Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Empirical Software Engineering
Erschienen in: Empirical Software Engineering 1/2017

30.04.2016

The impact of domain knowledge on the effectiveness of requirements engineering activities

verfasst von: Ali Niknafs, Daniel Berry

Erschienen in: Empirical Software Engineering | Ausgabe 1/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Excerpt

A key step of any software development is deciding precisely what to build (Brooks 1995). The process of arriving at a set of features that need to be developed is referred to as requirements engineering (RE). The quality of the final product of a software development project depends on the extent to which the product satisfies its stakeholders’ needs (Finkelstein 1994). Therefore, the more emphasis that is given to RE, the better the chances are of obtaining high quality software. …
Vorheriger Artikel Defect propagation at the project-level: results and a post-hoc analysis on inspection efficiency
Nächster Artikel Extracting and analyzing time-series HCI data from screen-captured task videos

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
Although a person could be a man or woman, we have assumed any nonspecific person is a man throughout the body of this paper.
 
2
In a Unicode-compliant BDWP, knowing the time-ordered, logically-ordered internal representation of the currently displayed visually-ordered text helps the user predict the effect of any editing change enacted on the displayed view, particularly since the internal representation may have so-called zero-width control characters that are invisible in the visual-order view.
 
3
Factors the statistical analyses.
 
4
Also called “principal axis factoring” or “common factor analysis”.
 
Literatur
Al-Rawas A, Easterbrook S (1996) Communication problems in requirements engineering: A field study. In: Proceedings of the First Westminster Conference on Professional Awareness in Software Engineering (PACE), pp 47–60
Anand SS, Bell DA, Hughes JG (1995) The role of domain knowledge in data mining. In: Proceedings of the Fourth International Conference on Information and Knowledge Management (CIKM), pp 37–43
Apfelbaum EP, Phillips KW, Richeson JA (2014) Rethinking the baseline in diversity research: Should we be explaining the effects of homogeneity? Perspect Psychol Sci 9(3):235–244CrossRef
Basili VR, Caldiera G, Rombach DH (1994) The goal question metric approach. In: Marciniak JJ (ed) Encyclopedia of software engineering, vol I. Wiley
Berenbach B, Paulish DJ, Kazmeier J, Rudorfer A (2009) Software & systems requirements engineering: in practice. McGraw-Hill, New York
Berry DM (1995) The importance of ignorance in requirements engineering. J Syst Softw 28(2):179–184CrossRef
Berry DM (1999) Stretching letter and slanted-baseline formatting for arabic, hebrew, and persian with ditroff/ffortid and dynamic postscript fonts. Softw Pract Experience 29(15):1417–1457CrossRef
Berry DM (2002) The importance of ignorance in requirements engineering: an earlier sighting and a revisitation. J Syst Softw 60(1):83–85MathSciNetCrossRef
Blom G (1960) Statistical estimates and transformed beta-variables. Inc Stat 10 (1):53–55
Brooks FP (1995) The mythical man-month: essays on software engineering, 20th anniversary edition. Addison-Wesley Professional, Boston
Carver JC, Nagappan N, Page A (2008) The impact of educational background on the effectiveness of requirements inspections: an empirical study. IEEE Trans Softw Eng 34(6):800–812CrossRef
Dagenais B, Ossher H, Bellamy RKE, Robillard MP, de Vries JP (2010) Moving into a new software project landscape. In: Proceedings of the International Conference on Software Engineering (ICSE), vol 1, pp 275–284
Damian D, Helms R, Kwan I, Marczak S, Koelewijn B (2013) The role of domain knowledge and cross-functional communication in socio-technical coordination. In: Proceedings of the 2013 International Conference on Software Engineering (ICSE), pp 442–451
DeMarco T, Lister T (1987) Peopleware: productive projects and teams. Dorset House, New York
Dieste O, Juristo N, Shull F (2008) Understanding the customer: what do we know about requirements elicitation? IEEE Softw 25(2):11–13CrossRef
Dunbar K (1999) How scientists build models invivo science as a window on the science mind. In: Magnani L, Nersessian N, Thagard P (eds) Model-based reasoning in scientific discovery. Kluwer Academic/Plenum Publishers, New York, pp 85–99
Feldt R, Magazinius A (2010) Validity threats in empirical software engineering research—an initial survey. In: Proceedings of the International Conference on Software Engineering and Knowledge Engineering, pp 374–379
Ferrari R, Madhavji NH (2007) The impact of requirements knowledge and experience on software architecting: An empirical study. In: Proceedings of the Sixth Working IEEE/IFIP Conference on Software Architecture (WICSA)
Finkelstein A (1994) Requirements engineering: a review and research agenda. In: Proceedings of the First Asia-Pacific Software Engineering Conference, pp 10–19
