Abstract:
A method and system estimates future software support requirements based on statistical models of previous observations of support requests, either for the same product or for a different product having features previously identified as correlated with features of a new product. The estimates include an estimated volume of support requests and an estimated type of support requests. The estimated types include the activity occurring at the time of the failure, an identifier as to whether a defect in the software was previously known, and the like. The estimates are used to estimate and allocate support resources prior to support requests being received, and prior to a software product being released.
Abstract:
Systems and methods are provided to produce natural language interpretations of analytic operations in an automated manner, by associating with each analytic procedure a set of parameters that determine the interpretation of the resulting analysis.
Abstract:
A method and system estimates future software support requirements based on statistical models of previous observations of support requests, either for the same product or for a different product having features previously identified as correlated with features of a new product. The estimates include an estimated volume of support requests and an estimated type of support requests. The estimated types include the activity occurring at the time of the failure, an identifier as to whether a defect in the software was previously known, and the like. The estimates are used to estimate and allocate support resources prior to support requests being received, and prior to a software product being released.
Abstract:
A computer-implemented method of optimizing a design of a product in a mass manufacturing process includes steps of: collecting error data relating to a product; classifying the error data into categories of errors to provide classifier error data; analyzing relationships among the classified error data; producing an analysis report; and recommending modifications to an end user for the design of the product.
Abstract:
A method to create an instance of a defect-based production and testing process analysis machine (DPTPAM) provides continual process improvement based on foundational questions and classified defect data. The method includes the following steps: obtaining domain specific questions; developing a domain specific classification scheme that supports the answering of the foundational and domain specific questions; determining a method of using the domain specific classification scheme to answer both the foundational and domain specific questions; and creating a domain specific DPTPAM instance embodying the domain specific classification scheme and the method of answering the foundational and domain specific questions. The method can be implemented with a machine and a computer readable medium comprising logic for performing the method.
Abstract:
A computer-implemented method of optimizing at least one production or testing processes in a mass manufacturing industry, includes steps of: collecting error data relating to a product at a plurality of points along its production and distribution chain; classifying the error data into categories of errors to provide classified error data; analyzing relationships among the classified error data; and suggesting modifications to at least one of the production or testing processes based on the analysis.
Abstract:
A computer-implemented method of optimizing at least one of a design, production and testing process in a mass manufacturing process includes steps of: collecting error data relating to a product; classifying the error data into categories of symptoms; mapping the symptom to a revealing condition of the product; mapping the revealing condition to a test type; mapping a scope of a fix to phases of error injection mapping; and recommending modifications to an end user for at least one of the design, production, delivery, and testing process based on the scope of the fix.
Abstract:
A system, method and computer program product for requirements management. Particularly, a requirements management scheme performs at least the following functions: 1) it guides a team through the requirements process and provides a structure for collecting “requests”. By using the scheme, team members are prompted to think about and record relevant information that will help clarify and complete requests; and, 2) the scheme allows users to use the attributes throughout the development process to identify risk and make improvements to their process. Many of these attributes can be refined during the development phase or even later. Besides helping team members achieve continuous improvement in their requirements process by providing a set of data and metrics for collection and assessment, the scheme enables an organization to effectively manage their requirements as well as manage changes to those requirements.
Abstract:
A method and system estimates future software support requirements based on statistical models of previous observations of support requests, either for the same product or for a different product having features previously identified as correlated with features of a new product. The estimates include an estimated volume of support requests and an estimated type of support requests. The estimated types include the activity occurring at the time of the failure, an identifier as to whether a defect in the software was previously known, and the like. The estimates are used to estimate and allocate support resources prior to support requests being received, and prior to a software product being released.
Abstract:
A method to create an instance of a defect-based production and testing process analysis machine (DPTPAM) provides continual process improvement based on foundational questions and classified defect data. The method includes the following steps: obtaining domain specific questions; developing a domain specific classification scheme that supports the answering of the foundational and domain specific questions; determining a method of using the domain specific classification scheme to answer both the foundational and domain specific questions; and creating a domain specific DPTPAM instance embodying the domain specific classification scheme and the method of answering the foundational and domain specific questions. The method can be implemented with a machine and a computer readable medium comprising logic for performing the method.