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Automatic Extraction of Cause-Effect-Relations from Requirements Artifacts

Frattini, Julian, 1995- (author)
Blekinge Tekniska Högskola,Institutionen för programvaruteknik
Junker, Maximilian (author)
Qualicen GmbH, DEU
Unterkalmsteiner, Michael (author)
Blekinge Tekniska Högskola,Institutionen för programvaruteknik,fortiss GmbH, DEU
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Mendez, Daniel (author)
Blekinge Tekniska Högskola,Institutionen för programvaruteknik,fortiss GmbH, DEU
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 (creator_code:org_t)
2021-01-27
2020
English.
In: Proceedings - 2020 35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020. - New York, NY, USA : Institute of Electrical and Electronics Engineers Inc.. - 9781450367684 ; , s. 561-572
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Background: The detection and extraction of causality from natural language sentences have shown great potential in various fields of application. The field of requirements engineering is eligible for multiple reasons: (1) requirements artifacts are primarily written in natural language, (2) causal sentences convey essential context about the subject of requirements, and (3) extracted and formalized causality relations are usable for a (semi-)automatic translation into further artifacts, such as test cases. Objective: We aim at understanding the value of interactive causality extraction based on syntactic criteria for the context of requirements engineering. Method: We developed a prototype of a system for automatic causality extraction and evaluate it by applying it to a set of publicly available requirements artifacts, determining whether the automatic extraction reduces the manual effort of requirements formalization. Result: During the evaluation we analyzed 4457 natural language sentences from 18 requirements documents, 558 of which were causal (12.52%). The best evaluation of a requirements document provided an automatic extraction of 48.57% cause-effect graphs on average, which demonstrates the feasibility of the approach. Limitation: The feasibility of the approach has been proven in theory but lacks exploration of being scaled up for practical use. Evaluating the applicability of the automatic causality extraction for a requirements engineer is left for future research. Conclusion: A syntactic approach for causality extraction is viable for the context of requirements engineering and can aid a pipeline towards an automatic generation of further artifacts from requirements artifacts. © 2020 ACM.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Language Technology (hsv//eng)

Keyword

causality extraction
natural language processing
pattern matching
requirements artifacts
Requirements engineering
Software engineering
Syntactics
Automatic extraction
Automatic Generation
Automatic translation
Interactive causality
Requirements document
Requirements formalizations
Syntactic approach
Syntactic criteria
Extraction

Publication and Content Type

ref (subject category)
kon (subject category)

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