Anticipating Identification of Technical Debt Items in Model-Driven Software Projects

Gomes, Ramon Araújo; Pinheiro, Larissa Barbosa L.; Maciel, Rita Suzana Pitangueira

doi:10.1145/3422392.3422434

Cited by 2 publications

(1 citation statement)

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“…2 Like any software development approach, given the inherent and increasing complexity of MTs in MDD, there will often be some technical debt and code smells in developed model transformations. [3][4][5][6][7][8] Accumulation of neglected development quality issues on the model transformation development is called technical debts. MT related problems are termed MT quality flaws as well.…”

Section: Introductionmentioning

confidence: 99%

Towards a pattern‐based model transformation framework

Rouhi

Lano

2023

Softw Pract Exp

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Model‐Driven Development (MDD) is one of the important approaches to develop complex software systems. This approach tries to model a system in high‐abstraction level. Then through applying multiple transformations step by step, the model abstraction level is reduced and finally yields to executable code. As a result, Model transformation (MT) plays a pivotal role on the realization of MDD goals. Due to the increasing complexity of software systems, MTs naturally become more complex. Hence, qualitative technical issues may be overlooked or forgotten in these model transformations. To alleviate these issues in terms of technical debts/code smells in MTs, we can apply MT patterns. A main drawback on applying patterns is that most of them are cataloged in informal language. Additionally, construction of a conceptual framework to help MT designers through applying patterns requires a precise specification of the underlying MT patterns. With a formal basis, this paper is trying to realize the proposed framework. Hence, some of the existing well‐known MT patterns are formalized. Then based on the identified common technical debts/code smells in MTs, a designer can be directed to apply the appropriate patterns and resolve the detected problems iteratively. For the applicability and functionality of the proposed framework, several examples of problematic model transformations in terms of quality flaws were considered and resolved using the appropriate patterns. We consider the Epsilon Transformation Language (ETL) cases of model transformations in this paper, and other similar MT languages could be treated using the same measures and patterns as well.

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