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
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Empirical Software Engineering
Erschienen in: Empirical Software Engineering 3/2015

01.06.2015

Multi-objective ant colony optimization for requirements selection

verfasst von: José del Sagrado, Isabel M. del Águila, Francisco J. Orellana

Erschienen in: Empirical Software Engineering | Ausgabe 3/2015

Einloggen

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

search-config
loading …

Abstract

The selection of a set of requirements between all the requirements previously defined by customers is an important process, repeated at the beginning of each development step when an incremental or agile software development approach is adopted. The set of selected requirements will be developed during the actual iteration. This selection problem can be reformulated as a search problem, allowing its treatment with metaheuristic optimization techniques. This paper studies how to apply Ant Colony Optimization algorithms to select requirements. First, we describe this problem formally extending an earlier version of the problem, and introduce a method based on Ant Colony System to find a variety of efficient solutions. The performance achieved by the Ant Colony System is compared with that of Greedy Randomized Adaptive Search Procedure and Non-dominated Sorting Genetic Algorithm, by means of computational experiments carried out on two instances of the problem constructed from data provided by the experts.
Nächster Artikel 1600 faults in 100 projects: automatically finding faults while achieving high coverage with EvoSuite

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
Literatur
Albrecht AJ, Gaffney JE (1983) Software function, source lines of code, and development effort prediction: a software science validation. IEEE Trans Softw Eng 9(6):639–648CrossRef
Ali S, Briand LC, Hemmati H, Panesar-Walawege RK (2010) A systematic review of the application and empirical investigation of search-based test case generation. IEEE Trans Softw Eng 36(6):742–762CrossRef
Arcuri A, Fraser G (2013) Parameter tuning or default values? An empirical investigation in search-based software engineering. Empir Softw Eng 18(3):594–623CrossRef
Bagnall AJ, Rayward-Smith VJ, Whittley I (2001) The next release problem. Inf Softw Technol 43(14):883–890CrossRef
Baker P, Harman M, Steinhöfel K, Skaliotis A (2006) Search based approaches to component selection and prioritization for the next release problem. In: Proceedings of 22nd IEEE international conference on software maintenance (ICSM 2006). IEEE Computer Society, Philadelphia, pp 176–185CrossRef
Boehm BW (1981) Software engineering economics. Prentice Hall, Englewood CliffsMATH
Brooks FP (1995) The mythical man-month (anniversary edn). Addison-Wesley Longman Publishing Co., Inc., Boston
Carlshamre P (2002) Release planning in market-driven software product development: provoking an understanding. Requir Eng 7(3):139–151CrossRef
Carlshamre P, Sandahl K, Lindvall M, Regnell B, och Dag JN (2001) An industrial survey of requirements interdependencies in software product release planning. In: Proceedings of 5th IEEE international symposium on requirements engineering (RE 2001). IEEE Computer Society, Toronto, pp 84–93
Cheng BHC, Atlee JM (2007) Research directions in requirements engineering. In: Proceedings of international conference on software engineering, ISCE 2007. Workshop on the future of software engineering (FOSE 2007). Minneapolis, pp 285–303
Coello CAC, Lamont GB, Veldhuizen DAV (2007) Evolutionary algorithms for solving multi-objective problems evolutionary algorithms for solving multi-objective problems. Springer, New YorkMATH
Davis AM (2003) The art of requirements triage. IEEE Comput 36(3):42–49CrossRef
Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, New YorkMATH
Deb K, Agrawal S, Pratap A, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197CrossRef
del Sagrado J, del Águila IM (2009) Ant colony optimization for requirement selection in incremental software development. In: Proceedings of the 1st International Symposium on Search Based Software Engineering (SSBSE ’09). IEEE, Cumberland Lodge, Windsor
del Sagrado J, del Águila I, Orellana F (2010a) Ant colony optimization for the next release problem: a comparative study. In: Proceeding of Second International Symposium on Search Based Software Engineering (SSBSE 2010), Benevento, Italy, pp 67–76
del Sagrado J, del Águila IM, Orellana FJ, Túnez S (2010b) Requirements selection: knowledge based optimization techniques for solving the next release problem. In: Proceedings of the 6th Workshop on Knowledge Engineering and Software Engineering (KESE6). Karlsruhe, Germany, CEUR-WS.org, CEUR Workshop Proceedings, vol 636
del Sagrado J, del Águila IM, Orellana FJ (2011) Requirements interaction in the next release problem. In: Proceedings of 13th annual Genetic and Evolutionary Computation Conference (GECCO 2011). Dublin, Ireland, pp 241–242
del Sagrado J, del Águila IM, Orellana FJ (2012) Metaheuristic aided software features assembly. In: Proceeding of 20th European Conference on Artificial Intelligence (ECAI 2012) Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track. Montpellier, France, pp 1009–1010
de Souza JT, Maia CLB, Ferreira T, do Carmo RAF, Brasil M (2011) An ant colony optimization approach to the software release planning with dependent requirements. In: Proceedings of the 3rd International Symposium on Search Based Software Engineering (SSBSE ’11), vol 6956. Springer, Szeged, Hungary, pp 142–157
Doerner KF, Gutjahr WJ, Hartl RF, Strauss C, Stummer C (2004) Pareto ant colony optimization: a metaheuristic approach to multiobjective portfolio selection. Ann Oper Res 131(1–4):79–99CrossRefMATHMathSciNet
