Automated Bug Report Ranking for Modeling Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Identifying and addressing software bugs in complex computer programs is time-consuming and costly, prolonging development times due to the inefficiencies in existing bug detection and reporting systems.
Innovation Solution
A system that generates a check report of relevant bug reports for graphical models using a bug reports system, which ranks bug reports based on criticality scores computed from stored information, statistics, and rules, facilitating quicker identification and prioritization of critical issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If developers manually check for bugs in existing computer programs used as building blocks, then bug detection thoroughness is improved, but development time and costs increase
Solution Approach 1:
The system enables self-service bug detection by automatically generating check reports that query a bug reports database using model information as parameters. The bug detection process serves itself through automated database queries and report generation, eliminating the need for manual bug checking while maintaining thoroughness through systematic coverage of all model elements.
Solution Approach 2:
The system performs preliminary bug detection by generating check reports before the actual model deployment or further development work. Bug reports are retrieved and analyzed in advance, allowing developers to identify and address potential issues before they impact the development timeline, thus reducing overall development time while maintaining detection quality.
2Measurement precision
If developers manually check for bugs in existing computer programs, then bug identification accuracy is improved, but development costs increase
Solution Approach 1:
The automated check report generation system performs bug identification without human intervention, retrieving relevant bug reports from the database and presenting them systematically. This self-service approach maintains high identification accuracy through comprehensive database queries while dramatically improving development efficiency by eliminating manual checking processes.
Solution Approach 2:
The system replaces the mechanical manual process of bug checking with an automated information processing system. Database queries, report generation, and bug identification are performed automatically through software mechanisms rather than human manual inspection, maintaining accuracy through systematic coverage while improving productivity through automation.
3Reliability
If a comprehensive bug checking process is implemented, then bug detection quality is improved, but system complexity increases
Solution Approach 1:
The bug detection system is segmented into distinct functional components: a bug reports database storing organized bug information, a query mechanism that accepts model information as parameters, and a report generation module. This segmentation allows comprehensive bug detection through systematic querying while managing complexity by dividing the system into manageable, independent modules with clear interfaces.
Solution Approach 2:
The check report generation system serves multiple functions: it queries the bug database, processes model information, generates comprehensive bug reports, and presents findings to developers. This multi-functionality achieves high bug detection quality through a single integrated system rather than multiple separate tools, actually reducing overall system complexity while maintaining comprehensive detection capabilities.
Data Source
AI summary
A method may include storing bug reports in a memory, where a particular one of the bug reports describes a software bug and includes information about a modeling application. The method may further include receiving, from another computer device, a request for bug reports relevant to a model generated using the modeling application, where the request includes information about the model; identifying one or more relevant bug reports, in the stored bug reports, by comparing the information about the modeling application, included in the stored bug reports, with the information about the model, included in the received request; and providing information about the one or more relevant bug reports to the other computer device.