ABSTRACT
Automatic text summarisation has drawn considerable interest in the field of software engineering. It can improve the efficiency of software developers, enhance the quality of products, and ensure timely delivery. In this paper, we present our initial work towards automatically generating human-like multi-document summaries from heterogeneous software artefacts. Our analysis of the text properties of 545 human-written summaries from 15 software engineering projects will ultimately guide heuristics searches in the automatic generation of human-like summaries.
- M. Allahyari, S. A. Pouriyeh, M. Assefi, S. Safaei, E. D. Trippe, J. B. Gutierrez, and K. Kochut. 2017. Text Summarization Techniques: A Brief Survey. CoRR abs/1707.02268 (2017).Google Scholar
- S. Chand and M. Wagner. 2015. Evolutionary many-objective optimization: A quick-start guide. Surveys in Operations Research and Management Science 20, 2 (2015), 35--42.Google ScholarCross Ref
- L. Dabbish, C. Stuart, J. Tsay, and J. Herbsleb. 2012. Social Coding in GitHub: Transparency and Collaboration in an Open Software Repository. In Proc. of the Conf. on Computer Supported Cooperative Work. 1277--1286. Google ScholarDigital Library
- U. Hahn and I. Mani. 2000. The Challenges of Automatic Summarization. Computer 33, 11 (2000), 29--36. Google ScholarDigital Library
- M. Harman andB. F.Jones. 2001. Search-based software engineering. Information and Software Technology 43, 14 (2001), 833--839.Google ScholarCross Ref
- H. P. Luhn. 1958. The Automatic Creation of Literature Abstracts. IBM Journal of Research and Development 2, 2 (1958), 159--165. Google ScholarDigital Library
- L. v. d. Maaten and G. Hinton. 2008. Visualizing data using t-SNE. Journal of Machine Learning Research 9 (2008), 2579--2605.Google ScholarDigital Library
- L. Moreno, J. Aponte, G. Sridhara, A. Marcus, L. Pollock, and K. Vijay-Shanker. 2013. Automatic generation of natural language summaries for Java classes. In Proc. of thelnt'l. Conf. on Program Comprehension. 23--32.Google Scholar
- S. Rastkar, G. C. Murphy, and G. Murray. 2014. Automatic Summarization of Bug Reports. IEEE Trans, on Softw. Engg. 40, 4 (2014), 366--380. Google ScholarDigital Library
- P. C. Rigby and M. P. Robillard. 2013. Discovering Essential Code Elements in Informal Documentation. In Proc. of the Int'l. Conf. on Softw. Engg. 832--841. Google ScholarDigital Library
- G. Sridhara, E. Hill, D. Muppaneni, L. Pollock, and K. Vijay-Shanker. 2010. Towards Automatically Generating Summary Comments for Java Methods. In Proc. of the Int'l. Conf. on Automated Softw. Engg. 43--52. Google ScholarDigital Library
- C. Treude, F. Figueira Filho, and U. Kulesza. 2015. Summarizing and Measuring Development Activity. In Proc. of the Meeting on Found, of Softw. Engg. 625--636. Google ScholarDigital Library
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Toward human-like summaries generated from heterogeneous software artefacts
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Parallel Problem Solving from Nature – PPSN XVIAbstractAutomatic text summarisation has drawn considerable interest in the area of software engineering. It is challenging to summarise the activities related to a software project, (1) because of the volume and heterogeneity of involved software ...
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