CS2125 Paper Review Form - Winter 2018

Reviewer: Laura Walsh

Paper Title: A Relationship-Based Approach to Model Integration

Author(s):  M. Chechik, S. Nejati, M. Sabetzadeh 

1) Is the paper technically correct?
 [x] Yes
 [ ] Mostly (minor flaws, but mostly solid)
 [ ] No

2) Originality
 [ ] Very good (very novel, trailblazing work)
 [ ] Good 
 [x] Marginal (very incremental)
 [ ] Poor (little or nothing that is new)

3) Technical Depth
 [ ] Very good (comparable to best conference papers)
 [x] Good (comparable to typical conference papers)
 [ ] Marginal depth
 [ ] Little or no depth

4) Impact/Significance
 [ ] Very significant
 [ ] Significant
 [x] Marginal significance.
 [ ] Little or no significance.

5) Presentation
 [x] Very well written
 [ ] Generally well written
 [ ] Readable
 [ ] Needs considerable work
 [ ] Unacceptably bad

6) Overall Rating
 [ ] Strong accept (award quality)
 [x] Accept (high quality - would argue for acceptance)
 [ ] Weak Accept (borderline, but lean towards acceptance)
 [ ] Weak Reject (not sure why this paper was published)


7) Summary of the paper's main contribution and rationale
   for your recommendation. (1-2 paragraphs)
This paper gives a very nice overview of the current approaches to model integration and their uses and limitations. The authors describe that the motivation for this work is the lack of well defined terminology in the existing literature. This paper acts to more precisely define the three main integration techniques, namely: merge, composition and weaving. As well, the authors present two different merge operators that they have developed in previous work (algebraic merge and state machine merge).

The concepts presented in this paper are clearly explained. The paper itself is well structured and has good logical flow from one section to another. As this paper itself gives an overview of existing integration operators, it does not present wholly new information. However, it succeeds in effectively summarizing these existing techniques in an understandable way. It is technically very well written and is of high quality overall.


8) List 1-3 strengths of the paper.  (1-2 sentences each,
identified as S1, S2, S3.)

S1. The running example of a hospital system from different stakeholder's points of view lends itself very well to the explanation of the concepts discussed in this paper and helps to deepen understanding.

S2. A clearly presented, concise overview of the current state of model integration techniques is given. This would be a useful educational tool for those without strong background knowledge in this area.

S3. The two developed merge operators were each tested in a real case study. This gave a good idea of the applicability of these operators in these specific settings. These case studies showed that the TReMer+ tool could successfully be applied to merge models, among other uses.



9) List 1-3 weaknesses of the paper (1-2 sentences each,
identified as W1, W2, W3.)

W1. Some of the diagrams in the last few pages of the paper are a bit crowded (e.g. Fig 8 showing the mappings between the connector model and models M5 and M6). They are harder to interpret readily and take a bit more time to review. Maybe there is a simpler way to depict the commonalities between these models.

W2. It would have been interesting to get some more information within this paper about the results of the two case studies. The full details are available in two other referenced papers, however I think that a few sentences at the end of Section 5 that summarized the results would have been illuminating within this paper itself.