Effective team coordination is crucial for successful global software projects. Although consider... more Effective team coordination is crucial for successful global software projects. Although considerable research effort has been made in this area, no agreement has been reached on the influence of dispersion on team coordination and performance. The objective of this paper is to summarize the evidence on the relationship among context dispersion, team coordination and performance in global software projects. We have performed a Systematic literature review (SLR) to collect relevant studies and a thematic analysis to synthesize the extracted data. We found 28 primary studies reporting the impact of five dispersion dimensions on team performance. Previously, only two primary studies considered and distinguished all of these dispersion dimensions in studying dispersed team performance. The dispersion dimensions affect team outcomes indirectly through influencing organic and mechanistic coordination processes. Empirical evidence show that geographical dispersion impacts negatively and temporal dispersion has a mixed effect on team performance. While studies with teams working across different time zones shows a tendency that the team performance is pessimistically perceived, studies that use direct measure on task performance shows a positive association to temporal dispersion. The paper provides implications for future research and practitioners in establishing effective distributed team coordination.
Early prediction of software quality is important for better software planning and controlling. I... more Early prediction of software quality is important for better software planning and controlling. In early development phases, design complexity metrics are considered as useful indicators of software testing effort and some quality attributes. Although many studies investigate the relationship between design complexity and cost and quality, it is unclear what we have learned from these studies, because no systematic synthesis exists to date. This paper presented a systematic review on the influence of software complexity metrics on quality attributes. We aggregated Spearman correlation coefficients from 59 different data sets from 57 primary studies by a tailored meta-analysis approach. We found that fault proneness and maintainability are most frequently investigated attributes. Chidamber& Kemerer metric suite is most frequently used but not all of them are good quality attribute indicators. Moreover, the impact of these metrics is not different in closed source and open source projects. The result provides some implications for building quality model across project type.
Software developers often spend a significant portion of their resources resolving submitted evol... more Software developers often spend a significant portion of their resources resolving submitted evolution issue reports. Classification or prediction of issue lead time is useful for prioritizing evolution issues and supporting human resources allocation in software maintenance. However, the predictability of issue lead time is still a research gap that calls for more empirical investigation.In this paper, we empirically assess different types of issue lead time prediction models using human factor measures collected from issue tracking systems. We conduct an empirical investigation of three active open source projects. A machine learning based classification and statistical univariate and multivariate analyses are performed. The accuracy of classification models in ten-fold cross-validation varies from 75.56% to 91%. The R2 value of linear multivariate regression models ranges from 0.29 to 0.60. Correlation analysis confirms the effectiveness of collaboration measures, such as the number of stakeholders and number of comments, in prediction models. The measures of assignee past performance are also an effective indicator of issue lead time. The results indicate that the number of stakeholders and average past issue lead time are important variables in constructing prediction models of issue lead time. However, more variables should be explored to achieve better prediction performance.
Initialized by a collective contribution of volunteer developers,
Open source software (OSS) attr... more Initialized by a collective contribution of volunteer developers, Open source software (OSS) attracts an increasing involvement of commercial firms. Many OSS projects are composed of a mix group of firm-paid and volunteer developers, with different motivations, collaboration practices and working styles. As OSS development consists of collaborative works in nature, it is important to know whether these differences have an impact on collaboration between difference types of stakeholders, which lead to an influence in the project outcomes. In this paper, we empirically investigate the firm-paid participation in resolving OSS evolution issues, the stakeholder collaboration and its impact on OSS issue resolution time. The results suggest that though a firm-paid assigned developer resolves much more issues than a volunteer developer does, there is no difference in issue resolution time between them. Besides, the more important factor that influences the issue resolution time comes from the collaboration among stakeholders rather than from individual characteristics.
Effective team coordination is crucial for successful global software projects. Although consider... more Effective team coordination is crucial for successful global software projects. Although considerable research effort has been made in this area, no agreement has been reached on the influence of dispersion on team coordination and performance. The objective of this paper is to summarize the evidence on the relationship among context dispersion, team coordination and performance in global software projects. We have performed a Systematic literature review (SLR) to collect relevant studies and a thematic analysis to synthesize the extracted data. We found 28 primary studies reporting the impact of five dispersion dimensions on team performance. Previously, only two primary studies considered and distinguished all of these dispersion dimensions in studying dispersed team performance. The dispersion dimensions affect team outcomes indirectly through influencing organic and mechanistic coordination processes. Empirical evidence show that geographical dispersion impacts negatively and temporal dispersion has a mixed effect on team performance. While studies with teams working across different time zones shows a tendency that the team performance is pessimistically perceived, studies that use direct measure on task performance shows a positive association to temporal dispersion. The paper provides implications for future research and practitioners in establishing effective distributed team coordination.
Early prediction of software quality is important for better software planning and controlling. I... more Early prediction of software quality is important for better software planning and controlling. In early development phases, design complexity metrics are considered as useful indicators of software testing effort and some quality attributes. Although many studies investigate the relationship between design complexity and cost and quality, it is unclear what we have learned from these studies, because no systematic synthesis exists to date. This paper presented a systematic review on the influence of software complexity metrics on quality attributes. We aggregated Spearman correlation coefficients from 59 different data sets from 57 primary studies by a tailored meta-analysis approach. We found that fault proneness and maintainability are most frequently investigated attributes. Chidamber& Kemerer metric suite is most frequently used but not all of them are good quality attribute indicators. Moreover, the impact of these metrics is not different in closed source and open source projects. The result provides some implications for building quality model across project type.
