... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perce... more ... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perception differences of software success: Provider and user views of system metrics. ... June M.Verner is a Visiting Professor at The University of New South Wales. back to top Footnotes. ...
Understanding what software practitioners value and how they define project success has implicati... more Understanding what software practitioners value and how they define project success has implications for both practitioner motivation and software development productivity. We conducted a survey to discover some of the components of project outcome (in terms of personal/professional aspects as well as the project as a whole) that practitioners consider important in defining project success. We also investigated some of those components that practitioners perceived were important contributors to success through their impact on the development process. Sixty-six practitioners participated in our study. They considered software projects to be successful if they provide them with intrinsic, internally motivating work in developing software systems that both meet customer/ user needs and are easy to use.
Software has been developed since the 1960s but the success rate of software development projects... more Software has been developed since the 1960s but the success rate of software development projects is still low. During the development of software, the probability of success is affected by various practices or aspects. To date, it is not clear which of these aspects are more important in influencing project outcome.In this research, we identify aspects which could influence project success, build prediction models based on the aspects using data collected from multiple companies, and then test their performance on data from a single organization.A survey-based empirical investigation was used to examine variables and factors that contribute to project outcome. Variables that were highly correlated to project success were selected and the set of variables was reduced to three factors by using principal components analysis. A logistic regression model was built for both the set of variables and the set of factors, using heterogeneous data collected from two different countries and a variety of organizations. We tested these models by using a homogeneous hold-out dataset from one organization. We used the receiver operating characteristic (ROC) analysis to compare the performance of the variable and factor-based models when applied to the homogeneous dataset.We found that using raw variables or factors in the logistic regression models did not make any significant difference in predictive capability. The prediction accuracy of these models is more balanced when the cut-off is set to the ratio of success to failures in the datasets used to build the models. We found that the raw variable and factor-based models predict significantly better than random chance.We conclude that an organization wishing to estimate whether a project will succeed or fail may use a model created from heterogeneous data derived from multiple organizations.
Initiated in 1992, the international PILPS project aims to evaluate and intercompare land-surface... more Initiated in 1992, the international PILPS project aims to evaluate and intercompare land-surface parameterization packages, destined for embedding into atmospheric general circulation models. The Project for Intercomparison of Landsurface Parameterization Schemes (PILPS) involves 27 numerical submodels to describe the interaction of the land surface with the overlying atmosphere. This project offers the opportunity of not only comparing the physical basis and simulation results of these land-surface codes, but also for collecting software engineering metrics on the codes themselves. The existing PILPS infrastructure supported the data collection of measures of the pieces of FORTRAN code in an organized fashion. A number of questions were included in a data gathering exercise, via questionnaire, regarding the structural complexity of the codes. Even for this parsimonious set of metrics, adequate data were returned for only 7 of the 27 land-surface parameterization schemes involved in the PILPS intercomparison. Results from these seven data sets are analyzed here in terms of control flow complexity and size. A second experiment is also described briefly. This was conducted to evaluate, subjectively, the overall “complexity” of four of the PILPS codes. Eight senior climate researchers, all of whom are also established FORTRAN programmers, were asked to evaluate the code listings using a questionnaire. These data were evaluated and their relationship to the objective measures assessed. A surprisingly good correlation was found between many of the standard, objective metrics and subjective assessments of overall “complexity.”
... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perce... more ... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perception differences of software success: Provider and user views of system metrics. ... June M.Verner is a Visiting Professor at The University of New South Wales. back to top Footnotes. ...
Proceedings of the Ifip Wg8 2 Working Group on Information Systems Development Human Social and Organizational Aspects Human Organizational and Social Dimensions of Information Systems Development, May 17, 1993
... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perce... more ... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perception differences of software success: Provider and user views of system metrics. ... June M.Verner is a Visiting Professor at The University of New South Wales. back to top Footnotes. ...
Understanding what software practitioners value and how they define project success has implicati... more Understanding what software practitioners value and how they define project success has implications for both practitioner motivation and software development productivity. We conducted a survey to discover some of the components of project outcome (in terms of personal/professional aspects as well as the project as a whole) that practitioners consider important in defining project success. We also investigated some of those components that practitioners perceived were important contributors to success through their impact on the development process. Sixty-six practitioners participated in our study. They considered software projects to be successful if they provide them with intrinsic, internally motivating work in developing software systems that both meet customer/ user needs and are easy to use.
Software has been developed since the 1960s but the success rate of software development projects... more Software has been developed since the 1960s but the success rate of software development projects is still low. During the development of software, the probability of success is affected by various practices or aspects. To date, it is not clear which of these aspects are more important in influencing project outcome.In this research, we identify aspects which could influence project success, build prediction models based on the aspects using data collected from multiple companies, and then test their performance on data from a single organization.A survey-based empirical investigation was used to examine variables and factors that contribute to project outcome. Variables that were highly correlated to project success were selected and the set of variables was reduced to three factors by using principal components analysis. A logistic regression model was built for both the set of variables and the set of factors, using heterogeneous data collected from two different countries and a variety of organizations. We tested these models by using a homogeneous hold-out dataset from one organization. We used the receiver operating characteristic (ROC) analysis to compare the performance of the variable and factor-based models when applied to the homogeneous dataset.We found that using raw variables or factors in the logistic regression models did not make any significant difference in predictive capability. The prediction accuracy of these models is more balanced when the cut-off is set to the ratio of success to failures in the datasets used to build the models. We found that the raw variable and factor-based models predict significantly better than random chance.We conclude that an organization wishing to estimate whether a project will succeed or fail may use a model created from heterogeneous data derived from multiple organizations.
Initiated in 1992, the international PILPS project aims to evaluate and intercompare land-surface... more Initiated in 1992, the international PILPS project aims to evaluate and intercompare land-surface parameterization packages, destined for embedding into atmospheric general circulation models. The Project for Intercomparison of Landsurface Parameterization Schemes (PILPS) involves 27 numerical submodels to describe the interaction of the land surface with the overlying atmosphere. This project offers the opportunity of not only comparing the physical basis and simulation results of these land-surface codes, but also for collecting software engineering metrics on the codes themselves. The existing PILPS infrastructure supported the data collection of measures of the pieces of FORTRAN code in an organized fashion. A number of questions were included in a data gathering exercise, via questionnaire, regarding the structural complexity of the codes. Even for this parsimonious set of metrics, adequate data were returned for only 7 of the 27 land-surface parameterization schemes involved in the PILPS intercomparison. Results from these seven data sets are analyzed here in terms of control flow complexity and size. A second experiment is also described briefly. This was conducted to evaluate, subjectively, the overall “complexity” of four of the PILPS codes. Eight senior climate researchers, all of whom are also established FORTRAN programmers, were asked to evaluate the code listings using a questionnaire. These data were evaluated and their relationship to the objective measures assessed. A surprisingly good correlation was found between many of the standard, objective metrics and subjective assessments of overall “complexity.”
... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perce... more ... Comm. of The ACM 26, 10, (Oct. 1983) 785–793. 9. Jiang, JJ, Klein, G., and Discenza, R. Perception differences of software success: Provider and user views of system metrics. ... June M.Verner is a Visiting Professor at The University of New South Wales. back to top Footnotes. ...
Proceedings of the Ifip Wg8 2 Working Group on Information Systems Development Human Social and Organizational Aspects Human Organizational and Social Dimensions of Information Systems Development, May 17, 1993
Uploads