The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
The Palladio component model for model-driven performance prediction
Open accessAbstract
One aim of component-based software engineering (CBSE) is to enable the prediction of extra-functional properties, such as performance and reliability, utilising a well-defined composition theory. Nowadays, such theories and their accompanying prediction methods are still in a maturation stage. Several factors influencing extra-functional properties need additional research to be understood. A special problem in CBSE stems from its specific development process: Software components should be specified and implemented independently from their later context to enable reuse. Thus, extra-functional properties of components need to be specified in a parametric way to take different influencing factors like the hardware platform or the usage profile into account. Our approach uses the Palladio component model (PCM) to specify component-based software architectures in a parametric way. This model offers direct support of the CBSE development process by dividing the model creation among the developer roles. This paper presents our model and a simulation tool based on it, which is capable of making performance predictions. Within a case study, we show that the resulting prediction accuracy is sufficient to support the evaluation of architectural design decisions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
Component software beyond object oriented programming
Szyperski, C., Gruntz, D., & Murer, S. (2002) · Cited by 4,576
Probability and Statistics With Reliability, Queuing, and Computer Science Applications.
Thompson, W. A., & Trivedi, K. S. (1983) · Journal of the American Statistical Association · doi:10.2307/2288237 · Cited by 2,601
(1992) · Choice Reviews Online · doi:10.5860/choice.29-3347 · Cited by 2,095
A classification and comparison framework for software architecture description languages
Medvidovic, N., & Taylor, R. N. (2000) · IEEE Transactions on Software Engineering · doi:10.1109/32.825767 · Cited by 1,987
(1984) · Prentice-Hall, Inc eBooks · Cited by 1,141
Queueing Networks and Markov Chains
Bolch, G., Greiner, S., de Meer, H., & Trivedi, K. S. (1998) · Wiley eBooks · doi:10.1002/0471200581 · Cited by 934
Component-Based Software Engineering: Putting the Pieces Together
Heineman, G. T., & Councill, W. T. (2001) · Medical Entomology and Zoology · Cited by 897
Model-based performance prediction in software development: a survey
Balsamo, S., Di Marco, A., Inverardi, P., & Simeoni, M. (2004) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2004.9 · Cited by 770
Modeling software architectures in the Unified Modeling Language
Medvidovic, N., Rosenblum, D. S., Redmiles, D. F., & Robbins, J. E. (2002) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/504087.504088 · Cited by 372
Cited by
Software Architecture Optimization Methods: A Systematic Literature Review
Aleti, A., Buhnova, B., Grunske, L., Koziolek, A., & Meedeniya, I. (2013) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2012.64 · Cited by 293
Automated Detection of AI-Obfuscated Plagiarism in Modeling Assignments
Sağlam, T., Hahner, S., Schmid, L., & Burger, E. (2024) · Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training · doi:10.1145/3639474.3640084 · Cited by 17
Metadata
- Authors
- Becker, S., Koziolek, H., & Reussner, R.
- Venue
- Journal of Systems and Software
- Publisher
- Elsevier BV
- Published
- 2009-01
- Volume
- 82
- Issue
- 1
- Pages
- 3-22
- ISSN
- 0164-1212 (ISSN-L)
- OpenAlex
- W1990405072
- Cited by
- 657
- References
- 21
- FWCI
- 72.08
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Palladio component model for model-driven performance prediction. https://app.cochat.ai/papers/10.1016/j.jss.2008.03.066
- The paper
- Becker, S., Koziolek, H., & Reussner, R. (2009). The Palladio component model for model-driven performance prediction. Journal of Systems and Software. https://doi.org/10.1016/j.jss.2008.03.066
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
