Improving software documentation using textual entailment

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Improving software documentation using textual entailment

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ACM SIGSOFT Software Engineering Notes archive
Volume 31 , Issue 6 (November 2006) table of contents

SESSION: FSE Poster Session table of contents

Pages: 1 - 2

Year of Publication: 2006

ISSN:0163-5948

Authors

Yasser Kotb	Japan Advanced Institute of Science and Technology, Ishikawa, Japan
Takuya Katayama	Japan Advanced Institute of Science and Technology, Ishikawa, Japan

Publisher

ACM New York, NY, USA

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ABSTRACT

Formal online errors/bugs documentation of real-time software is a difficult and error prone task. Conceptual and tool support for this activity plays a central role in the agenda of building large complex software products, especially if this software targets market abroad that requires a continuous massive inflow of data customers' needs and a regarding product requirements. Unfortunately, the manual linkage that is routinely performed today is cumbersome, time-consuming, and error-prone. This paper presents a framework to explore the redundancy of error reports in online documentation. The framework employs a recent natural language processing technique called Textual Entailment.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	David J. Smith. Achieving Software Quality - Including its Application to Safety-related Systems. Third edition. Publiched by Chapman & Hall, London, UK, 1987.
	2	Dagan, I. Glickman, O. and Magnini, B. The PASCAL Recognising Textual Entailment Challenge. LNCS, Volume 3944, Jan 2006, pp. 177--190.
	3	Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., Giampiccolo, D., Magnini, B. and Szpektor, I. The Second PASCAL Recognising Textual Entailment Challenge. In Proc. of the Second PASCAL Challenges Workshop on Recognizing Textual Entailment, 2006.
	4	J. Herrera, A. Peñas, F. Verdejo, 2006. Textual Entailment Recognition Based on Dependency Analysis and WordNet. In: J. Quinonero-Candela, I. Dagan, B. Magnini, F. dAlché-Buc (editors). MLCW 2005. LNAI. Springer. 3944. 231--239.
	5	WordNet: a lexical database for the English language. http://wordnet.princeton.edu/
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