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The system is distributed and embedded in the web and is based on structured retrieval using a classification schema.
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Nonetheless, weighing constructs proved to be a promising way of increasing the effectiveness of bug localization techniques based on structured information retrieval.
It was previously demonstrated that bug localization based on structured information retrieval benefits from the usage of more program constructs (RQ2, Section 3.7).
Thus, contrary to our initial assumption, it is not needed to remove low-contributing constructs from bug localization models based on structured information retrieval.
One possible way of increasing effectiveness of bug localization based on structured information retrieval is to assign different weights to the parts in which source files are split (Saha et al. 2013).
Initially, we questioned whether current state-of-the-art bug localization techniques based on structured information retrieval, i.e., BLUiR, BLUiR+, and AmaLgam, would effectively locate bugs in C# projects.
Bug localization techniques based on structured information retrieval, such as BLUiR (Saha et al. 2013) and AmaLgam (Wang and Lo 2014), have shown considerable improvements over other traditional IR approaches (Section 2.2).
This piece is based on structure, not note by note.
The study is based on retrieval of structured data from electronic patient records.
The main weakness of the study is that it is retrospective and based on retrieval of structured data from the EPR.
Assessment of retrieval effectiveness using string matching methods and methods based on structural characteristics of data.
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