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Recovering documentation-to-source-code traceability links using latent semantic indexing
TLDR
The method presented proves to give good results by comparison and additionally it is a low cost, highly flexible method to apply with regards to preprocessing and/or parsing of the source code and documentation.
An information retrieval approach to concept location in source code
TLDR
This work addresses the problem of concept location using an advanced information retrieval method, Latent Semantic Indexing (LSI), used to map concepts expressed in natural language by the programmer to the relevant parts of the source code.
Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval
TLDR
The results show that the combination of experts significantly improves the effectiveness of feature location as compared to each of the experts used independently.
Automated severity assessment of software defect reports
TLDR
The paper presents a new and automated method named SEVERIS (severity issue assessment), which assists the test engineer in assigning severity levels to defect reports, based on standard text mining and machine learning techniques applied to existing sets of defect reports.
On the Use of Automated Text Summarization Techniques for Summarizing Source Code
TLDR
The paper presents a solution which mitigates the two approaches, i.e., short and accurate textual descriptions that illustrate the software entities without having to read the details of the implementation.
The conceptual cohesion of classes
TLDR
A new set of measures for the cohesion of individual classes within an OO software system is proposed, based on the analysis of the semantic information embedded in the source code, such as comments and identifiers.
Feature location via information retrieval based filtering of a single scenario execution trace
TLDR
A semi-automated technique for feature location in source code based on combining information from two different sources, comparable with previously published approaches and easy to use as it considerably simplifies the dynamic analysis is presented.
Better cross company defect prediction
TLDR
This paper finds that: 1) within-company predictors are weak for small data-sets; 2) the Peters filter+cross-company builds better predictors than both within- company and the Burak filter+Cross-company; and 3) the PETS filter builds 64% more useful predictor than bothWithin-company and theBurak filter-cross- company approaches.
Using information retrieval based coupling measures for impact analysis
TLDR
A new set of coupling measures for Object-Oriented (OO) software systems measuring conceptual coupling of classes is presented, which capture new dimensions of coupling, which are not captured by the existing coupling measures.
Automatic generation of natural language summaries for Java classes
TLDR
This paper presents a technique to automatically generate human readable summaries for Java classes, assuming no documentation exists, and determines that they are readable and understandable, they do not include extraneous information, and, in most cases, they are not missing essential information.
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