summarizing software artifacts a literature review

Summarizing Software Artifacts: A Literature Review

• Najam Nazar , 
• Yan Hu , 

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Journal of Computer Science and Technology > 2016 > 31 > 5 > 883-909

This paper presents a literature review in the field of summarizing software artifacts, focusing on bug reports, source code, mailing lists and developer discussions artifacts. From Jan. 2010 to Apr. 2016, numerous summarization techniques, approaches, and tools have been proposed to satisfy the ongoing demand of improving software performance and quality and facilitating developers in understanding the problems at hand. Since aforementioned artifacts contain both structured and unstructured data at the same time, researchers have applied different machine learning and data mining techniques to generate summaries. Therefore, this paper first intends to provide a general perspective on the state of the art, describing the type of artifacts, approaches for summarization, as well as the common portions of experimental procedures shared among these artifacts. Moreover, we discuss the applications of summarization, i.e., what tasks at hand have been achieved through summarization. Next, this paper presents tools that are generated for summarization tasks or employed during summarization tasks. In addition, we present different summarization evaluation methods employed in selected studies as well as other important factors that are used for the evaluation of generated summaries such as adequacy and quality. Moreover, we briefly present modern communication channels and complementarities with commonalities among different software artifacts. Finally, some thoughts about the challenges applicable to the existing studies in general as well as future research directions are also discussed. The survey of existing studies will allow future researchers to have a wide and useful background knowledge on the main and important aspects of this research field.

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Najam Nazar

• Dalian University of Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian, China
• Wuhan University, State Key Laboratory of Software Engineering, Wuhan, China

mining software repositories mining software engineering data machine learning summarizing software artifacts summarizing source code

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Journal article

Summarizing Software Artifacts: A Literature Review

Najam Nazar, Yan Hu, He Jiang

JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY | SPRINGER SINGAPORE PTE LTD | Published : 2016

DOI: 10.1007/s11390-016-1671-1

This paper presents a literature review in the field of summarizing software artifacts, focusing on bug reports, source code, mailing lists and developer discussions artifacts. From Jan. 2010 to Apr. 2016, numerous summarization techniques, approaches, and tools have been proposed to satisfy the ongoing demand of improving software performance and quality and facilitating developers in understanding the problems at hand. Since aforementioned artifacts contain both structured and unstructured data at the same time, researchers have applied different machine learning and data mining techniques to generate summaries. Therefore, this paper first intends to provide a general perspective on the st..

University of Melbourne Researchers

Awarded by National Basic Research 973 Program of China

Awarded by Fundamental Research Funds for the Central Universities of China

Awarded by New Century Excellent Talents in University of China

Awarded by National Natural Science Foundation of China

Funding Acknowledgements

This work was supported in part by the National Basic Research 973 Program of China under Grant No. 2013CB035906, the Fundamental Research Funds for the Central Universities of China under Grant No. DUT13RC(3)53, and in part by the New Century Excellent Talents in University of China under Grant No. NCET-13-0073 and the National Natural Science Foundation of China under Grant No. 61300017.

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