Software developers often spend a significant portion of their resources resolving submitted evol... more Software developers often spend a significant portion of their resources resolving submitted evolution issue reports. Classification or prediction of issue lead time is useful for prioritizing evolution issues and supporting human resources allocation in software maintenance. However, the predictability of issue lead time is still a research gap that calls for more empirical investigation.In this paper, we empirically assess different types of issue lead time prediction models using human factor measures collected from issue tracking systems. We conduct an empirical investigation of three active open source projects. A machine learning based classification and statistical univariate and multivariate analyses are performed. The accuracy of classification models in ten-fold cross-validation varies from 75.56% to 91%. The R2 value of linear multivariate regression models ranges from 0.29 to 0.60. Correlation analysis confirms the effectiveness of collaboration measures, such as the number of stakeholders and number of comments, in prediction models. The measures of assignee past performance are also an effective indicator of issue lead time. The results indicate that the number of stakeholders and average past issue lead time are important variables in constructing prediction models of issue lead time. However, more variables should be explored to achieve better prediction performance.
Initialized by a collective contribution of volunteer developers,
Open source software (OSS) attr... more Initialized by a collective contribution of volunteer developers, Open source software (OSS) attracts an increasing involvement of commercial firms. Many OSS projects are composed of a mix group of firm-paid and volunteer developers, with different motivations, collaboration practices and working styles. As OSS development consists of collaborative works in nature, it is important to know whether these differences have an impact on collaboration between difference types of stakeholders, which lead to an influence in the project outcomes. In this paper, we empirically investigate the firm-paid participation in resolving OSS evolution issues, the stakeholder collaboration and its impact on OSS issue resolution time. The results suggest that though a firm-paid assigned developer resolves much more issues than a volunteer developer does, there is no difference in issue resolution time between them. Besides, the more important factor that influences the issue resolution time comes from the collaboration among stakeholders rather than from individual characteristics.
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Papers by Anh Nguyen
complexity metrics on quality attributes. We aggregated Spearman correlation coefficients from 59 different data sets from 57 primary studies by a tailored meta-analysis approach. We found that fault
proneness and maintainability are most frequently investigated attributes. Chidamber& Kemerer metric suite is most frequently used but not all of them are good quality attribute indicators. Moreover, the impact of these metrics is not different in closed source and open source projects. The result provides some
implications for building quality model across project type.
investigation.In this paper, we empirically assess different types of issue lead time prediction models using human factor measures collected from issue tracking systems. We conduct an empirical investigation of three active open source projects. A machine learning based classification and statistical univariate and multivariate analyses are performed. The accuracy of classification models in ten-fold cross-validation varies from 75.56% to 91%. The R2 value of linear multivariate regression models ranges from 0.29 to 0.60. Correlation analysis confirms the effectiveness of collaboration measures, such as the number of stakeholders and number of comments, in prediction models. The measures of assignee past performance are also an effective indicator of issue lead time. The results indicate that the number of stakeholders and average past issue lead time are important variables in constructing prediction models of issue lead time. However, more variables should be explored to achieve better prediction performance.
Open source software (OSS) attracts an increasing involvement of commercial firms. Many OSS projects are composed of a mix group of firm-paid and volunteer developers, with different motivations, collaboration practices and working styles. As OSS development consists of collaborative works in nature, it is important to know whether these differences have an impact on
collaboration between difference types of stakeholders, which lead to an influence in the project outcomes. In this paper, we empirically investigate the firm-paid participation in resolving OSS evolution issues, the stakeholder collaboration and its impact on OSS issue resolution time. The results suggest that though a firm-paid assigned developer resolves much more issues than a
volunteer developer does, there is no difference in issue resolution time between them. Besides, the more important factor that influences the issue resolution time comes from the collaboration among stakeholders rather than from individual characteristics.
complexity metrics on quality attributes. We aggregated Spearman correlation coefficients from 59 different data sets from 57 primary studies by a tailored meta-analysis approach. We found that fault
proneness and maintainability are most frequently investigated attributes. Chidamber& Kemerer metric suite is most frequently used but not all of them are good quality attribute indicators. Moreover, the impact of these metrics is not different in closed source and open source projects. The result provides some
implications for building quality model across project type.
investigation.In this paper, we empirically assess different types of issue lead time prediction models using human factor measures collected from issue tracking systems. We conduct an empirical investigation of three active open source projects. A machine learning based classification and statistical univariate and multivariate analyses are performed. The accuracy of classification models in ten-fold cross-validation varies from 75.56% to 91%. The R2 value of linear multivariate regression models ranges from 0.29 to 0.60. Correlation analysis confirms the effectiveness of collaboration measures, such as the number of stakeholders and number of comments, in prediction models. The measures of assignee past performance are also an effective indicator of issue lead time. The results indicate that the number of stakeholders and average past issue lead time are important variables in constructing prediction models of issue lead time. However, more variables should be explored to achieve better prediction performance.
Open source software (OSS) attracts an increasing involvement of commercial firms. Many OSS projects are composed of a mix group of firm-paid and volunteer developers, with different motivations, collaboration practices and working styles. As OSS development consists of collaborative works in nature, it is important to know whether these differences have an impact on
collaboration between difference types of stakeholders, which lead to an influence in the project outcomes. In this paper, we empirically investigate the firm-paid participation in resolving OSS evolution issues, the stakeholder collaboration and its impact on OSS issue resolution time. The results suggest that though a firm-paid assigned developer resolves much more issues than a
volunteer developer does, there is no difference in issue resolution time between them. Besides, the more important factor that influences the issue resolution time comes from the collaboration among stakeholders rather than from individual characteristics.