UML consistency rules

Torre, Damiano; Labiche, Yvan; Genero, Marcela

doi:10.1145/2601248.2601292

Cited by 33 publications

(2 citation statements)

References 31 publications

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“…Nonetheless, we adapted the general consistency types in our work. A more recent study supports the results of the survey [31]. Additional classification of inconsistencies can be found in literature [21].…”

Section: Related Worksupporting

confidence: 81%

Incremental Consistency Checking in Delta-oriented UML-Models for Automation Systems

Kowal

Schaefer

2016

Electron. Proc. Theor. Comput. Sci.

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Automation systems exist in many variants and may evolve over time in order to deal with different environment contexts or to fulfill changing customer requirements. This induces an increased complexity during design-time as well as tedious maintenance efforts. We already proposed a multiperspective modeling approach to improve the development of such systems. It operates on different levels of abstraction by using well-known UML-models with activity, composite structure and state chart models. Each perspective was enriched with delta modeling to manage variability and evolution. As an extension, we now focus on the development of an efficient consistency checking method at several levels to ensure valid variants of the automation system. Consistency checking must be provided for each perspective in isolation, in-between the perspectives as well as after the application of a delta.

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Section: Related Worksupporting

confidence: 81%

Incremental Consistency Checking in Delta-oriented UML-Models for Automation Systems

Kowal

Schaefer

2016

Electron. Proc. Theor. Comput. Sci.

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“…Merely understanding model changes is not sufficient to understand how to co-change the code and vice versa. Given the strong correctness benefit, we argue that the use of inconsistency feedback should be common practice not just for error detection but also be change propagations/co-evolution given that there is almost no cost involved in using consistency checking mechanisms (e.g., Nentwich et al [NEFE03], Egyed [Egy11], Musuvathi et al [MPC + 02]) and given that many commonly usable consistency rules are available [TLG14]. We believe that there are likely subsequent benefits that stem from the quicker availability of inconsistency feedback for more correct models or code which we did not measure since it was out of the scope of this paper.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Study on the Impact of Inconsistency Feedback during Model and Code Co-changing.

Kanakis¹,

Khelladi²,

Fischer³

et al. 2019

JOT

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Model and code co-changing is about the coordinated modification of models and code during evolution. Intermittent inconsistencies are a common occurrence during co-changing. A partial co-change is the period in which the developer changed, say, the model but has not yet propagated the change to the code. Inconsistency feedback can be provided to developers for helping them to complete partial co-changes. However, there is no evidence whether such inconsistency feedback is useful to developers. To investigate this problem, we conducted a controlled experiment with 36 subjects who were required to complete ten partially completed change tasks between models and code of two non-trivial systems. The tasks were of different levels of complexity depending on how many model diagrams they affected. All subjects had to work on all change tasks but sometimes with and sometimes without inconsistency feedback. We then measured differences between task effort and correctness. We found that when subjects were given inconsistency feedback during tasks, they were 268% more likely to complete the co-change correctly compared to when they were not given inconsistency feedback. We also found that when subjects were not given inconsistency feedback, they nearly always failed in completing co-change tasks with high complexity where the partially completed changes were spread across different diagrams in the model. These findings suggest that inconsistency feedback (i.e. detection and repair) should form an integral part of co-changing, regardless of whether the code or the model changes first. Furthermore, these findings suggest that merely having access to changes (as with the given partially completed changes) is insufficient for effective co-changing.

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