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09 On Presuppositions in Requirements






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    09 On Presuppositions in Requirements 09 On Presuppositions in Requirements Presentation Transcript

    • On Presuppositions in Requirements Lin Ma Bashar Nuseibeh , Paul Piwek, Anne De Roeck, Alistair Willis Department of Computing The Open University, U.K. Acknowledgement : MaTREx Project (EPSRC Grant Number: EP/F069227/1)
    • Research Aim and summary
      • To discover tacit knowledge in requirements text by tracking linguistic presuppositions.
      • Specific focus:
        • “ Nocuous tacit knowledge”
        • Determined by human judgement
      • Wider context:
        • MaTREx project on use of NLP techniques, such as ambiguity analysis and presuppositions
    • Tacit Knowledge
      • “ We know more than we can tell ” – Polanyi, 1963
      • Janik (1988) argues that the term “tacit knowledge” is used at two ways:
        • firstly, following Polanyi, tacit knowledge is knowledge inexpressible in words , and it is acquired by familiarity or practice such as smells and sounds;
        • secondly, tacit knowledge at a shallow level is knowledge not yet put into words such as craft knowledge and presuppositions .
      • We adopt Janek’s second perspective:
        • Tacit knowledge is knowledge that knowers know and could have articulated but omit doing so for some reason, perhaps because they simply were not asked .
    • Presupposition
      • Presuppositions are background information or assumptions that can be taken for granted.
      • Examples:
        • The King of France is Bald.
        • Presupposition: There is king of France.
        • John knows that Susan is coming to the party.
        • Presupposition : Susan is coming to the party.
        • Richard managed to pass the exam.
        • Presupposition : Richard tried to pass the exam.
    • Presupposition triggers
      • Presupposition is believed to be signalled by certain types of syntactical structure, which are called presupposition triggers .
      • Triggers:
      • Definite description: The King of France
      • Factive verb: know
      • Implicative verb: manage
    • Presupposition triggers - cont.
      • The trigger types include:
      • Definite descriptions , e.g. the device, its accessibility;
      • Factive verbs , e.g. know, reveal;
      • Implicative verbs , e.g. avoid, intend;
      • Change of state verbs , e.g. continue, stop;
      • Clefts – it + be + noun + subordinate clause;
      • Stressed constituents – words in italic in texts;
      • Counter factual conditionals – what would be the case is something were true;
      • Expressions of repetition , e.g. also, too;
      • Temporal relations , e.g. since, after;
      • Comparisons , e.g. less/larger than
    • Our preliminary case study
      • We studied a 20-page requirements document for integrated circuit chip design.
      • Our study was mostly manual , although we automated the identification of noun phrases.
      • We recorded the kinds of presuppositions that appeared, and found the majority triggered by definite descriptions .
    • Examples found in document
      • Noun phrases
      • Sentence: “ Accessibility in the experimental hall is required for changing the piggy board where the device will be mounted.”
      • Presuppositions: There is a piggy board.
      • There is a device.
      • Factive verb
      • Sentence: “…tests revealed that redundancy to Single Event Upsets is required.”
      • Presupposition: Redundancy to Single Event Upsets is required.
      • Implicative verb
      • Sentence: “…chambers shall avoid that two CMA share the same gas volume…”
      • Presupposition: Two CMA may share the same gas volume.
    • Which presuppositions are “dangerous”?
      • “ Accessibility in the experimental hall is required for changing the piggy board where the device will be mounted. ”
        • A new device or “the piggy board”?
      • “ ...will have various interfaces for different groups of users. While the appearance of the user interface may be similar, the functionality of each user interface will be distinct...”
      • “ The user interface” refers to “various interfaces” or “each user interface”?
    • Nocuously Tacit Knowledge
      • “ danger” is in the eye of the beholder (the reader).
      • One way to determine this is by conducting empirical studies to elicit human judgements ( ala Chantree et al @ RE’06).
      • As with nocuous ambiguity , nocuous presuppositions are those that signal tacit knowledge who tacitness may have a negative impact on the reading interpretation of the requirements.
    • Tracking presuppositions
      • What we know:
        • By using natural language processing techniques, definite descriptions can easily be found.
      • Where we are:
        • Currently, there are only a few representative example words or constructions of presupposition triggers. They can only be found by hand.
      • What we need to do:
        • Detect more presupposition triggers based on natural language processing techniques, and try to relate these to significant tacit knowledge.
    • Related work
      • Automatically tracking presupposition by NLP
      • K. Wiemer-Hastings and P. Wiemer-Hastings, “DP: a detector for presuppositions in survey questions,” Proceedings of the sixth conference on Applied natural language processing , 2000, pp. 90–96.D.
      • Clausen and C.D. Manning, “Presupposed Content and Entailments in Natural Language Inference,” ACL-IJCNLP 2009 , p. 70.  
      • Nothing in RE?
    • Future Work (Lin’s PhD research agenda!)
        • Case study on behaviour and linguistic attributes of presuppositions in more requirements documents with the help of NLP.
        • Discovery of nocuous presuppositions by collecting human judgments from stakeholders
        • Building a system to automatically highlight presuppositions that have negative impact on communication in requirement documents.
    • Conclusion
      • Our preliminary work has shown that tacit knowledge can be extracted by tracking presuppositions in requirements documents.
      • With the help of NLP techniques and the involvement of human judgements, tracking presuppositions in requirements can make some elements of tacit knowledge explicit.
    • Thank you.
      • Email:
        • {L.Ma, B.Nuseibeh, P.Piwek, A.Deroeck, A.G.Willis}@open.ac.uk
      • MaTREx Project:
        • http://crc.open.ac.uk/matrex
        • http://www.comp.lancs.ac.uk/research/projects/matrex/
        • http://gow.epsrc.ac.uk/ViewPanelROL.aspx?PanelId=4612&RankingListId=6037