Abstract: Described herein is a computer implemented method for managing a repository that includes one or more component packages and a repository configuration file listing repository dependencies. Each component package has a package configuration file listing package dependencies. The method including the steps of: parsing the repository configuration file; aliasing a package dependency listed in the repository configuration file with at least two repository dependency aliases; parsing a package configuration file; and linking each repository dependency alias to a package dependency listed in the package configuration file.

Abstract: Described herein is a computer implemented method for managing a repository that includes one or more component packages and a repository configuration file listing repository dependencies. Each component package has a package configuration file listing package dependencies. The method including the steps of: parsing the repository configuration file; aliasing a package dependency listed in the repository configuration file with at least two repository dependency aliases; parsing a package configuration file; and linking each repository dependency alias to a package dependency listed in the package configuration file.

Abstract: Disclosed herein is a computer implemented scheduling method. The method comprises processing project data to determine one or more team-specific scheduling solutions for work items, each team specific scheduling solution for the work item defining a particular team and one or more iterations of that particular team in which the work item can be completed; identifying from the one or more team-specific scheduling solutions an optimal scheduling solution for the work item, the optimal scheduling solution being selected based at least in part on the number of iterations defined by each of the one or more team-specific scheduling solutions; and scheduling the work item according to the optimal scheduling solution identified for the work item.

Abstract: Disclosed herein is a computer implemented scheduling method comprising: accessing project data from computer readable storage media. The project data comprises work item data defining a plurality of work items to be scheduled, and release data defining one or more releases into which one or more of the plurality of work items are to be scheduled. The method comprises processing, using a computer processor, the project data to schedule strictly assigned work items by identifying strictly assigned work items, a strictly assigned work item having a particular release into which the strictly assigned work item needs to be scheduled; and for each strictly assigned work item identified, scheduling the strictly assigned work item into the release specified for that strictly assigned work item.

Abstract: Disclosed herein is a computer implemented scheduling method comprising: accessing project data from computer readable storage media. The project data comprises work item data defining a plurality of work items to be scheduled, and release data defining one or more releases into which one or more of the plurality of work items are to be scheduled. The method comprises processing, using a computer processor, the project data to schedule strictly assigned work items by identifying strictly assigned work items, a strictly assigned work item having a particular release into which the strictly assigned work item needs to be scheduled; and for each strictly assigned work item identified, scheduling the strictly assigned work item into the release specified for that strictly assigned work item.

Abstract: Disclosed herein is a computer implemented scheduling method. The method comprises processing project data to determine one or more team-specific scheduling solutions for work items, each team specific scheduling solution for the work item defining a particular team and one or more iterations of that particular team in which the work item can be completed; identifying from the one or more team-specific scheduling solutions an optimal scheduling solution for the work item, the optimal scheduling solution being selected based at least in part on the number of iterations defined by each of the one or more team-specific scheduling solutions; and scheduling the work item according to the optimal scheduling solution identified for the work item.

Abstract: Described herein is a computer implemented method comprising processing, using a computer processor, project data to generate a set of solution candidates for an activity of a work item, selecting a solution candidate from the set of solution candidates, and processing the project data to attempt to identify an assignment of the activity to the selected solution candidate. A solution candidate comprises a subset of resources from a team of resources. Generating the a solution candidate comprises selecting a number of resources for inclusion in the subset of resources, and selecting a given resource for inclusion in a solution candidate subset comprises selecting a sampling method and using the selected sampling method to select a resource from the team of resources.

Abstract: A method of visualizing sets of correlated events of a stream of events on a display, each event having a time of occurrence in the stream and at least one attribute indicating its correlation with the other events of a set, including the steps of plotting a glyph for each event on the display at a radial distance and an angular position with respect to an origin; the radial distance and the size of a glyph being proportional to the occurrence time of its event; the angular position of the glyph of a succeeding event in a set being chosen equal to that of the preceding event in the set unless these two glyphs would over-lap in which case the angular position of the glyph of said subsequent event is shifted in a given direction by an amount just sufficient to avoid such overlap; and the angular position of the glyph of the first event in a set being chosen so that overlapping of all glyphs is minimized.

Abstract: A method of detecting a reference sequence of events in a sample sequence of events, wherein each event is of a certain event type and holds a set of data attributes, includes the steps of: picking candidate combinations of events from said sample sequence so that the event types within each candidate combination match the event types in the reference sequence, calculating an overall similarity score for each candidate combination from at least (i) an event occurrence score based on occurrence deviations representing a count of non-matching events between the events of a candidate combination matching events of the reference sequence and (ii) an attribute match score based on similarity deviations between the data attributes of the events of a candidate combination and the data attributes of the matching events of the reference sequence, and identifying the candidate combination with the best overall similarity score as reference sequence detected.

Abstract: A method of detecting a reference sequence of events in a sample sequence of events, wherein each event is of a certain event type and holds a set of data attributes, includes the steps of: picking candidate combinations of events from said sample sequence so that the event types within each candidate combination match the event types in the reference sequence, calculating an overall similarity score for each candidate combination from at least (i) an event occurrence score based on occurrence deviations representing a count of non-matching events between the events of a candidate combination matching events of the reference sequence and (ii) an attribute match score based on similarity deviations between the data attributes of the events of a candidate combination and the data attributes of the matching events of the reference sequence, and identifying the candidate combination with the best overall similarity score as reference sequence detected.

Abstract: A method of detecting a reference sequence of events in a sample sequence of events, wherein each event is of a certain event type and holds a set of data attributes, includes the steps of: picking candidate combinations of events from said sample sequence so that the event types within each candidate combination match the event types in the reference sequence, calculating an overall similarity score for each candidate combination from at least (i) an event occurrence score based on occurrence deviations of the events of a candidate combination with respect to the matching events of the reference sequence and (ii) an attribute match score based on similarity deviations between the data attributes of the events of a candidate combination and the data attributes of the matching events of the reference sequence, and identifying the candidate combination with the best overall similarity score as reference sequence detected.

Abstract: A method of detecting a reference sequence of events in a sample sequence of events, wherein each event is of a certain event type and holds a set of data attributes, includes the steps of: picking candidate combinations of events from said sample sequence so that the event types within each candidate combination match the event types in the reference sequence, calculating an overall similarity score for each candidate combination from at least (i) an event occurrence score based on occurrence deviations of the events of a candidate combination with respect to the matching events of the reference sequence and (ii) an attribute match score based on similarity deviations between the data attributes of the events of a candidate combination and the data attributes of the matching events of the reference sequence, and identifying the candidate combination with the best overall similarity score as reference sequence detected.

Abstract: A method of visualizing sets of correlated events of a stream of events on a display, each event having a time of occurrence in the stream and at least one attribute indicating its correlation with the other events of a set, including the steps of plotting a glyph for each event on the display at a radial distance and an angular position with respect to an origin; the radial distance and the size of a glyph being proportional to the occurrence time of its event; the angular position of the glyph of a succeeding event in a set being chosen equal to that of the preceding event in the set unless these two glyphs would over-lap in which case the angular position of the glyph of said subsequent event is shifted in a given direction by an amount just sufficient to avoid such overlap; and the angular position of the glyph of the first event in a set being chosen so that overlapping of all glyphs is minimized.