Recovering Traceability Links between Code and Documentation

By G. Antoniol, Gerardo Canfora, G. Casazza, Andrea De Lucia, E. Merlo. 2002

1,092 citations recorded by the source corpus.

Subfields: Information Systems, Software, Signal Processing

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Citations in the corpus

Advancing candidate link generation for requirements tracing: the study of methods (2006, methodology): “Most research in the area of requirements tracing has focused on models of requirements tracing [40] or has looked at recall and precision to assess the accuracy of the applied linking algorithms [3], [31].”
On the naturalness of software (2012, background): “Another source of aligned examples are in-line comments that are clearly matchable with nearby code [33].”
Recovering traceability links in software artifact management systems using information retrieval methods (2007, methodology): “This is the reason why information retrieval based traceability recovery methods are semi-automatic methods and require the interaction of the software engineer [Antoniol et al. 2002; Huffman Hayes et al. 2003; Marcus and Maletic 2003].”
A Hidden Markov Model to detect coded information islands in free text (2013, methodology): “For example, recovering the traceability between source code and software documentation stored in email has been tackled with methods based on vector of terms [6], [7].”
Semantically Enhanced Software Traceability Using Deep Learning Techniques (2017, neutral): “To address these problems, researchers have proposed and developed solutions for automating the task of creating and maintaining trace links [1], [17], [34].”
A survey of traceability in requirements engineering and model-driven development (2010, background): “, in [13, 111]) or explicitly [105] extended to general traceability of all artifacts as the ability to define, describe, capture, and follow traces from and to artifacts throughout the whole software development process, which seems sensible because all artifacts of a software development are (or a”
Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems (2008, background): “Existing work on concept and feature location [60], [66], traceability link recovery between the source code and documentation [3], [58], impact analysis [2], and other such tasks showed that our premise stands and this type of information extracted from the source code is very useful.”
On the naturalness of software (2016, background): “Second, many in-line comments could be matched with nearby code.(2) Stack-overflow posts (both questions and answers) often include closely-related code and text.”
ReLink: recovering links between bugs and changes (2011, background): “Many researchers have proposed information retrieval (IR) based techniques to recover traceability links between source code and text documents (such as development journals, error logs, and emails) [2, 3, 4].”
Semantic clustering: Identifying topics in source code (2007, background): “Most approaches that have been developed focus on program structure [2] or on external documentation [3,4].”
Improving requirements tracing via information retrieval (2003, methodology): “Antionol et al [3] applied a probabilistic and a vector space IR model in two case studies to trace C++ source code onto manual pages and to trace Java code to functional requirements.”
Software traceability: trends and future directions (2014, methodology): “[3], who used a probabilistic approach to retrieve trace links between code and documentation.”
An information retrieval approach to concept location in source code (2004, methodology): “This approach is compared to that of Antoniol’s [2] supporting the conclusion that IR methods can be successfully applied to these types of problems.”