process Improvement in future periods. This may motivate a firm to invest in Process Improvements as early as possible. Second, it may be optimal for a firm to stop investing when such investments do not create enough value in the later stages of the investment horizon. Third, while one would expect the state of a firm's Process relative to that of other firms to impact a firm's decision to invest in Process Improvement, this study finds that the impetus is conditional and identifies these conditions. Finally, in such an environment, the delay of investment in Process Improvement incurs an opportunity cost for a firm and we show that the traditional NPV (net present value) rule must incorporate this opportunity cost and the knowledge-induced change in future option values to lead to a correct investment decision.
John S. Snyder - One of the best experts on this subject based on the ideXlab platform.
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Quantitative evaluation of software Process Improvement
Journal of Systems and Software, 1995Co-Authors: Joel Henry, Allan J. Rossman, John S. SnyderAbstract:Abstract This article describes statistical analysis techniques and results used to quantitatively evaluate software Process Improvement. The analysis techniques include linear regression, rank correlation, and χ2 tests that have been successfully used to quantitatively assess the software Process of a large military subcontractor. A logical extension of this work is to examine the results of these statistical techniques after Process Improvement. We perform these investigations by altering original data to reflect varying types and degrees of Process Improvements and then repeating the statistical analyses. We find that different types of Process Improvement generate very different statistical results. The techniques and results presented here can be used to evaluate the effectiveness of Process Improvements and determine where continued Process Improvement is needed.
Torkarrichard - One of the best experts on this subject based on the ideXlab platform.
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Software test Process Improvement approaches
Journal of Systems and Software, 2016Co-Authors: Afzalwasif, Alonesnehal, Glocksienkerstin, TorkarrichardAbstract:A total of 18 software test Process Improvement (STPI) approaches are identified.These approaches are evaluated with respect to general applicability in industry.Two STPI approaches, TPI NEXT and T...