Fischer G (1999) Symmetry of igorance, social creativity, and meta-design. In: Proceedings of the 3rd Conference on Creativity & Cognition (C&C), pp 116–123
Frappaolo C (2008) Implicit knowledge. Knowl Manag Res Pract 6(1):23–25CrossRef
Glass GV, Peckham PD, Sanders JR (1972) Consequences of failure to meet assumptions underlying the fixed effects analyses of variance and covariance. Rev Educ Res 42(3):237–288CrossRef
Habusha U, Berry D (1990) vi.iv, a bi-directional version of the vi full-screen editor. Electron Publ — Origination Dissemination, Des 3(2):65–91
Hadar I, Soffer P, Kenzi K (2014) The role of domain knowledge in requirements elicitation via interviews: an exploratory study. J Requir Eng 19(2):143–149CrossRef
Hanebutte N, Taylor CS, Dumke RR (2003) Techniques of successful application of factor analysis in software measurement. Empir Softw Eng 8(1):43–57CrossRefMATH
Hinton PR, McMurray I, Brownlow C (2004) SPSS Explained. Routledge, East Sussex
Höst M, Regnell B, Wohlin C (2000) Using students as subjects — a comparative study of students and professionals in lead-time impact assessment. Empir Softw Eng 5(3):201–214CrossRefMATH
Itkonen J, Mantyla MV, Lassenius C (2013) The role of the tester’s knowledge in exploratory software testing. IEEE Trans Softw Eng 39(5):707–724CrossRef
Jarke M, Jr JAB, Rolland C, Sutcliffe AG, Vassiliou Y (1993) Theories underlying requirements engineering: an overview of NATURE at Genesis. In: Proceedings of the IEEE International Symposium on Requirements Engineering (RE), pp 19–31
Kopanas I, Avouris NM, Daskalaki S (2002) The role of domain knowledge in a large scale data mining project. In: Vlahavas CDS, Ioannis P (eds) Methods and Applications of Artificial Intelligence, Lecture Notes in Computer Science, vol 2308. Springer, Berlin, pp 288–299
Kristensson P, Gustafsson A, Archer T (2004) Harnessing the creative potential among users. J Prod Innov Manag 21(1):4–14CrossRef
Laplante PA (2014) Requirements engineering for software and systems, 2nd Edn. Taylor & Francis Group, Boca Raton
Lauesen S (2001) Software requirements: styles & techniques. Pearson Education, Harlow
Luchins AS (1942) Mechanization in problem solving: the effect of einstellung. Psychol Monogr 54(6):i–95CrossRef
Luchins AS, Luchins EH (1950) New experimental attempts at preventing mechanization in problem solving. J Gen Psychol 42:1335–1342CrossRef
Naur P, Randell B (1969) Software engineering: report of a conference sponsored by the NATO science committee. Scientific Affairs Division, NATO, Brussels
Niknafs A, Berry DM (2012) The impact of domain knowledge on the effectiveness of requirements idea generation during requirements elicitation. In: Proceedings of the 20th IEEE International Requirements Engineering Conference (RE), pp 181–190
Niknafs A, Berry DM (2013) An industrial case study of the impact of domain ignorance on the effectiveness of requirements idea generation during requirements elicitation. In: Proceedings of the 21st IEEE International Requirements Engineering Conference (RE), pp 279–283
Osborn A (1953) Applied Imagination. Charles Scribner’s, New York
Pascal B, Krailsheimer AJ (1968) Pensees: Translated with an Introduction by A.J. Krailsheimer. Penguin, London
Rose P, Kumar M, Ajmeri N, Agrawal M, Sivakumar V, Ghaisas S (2009) A method and framework for domain knowledge assisted requirements evolution (K-RE). In: Proceedings of CONSEG-09: International Conference on Software Engineering, pp 87–97
Sharp H (1991) The role of domain knowledge in software design. Behav Inform Technol 10(5):383–401CrossRef
Warner RM (2012) Applied statistics: from bivariate through multivariate techniques: from bivariate through multivariate techniques. Sage Publications, Thousand Oaks
Wiley J (1998) Expertise as mental set: the effects of domain knowledge in creative problem solving. Mem Cogn 26(4):716–730CrossRef
Wohlin C, Runeson P, Höst M, Ohlsson MC, Regnell B, Wesslén A (2000) Experimentation in software engineering: an introduction. Kluwer Academic Publishers, NorwellCrossRefMATH
Metadaten
Titel
The impact of domain knowledge on the effectiveness of requirements engineering activities
verfasst von
Ali Niknafs
Daniel Berry
Publikationsdatum
30.04.2016
Verlag
Springer US
Erschienen in
Empirical Software Engineering / Ausgabe 1/2017
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI
https://doi.org/10.1007/s10664-015-9416-2

Weitere Artikel der Ausgabe 1/2017

Empirical Software Engineering 1/2017 Zur Ausgabe

OriginalPaper

Characterizing logging practices in Java-based open source software projects – a replication study in Apache Software Foundation

OriginalPaper

An experimental search-based approach to cohesion metric evaluation

OriginalPaper

An empirical study of emergency updates for top android mobile apps

OriginalPaper

Extracting and analyzing time-series HCI data from screen-captured task videos

OriginalPaper

A stability assessment of solution adaptation techniques for analogy-based software effort estimation

OriginalPaper

Learning to rank code examples for code search engines