Duplicate Bug Report Detection Using Word Matrix Expansion
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Solution Overview
Problem
Current duplicate bug report detection systems are unable to identify dissimilar duplicate reports, as they rely on Natural Language Processing and Information Retrieval techniques that only detect duplicates with similar text, failing to recognize reports with different vocabularies that share the same underlying cause.
Innovation Solution
A system and method that capture underlying root cause relations between bug reports using a word matrix, allowing for the expansion of search queries to identify both similar and dissimilar duplicate reports by extracting keywords and expanding search strings to include dissimilar duplicate words.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Natural Language Processing and Information Retrieval techniques are used to detect duplicate bug reports, then similar duplicate bug reports with similar text can be identified, but dissimilar duplicate bug reports with different vocabularies cannot be detected
Solution Approach 1:
The patent introduces a word matrix as an intermediary structure that maps relationships between dissimilar words. The word matrix serves as a mediator between the search string and bug reports, enabling the system to detect dissimilar duplicates by translating different vocabularies into comparable representations through the matrix.
Solution Approach 2:
The patent transforms the detection approach by changing the parameter representation from direct text matching to matrix-based vector representation. Bug reports and search strings are converted into vectors in a multi-dimensional space, allowing detection of semantic similarity even when surface-level vocabulary differs significantly.
2Measurement precision
If synonym replacement techniques are used to detect duplicate bug reports, then duplicates with different but synonymous words can be identified, but dissimilar duplicate bug reports with completely different vocabularies still cannot be detected
Solution Approach 1:
The patent moves the detection problem from one dimension (textual similarity) to another dimension (vector space relationships). By representing bug reports as vectors in a multi-dimensional space where semantic relationships are preserved, the system can detect duplicates across different vocabularies by measuring distances or angles in this higher-dimensional space.
3Productivity
If existing duplicate detection systems focus on text similarity, then processing speed is maintained, but the ability to detect dissimilar duplicates is lost
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing word co-occurrence statistics in the word matrix during an offline phase. This pre-processing creates a ready-to-use transformation framework that enables fast online detection without requiring complex real-time computations, thus maintaining processing speed while enhancing detection capability.
Data Source
AI summary
A system and method for detection of duplicate bug reports. A receiver is configured to receive a first bug report and a word matrix. An extractor extracts keywords from the first bug report for creating a first search string. A comparator compares each of the keywords from the first search string with the word matrix for identifying dissimilar duplicate words. The duplicate bug detector further includes an expander to expand the first search string by including the dissimilar duplicate words for creating the second search string and a searcher to search a bug repository with the first search string and the second search string for identifying similar duplicate bug reports and dissimilar duplicate bug reports.