Dorigo M, Gambardella LM (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1(1):53–66CrossRef
Dorigo M, Birattari M, Stutzle T (2006) Ant colony optimization. IEEE Comput Intell Mag 1(4):28–39CrossRef
Durillo J, Zhang Y, Alba E, Nebro A (2009) A study of the multi-objective next release problem. In: Proceeding of 1st international symposium on search based software engineering (SSBSE 2009). Cumberland Lodge, Windsor, pp 49–58
Durillo JJ, Zhang Y, Alba E, Harman M, Nebro AJ (2011) A study of the bi-objective next release problem. Empir Softw Eng 16(1):29–60CrossRef
Feo TA, Resende MGC (1989) A probabilistic heuristic for a computationally difficult set covering problem. Oper Res Lett 8(2):67–71CrossRefMATHMathSciNet
Finkelstein A, Harman M, Mansouri SA, Ren J, Zhang Y (2008) “Fairness analysis” in requirements assignments. In: Proceeding of 16th IEEE international requirements engineering conference (RE 2008). Barcelona, pp 115–124
Finkelstein A, Harman M, Mansouri SA, Ren J, Zhang Y (2009) A search based approach to fairness analysis in requirement assignments to aid negotiation, mediation and decision making. Requirement Eng 14(4):231–245CrossRef
Garey MR, Johnson DS (1990) Computers and intractability: a guide to the theory of NP-completeness. Freeman, New York
Greer D, Ruhe G (2004) Software release planning: an evolutionary and iterative approach. Inf Softw Technol 46(4):243–253CrossRef
Häckel S, Fischer M, Zechel D, Teich T (2008) A multi-objective ant colony approach for pareto-optimization using dynamic programming. In: Proceedings of genetic and evolutionary computation conference (GECCO 2008). ACM, Atlanta, pp 33–40
Harman M (2007) The current state and future of search based software engineering. In: Future of software engineering, FOSE ’07, pp 342–357
Harman M, Jones BF (2001) Search-based software engineering. Inf Softw Technol 43(14):833–839CrossRef
Iredi S, Merkle D, Middendorf M (2001) Bi-criterion optimization with multi colony ant algorithms. In: Proceedings of evolutionary multi-criterion optimization, first international conference (EMO 2001). Zurich, pp 359–372
Jiang H, Zhang J, Xuan J, Re Z, Hu Y (2010) A hybrid ACO algorithm for the next release problem. In: Proceedings of the 2nd international conference on software engineering and data mining (SEDM ’10). IEEE, Chengdu, pp 166–171
Johnson J (2003) CHAOS chronicles v3.0. Tech. rep.
Karlsson J, Olsson S, Ryan K (1997) Improving practical support for large-scale requirement prioritising. Requirement Eng 2(1):51–60CrossRef
Kotonya G, Sommerville I (1998) Requirements engineering: processes and techniques. Wiley, New York
Momoh J, Ruhe G (2006) Release planning process improvement an industrial case study. Software Process Improvement and Practice 11(3):295–307CrossRef
Pitsoulis L, Resende M (2003) Greedy randomized adaptive search procedures. Oxford University Press, pp 168–183
Resende M, Ribeiro C (2003) Greedy randomized adaptive search procedures. Kluwer Academic Publishers, Dordrecht, pp 219–249
Ruhe G, Saliu MO (2005) The art and science of software release planning. IEEE Softw 22(6):47–53CrossRef
Saliu MO, Ruhe G (2007) Bi-objective release planning for evolving software systems. In: Proceedings of the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT international symposium on foundations of software engineering. Dubrovnik, Croatia, pp 105–114
Schott J (1995) Fault tolerant design using single and multicriteria genetic algorithm optimization. PhD thesis, Massachusetts Institute of Technology, M.S., USA
Simmons E (2004) Requirements triage: what can we learn from a “medical” approach? IEEE Softw 21(4):86–88CrossRef
Srinivas N, Deb K (1994) Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evoltionary Computation 2:221–248CrossRef
Vianna DS, Arroyo JEC (2004) A GRASP algorithm for the multi-objective knapsack problem. In: Proceedings of 24th International Conference of the Chilean Computer Science Society (SCCC 2004), pp 69–75
Wiegers KE (2003) Software requirements. Microsoft Press, Redmon, WA, USA
Wohlin C, Runeson P, Höst M, Ohlsson M, Regnell B, Wesslén A (2012) Experimentation in software engineering: an introduction. Springer, BerlinCrossRef
Zhang Y, Harman M (2010) Search based optimization of requirements interaction management. In: Proceedings of Second International Symposium on Search Based Software Engineering (SSBSE 2010). Benevento, Italy, pp 47–56
Zhang Y, Harman M, Mansouri SA (2007) The multi-objective next release problem. In: Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2007). London, England, UK, pp 1129–1137
Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Trans Evol Comput 3(4):257–271CrossRef
Metadaten
Titel
Multi-objective ant colony optimization for requirements selection
verfasst von
José del Sagrado
Isabel M. del Águila
Francisco J. Orellana
Publikationsdatum
01.06.2015
Verlag
Springer US
Erschienen in
Empirical Software Engineering / Ausgabe 3/2015
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI
https://doi.org/10.1007/s10664-013-9287-3

Weitere Artikel der Ausgabe 3/2015

Empirical Software Engineering 3/2015 Zur Ausgabe

OriginalPaper

Achieving scalable mutation-based generation of whole test suites

OriginalPaper

Empirical evidence on the link between object-oriented measures and external quality attributes: a systematic literature review

OriginalPaper

An experiment on the effectiveness and efficiency of exploratory testing

OriginalPaper

Transfer learning in effort estimation

OriginalPaper

1600 faults in 100 projects: automatically finding faults while achieving high coverage with EvoSuite

OriginalPaper

Object-oriented software extensions in practice

Premium Partner

    Bildnachweise