Quality analysis of source code comments

Steidl, Daniela; Hummel, Benjamin; Juergens, Elmar

doi:10.1109/icpc.2013.6613836

Cited by 161 publications

(143 citation statements)

References 12 publications

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“…Our work can assist code summarization research by providing a guide to the sections of code that should be targetted for summarization. At the same time, our work may assist in creating metrics for source code comment quality [59] by providing evidence about which sections of the code the comments should reflect. Although this work contributes important evidence and advances the state-of-the-art in source code summarization, there are some limitations which we aim to address in future work.…”

Section: Discussionmentioning

confidence: 99%

Improving automated source code summarization via an eye-tracking study of programmers

Rodeghero

McMillan

McBurney

et al. 2014

Proceedings of the 36th International Conference on Software Engineering

165

106

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Source Code Summarization is an emerging technology for automatically generating brief descriptions of code. Current summarization techniques work by selecting a subset of the statements and keywords from the code, and then including information from those statements and keywords in the summary. The quality of the summary depends heavily on the process of selecting the subset: a high-quality selection would contain the same statements and keywords that a programmer would choose. Unfortunately, little evidence exists about the statements and keywords that programmers view as important when they summarize source code. In this paper, we present an eye-tracking study of 10 professional Java programmers in which the programmers read Java methods and wrote English summaries of those methods. We apply the findings to build a novel summarization tool. Then, we evaluate this tool and provide evidence to support the development of source code summarization systems.

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Section: Discussionmentioning

confidence: 99%

Improving automated source code summarization via an eye-tracking study of programmers

Rodeghero

McMillan

McBurney

et al. 2014

Proceedings of the 36th International Conference on Software Engineering

165

106

View full text Add to dashboard Cite

show abstract

“…Their subsequent work on the comment level detection includes [23], [24]. Similar work on comment quality analysis and use case documents analysis were presented in [25] and [26] respectively. Compared with all these work, we target at different research questions although some similar analysis techniques are used.…”

Section: Related Workmentioning

confidence: 99%

Analyzing APIs Documentation and Code to Detect Directive Defects

Zhou

Chen

et al. 2017

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)

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Abstract-Application Programming Interface (API) documents represent one of the most important references for API users. However, it is frequently reported that the documentation is inconsistent with the source code and deviates from the API itself. Such inconsistencies in the documents inevitably confuse the API users hampering considerably their API comprehension and the quality of software built from such APIs. In this paper, we propose an automated approach to detect defects of API documents by leveraging techniques from program comprehension and natural language processing. Particularly, we focus on the directives of the API documents which are related to parameter constraints and exception throwing declarations. A first-order logic based constraint solver is employed to detect such defects based on the obtained analysis results. We evaluate our approach on parts of well documented JDK 1.8 APIs. Experiment results show that, out of around 2000 API usage constraints, our approach can detect 1146 defective document directives, with a precision rate of 81.6%, and a recall rate of 82.0%, which demonstrates its practical feasibility.

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“…Content adequacy referred to whether there was missing information, while conciseness referred to limiting unnecessary information in the summary. This strategy for evaluating generated comments is supported by a recent study of source code comments [49] in which quality was modeled as a combination of factors correlating to accuracy, adequacy, and conciseness.…”

Section: Discussionmentioning

confidence: 86%

Automatic documentation generation via source code summarization of method context

McBurney

McMillan

2014

Proceedings of the 22nd International Conference on Program Comprehension

173

107

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A documentation generator is a programming tool that creates documentation for software by analyzing the statements and comments in the software's source code. While many of these tools are manual, in that they require speciallyformatted metadata written by programmers, new research has made inroads towards automatic generation of documentation. These approaches work by stitching together keywords from the source code into readable natural language sentences. These approaches have been shown to be effective, but carry a key limitation: the generated documents do not explain the source code's context. They can describe the behavior of a Java method, but not why the method exists or what role it plays in the software. In this paper, we propose a technique that includes this context by analyzing how the Java methods are invoked. In a user study, we found that programmers benefit from our generated documentation because it includes context information.

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Quality analysis of source code comments

Cited by 161 publications

References 12 publications

Improving automated source code summarization via an eye-tracking study of programmers

Improving automated source code summarization via an eye-tracking study of programmers

Analyzing APIs Documentation and Code to Detect Directive Defects

Automatic documentation generation via source code summarization of method context

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