Abstract
The performance of an enterprise application (e.g. response time, throughput, or resource utilization) is an important quality attribute that can have a significant impact on a company’s success. When a performance problem such as a performance bottleneck has been detected, the root cause identified and a solution proposed, developers have to identify the elements of the application often manually that will undergo changes and determine how these elements must be changed in order to implement the solution. Many existing approaches are able to identify the elements that have to be modified but only few are able to determine the necessary types of changes on these elements. Neither of the approaches supports developers with a work plan sketching the implementation steps. In this paper, we propose an approach to point developers the way torwards an implementation of a performance or scalability solution with an ordered set of work activities. Rules are used to derive a work plan sketching the implementation of a solution for the particular application based on an initial set of work activities. The rule-based approach identifies impacted elements and determines how they should be changed. We demonstrate the proposed approach with a solution of a performance bottleneck as an example.
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References
UML Marte, http://www.omgmarte.org
Albrecht, A.J.: Measuring application development productivity. In: Proceedings of the Joint SHARE/GUIDE/IBM Application Development Symposium, vol. 10 (1979)
Arcelli, D., Cortellessa, V.: Software model refactoring based on performance analysis: Better working on software or performance side? In: FESCA (2013)
Arcelli, D., Cortellessa, V., Di Ruscio, D.: Applying model differences to automate performance-driven refactoring of software models. In: Balsamo, M.S., Knottenbelt, W.J., Marin, A. (eds.) EPEW 2013. LNCS, vol. 8168, pp. 312–324. Springer, Heidelberg (2013)
Arcelli, D., Cortellessa, V., Trubiani, C.: Antipattern-based model refactoring for software performance improvement. In: Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures. ACM (2012)
Arnold, R.S., Bohner, S.A.: Software Change Impact Analysis. IEEE Computer Society Press (1996)
Becker, S., Koziolek, H., Reussner, R.: The palladio component model for model-driven performance prediction. Journal of Systems and Software 82(1) (2009)
Boehm, B., Clark, B., Horowitz, E., Westland, C., Madachy, R., Selby, R.: Cost models for future software life cycle processes: Cocomo 2.0. Annals of Software Engineering 1(1) (1995)
Briand, L.C., Labiche, Y., O’sullivan, L.: Impact analysis and change management of uml models. In: Proceedings of the International Conference on Software Maintenance, ICSM 2003. IEEE (2003)
Cortellessa, V., Di Marco, A., Eramo, R., Pierantonio, A., Trubiani, C.: Approaching the model-driven generation of feedback to remove software performance flaws. In: 35th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2009. IEEE (2009)
Cortellessa, V., Di Marco, A., Trubiani, C.: An approach for modeling and detecting software performance antipatterns based on first-order logics. Software and Systems Modeling (2012)
Edwards, W.: How to use multiattribute utility measurement for social decision making. IEEE Transactions on Systems, Man and Cybernetics 7(5) (1977)
Eramo, R., Pierantonio, A., Romero, J.R., Vallecillo, A.: Change management in multi-viewpoint system using asp. In: 2008 12th Enterprise Distributed Object Computing Conference Workshops. IEEE (2008)
O.M. Group. Business process model and notation, bpmn (2011)
Heidenreich, F., Johannes, J., Seifert, M., Wende, C.: Jamopp: The java model parser and printer. Techn. Univ., Fakultät Informatik (2009)
Keller, A., Schippers, H., Demeyer, S.: Supporting inconsistency resolution through predictive change impact analysis. In: Proceedings of the 6th International Workshop on Model-Driven Engineering, Verification and Validation, p. 9. ACM (2009)
Lehnert, S.: A review of software change impact analysis. Ilmenau University of Technology, Tech. Rep. (2011)
Lehnert, S., Farooq, Q., Riebisch, M.: A taxonomy of change types and its application in software evolution. In: 2012 IEEE 19th International Conference and Workshops on Engineering of Computer Based Systems (ECBS) (April 2012)
Lehnert, S., Riebisch, M., et al.: Rule-based impact analysis for heterogeneous software artifacts. In: 2013 17th European Conference on Software Maintenance and Reengineering (CSMR). IEEE (2013)
Lindvall, M., Sandahl, K.: Traceability aspects of impact analysis in object-oriented systems. Journal of Software Maintenance: Research and Practice 10(1) (1998)
McCabe, T.J.: A complexity measure. In: Proceedings of the 2nd International Conference on Software Engineering, ICSE 1976, Los Alamitos, CA, USA. IEEE Computer Society Press (1976)
Parsons, T.: Automatic Detection of Performance Design and Deployment Antipatterns in Component Based Enterprise Systems. PhD thesis, University College Dublin (2007)
Saaty, T.: The analytic hierarchy and analytic network processes for the measurement of intangible criteria and for decision-making. In: Multiple Criteria Decision Analysis: State of the Art Surveys. Springer, New York (2005)
Schwaber, K., Beedle, M.: Agile Software Development with Scrum. Pearson (2002)
Smith, C.U., Williams, L.G.: Software performance antipatterns. In: Workshop on Software and Performance (2000)
Stammel, J., Reussner, R.: Kamp: Karlsruhe architectural maintainability prediction. In: Proceedings of the 1st Workshop des GI-Arbeitskreises Langlebige Softwaresysteme (L2S2): Design for Future-Langlebige Softwaresysteme (2009)
Stammel, J., Trifu, M.: Tool-supported estimation of software evolution effort in service-oriented systems. In: Joint Proceedings of the First International Workshop on Model-Driven Software Migration (MDSM 2011) and the Fifth International Workshop on Software Quality and Maintainability (SQM 2011), vol. 708 (2011)
Trubiani, C., Koziolek, A.: Detection and solution of software performance antipatterns in palladio architectural models. In: ICPE (2011)
van Hoorn, A., Rohr, M., Hasselbring, W.: Generating probabilistic and intensity-varying workload for web-based software systems. In: Kounev, S., Gorton, I., Sachs, K. (eds.) SIPEW 2008. LNCS, vol. 5119, pp. 124–143. Springer, Heidelberg (2008)
Wert, A., Oehler, M., Heger, C., Farahbod, R.: Automatic Detection of Performance Anti-patterns in Inter-component Communications. In: Proceedings of the 10th International Conference on Quality of Software Architecture, QoSA 2014 (2014)
Xu, J.: Rule-based automatic software performance diagnosis and improvement. Performance Evaluation 69(11) (2012)
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Heger, C., Heinrich, R. (2014). Deriving Work Plans for Solving Performance and Scalability Problems. In: Horváth, A., Wolter, K. (eds) Computer Performance Engineering. EPEW 2014. Lecture Notes in Computer Science, vol 8721. Springer, Cham. https://doi.org/10.1007/978-3-319-10885-8_8
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DOI: https://doi.org/10.1007/978-3-319-10885-8_8
Publisher Name: Springer, Cham
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