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Estimation of Characteristics of a Software Team for Implementing Effective Inspection Process through Inspection Performance Metric
Software Engineering · Submitted 16 Jul 2011
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim The IPM values observed onsite and IPM values produced by our model which are strongly matching, support the predictive capability of IPM through team coefficients.
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The abstract, sentence by sentence
The continued existence of any software industry depends on its capability to develop nearly zero-defect product, which is achievable through effective defect management. Inspection has proven to be one of the promising techniques of defect management. Introductions of metrics like, Depth of Inspection (DI, a process metric) and Inspection Performance Metric (IPM, a people metric) enable one to have an appropriate measurement of inspection technique. This article elucidates a mathematical approach to estimate the IPM value without depending on shop floor defect count at every time. By applying multiple linear regression models, a set of characteristic coefficients of the team is evaluated. These coefficients are calculated from the empirical projects that are sampled from the teams of product-based and service-based IT industries. A sample of three verification projects indicates a close match between the IPM values obtained from the defect count (IPMdc) and IPM values obtained using the team coefficients using the mathematical model (IPMtc). The IPM values observed onsite and IPM values produced by our model which are strongly matching, support the predictive capability of IPM through team coefficients. Having finalized the value of IPM that a company should achieve for a project, it can tune the inspection influencing parameters to realize the desired quality level of IPM. Evaluation of team coefficients resolves several defect-associated issues, which are related to the management, stakeholders, outsourcing agents and customers. In addition, the coefficient vector will further aid the strategy of PSP and TSP
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | The continued existence of any software industry depends on its capability to develop nearly zero-defect product, which is achievable through effective defect management. | background 1.00 | 0.05 | 0.03 | asserted 0.99 |
| s1 | Inspection has proven to be one of the promising techniques of defect management. | background 1.00 | 0.06 | 0.02 | asserted 0.99 |
| s2 | Introductions of metrics like, Depth of Inspection (DI, a process metric) and Inspection Performance Metric (IPM, a people metric) enable one to have an appropriate measurement of inspection technique. | background 0.99 | 0.12 | 0.04 | asserted 0.84 |
| s3 | This article elucidates a mathematical approach to estimate the IPM value without depending on shop floor defect count at every time. | contribution 0.98 | 0.87 | 0.13 | asserted 0.99 |
| s4 | By applying multiple linear regression models, a set of characteristic coefficients of the team is evaluated. | method 0.99 | 0.89 | 0.07 | asserted 1.00 |
| s5 | These coefficients are calculated from the empirical projects that are sampled from the teams of product-based and service-based IT industries. | method 0.99 | 0.88 | 0.04 | asserted 0.99 |
| s6 | A sample of three verification projects indicates a close match between the IPM values obtained from the defect count (IPMdc) and IPM values obtained using the team coefficients using the mathematical model (IPMtc). | result 1.00 | 0.93 | 0.26 | hedged possibility 0.86 |
| s7 | The IPM values observed onsite and IPM values produced by our model which are strongly matching, support the predictive capability of IPM through team coefficients. | interpretation 0.86 | 0.92 | 0.42 | asserted 0.97 |
| s8 | Having finalized the value of IPM that a company should achieve for a project, it can tune the inspection influencing parameters to realize the desired quality level of IPM. | interpretation 0.73 | 0.30 | 0.19 | asserted 0.76 |
| s9 | Evaluation of team coefficients resolves several defect-associated issues, which are related to the management, stakeholders, outsourcing agents and customers. | interpretation 0.92 | 0.55 | 0.14 | asserted 0.99 |
| s10 | In addition, the coefficient vector will further aid the strategy of PSP and TSP | interpretation 0.52 | 0.28 | 0.08 | asserted 0.56 |
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The paper
Original abstract
The continued existence of any software industry depends on its capability to develop nearly zero-defect product, which is achievable through effective defect management. Inspection has proven to be one of the promising techniques of defect management. Introductions of metrics like, Depth of Inspection (DI, a process metric) and Inspection Performance Metric (IPM, a people metric) enable one to have an appropriate measurement of inspection technique. This article elucidates a mathematical approach to estimate the IPM value without depending on shop floor defect count at every time. By applying multiple linear regression models, a set of characteristic coefficients of the team is evaluated. These coefficients are calculated from the empirical projects that are sampled from the teams of product-based and service-based IT industries. A sample of three verification projects indicates a close match between the IPM values obtained from the defect count (IPMdc) and IPM values obtained using the team coefficients using the mathematical model (IPMtc). The IPM values observed onsite and IPM values produced by our model which are strongly matching, support the predictive capability of IPM through team coefficients. Having finalized the value of IPM that a company should achieve for a project, it can tune the inspection influencing parameters to realize the desired quality level of IPM. Evaluation of team coefficients resolves several defect-associated issues, which are related to the management, stakeholders, outsourcing agents and customers. In addition, the coefficient vector will further aid the strategy of PSP and TSP
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