On the use of developers’ context for automatic refactoring of software anti-patterns

Morales, Rodrigo Rivera; Soh, Zphyrin; Khomh, Foutse; Antoniol, Giuliano; Chicano, Francisco

doi:10.1016/j.jss.2016.05.042

Cited by 42 publications

(18 citation statements)

References 65 publications

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“…The gist of the above-mentioned works on BPMA and BP patterns has much in common with the fields of refactoring [27] and anti-patterns [28] which in turn are closely related to our proposal. Antipatterns share certain features with the simplifiable fragments of a process model and can be found for different modelling languages (EPC, BPMN, PetriNets, YAWL, among others).…”

Section: Related Worksupporting

confidence: 56%

“…Subsequently, an automated software mechanism would translate these patterns into a representation that could be used for the simplification algorithm. In this line it is interesting to analyse the research themes of BP patterns [25], refactoring [27], anti-patterns [28], BPMV [18] or BPMA [11].…”

Section: Discussionmentioning

confidence: 99%

“…The replacement operation involves simple modifications on the BPMN model, actually, just adjusting or deleting some BPMN elements. The reader can see on the Listing 2 the Java code responsible for the replacement of pattern A (lines [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36].…”

Section: Complexitymentioning

confidence: 99%

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A Pattern Based Method for Simplifying a BPMN Process Model

et al. 2019

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Featured Application: To work with a simplified version of a BPMN model that condenses the information of interest can be very interesting from a human point of view (the understanding of the model is facilitated). Moreover, an optimised version of a BPMN model can yield in more efficient results for mining process software and data analytic techniques.Abstract: BPMN (Business Process Model and Notation) is currently the preferred standard for the representation and analysis of business processes. The elaboration of these BPMN diagrams is usually carried out in an entirely manual manner. As a result of this human-driven process, it is not uncommon to find diagrams that are not in their most simplified version possible (regarding the number of elements). This work presents a fully automatic method to simplify a BPMN process model document. A two-phase iterative algorithm to achieve this simplification is described in detail. This algorithm follows a heuristic approach that makes intensive use of a Pattern Repository. This software element is concerned with the description of feasible reductions and its enactment. The critical concept lies in the discovery of small reducible patterns in the whole model and their substitution with optimised versions. This approach has been verified through a double validation testing in total 8102 cases taken from real world BPMN process models. Details for its implementation and usage by practitioners are provided in this paper along with a comparison with other existing techniques concerned with similar goals.

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Section: Related Worksupporting

confidence: 56%

Section: Discussionmentioning

confidence: 99%

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A Pattern Based Method for Simplifying a BPMN Process Model

et al. 2019

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“…Finally, Morales et al [78] proposed the use of developers' context as a way for improving the practical usefulness of code smell detectors, devising an approach for automatic refactoring code smells.…”

Section: Related Literature On Code Smellsmentioning

confidence: 99%

Toward a Smell-Aware Bug Prediction Model

Palomba

Zanoni

Fontana

et al. 2019

IIEEE Trans. Software Eng.

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Code smells are symptoms of poor design and implementation choices. Previous studies empirically assessed the impact of smells on code quality and clearly indicate their negative impact on maintainability, including a higher bug-proneness of components affected by code smells. In this paper, we capture previous findings on bug-proneness to build a specialized bug prediction model for smelly classes. Specifically, we evaluate the contribution of a measure of the severity of code smells (i.e., code smell intensity) by adding it to existing bug prediction models based on both product and process metrics, and comparing the results of the new model against the baseline models. Results indicate that the accuracy of a bug prediction model increases by adding the code smell intensity as predictor. We also compare the results achieved by the proposed model with the ones of an alternative technique which considers metrics about the history of code smells in files, finding that our model works generally better. However, we observed interesting complementarities between the set of buggy and smelly classes correctly classified by the two models. By evaluating the actual information gain provided by the intensity index with respect to the other metrics in the model, we found that the intensity index is a relevant feature for both product and process metrics-based models. At the same time, the metric counting the average number of code smells in previous versions of a class considered by the alternative model is also able to reduce the entropy of the model. On the basis of this result, we devise and evaluate a smell-aware combined bug prediction model that included product, process, and smell-related features.We demonstrate how such model classifies bug-prone code components with an F-Measure at least 13% higher than the existing state-of-the-art models.

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“…Morales et al proposed ReCon, an approach that uses a developer's context for automatic refactoring of code smells. They defined the refactoring strategies for code smells of 4 types: Lazy Class, Long Parameter List, Spaghetti Code, and Speculative Generality.…”

Section: Related Workmentioning

confidence: 99%

Context‐based approach to prioritize code smells for prefactoring

Sae-Lim

Hayashi

Saeki

2017

J Software Evolu Process

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Existing techniques for detecting code smells (indicators of source code problems) do not consider the current context, which renders them unsuitable for developers who have a specific context, such as modules within their focus. Consequently, the developers must spend time identifying relevant smells. We propose a technique to prioritize code smells using the developers' context. Explicit data of the context are obtained using a list of issues extracted from an issue tracking system. We applied impact analysis to the list of issues and used the results to specify the context-relevant smells. Results show that our approach can provide developers with a list of prioritized code smells related to their current context. We conducted several empirical studies to investigate the characteristics of our technique and factors that might affect the ranking quality.Additionally, we conducted a controlled experiment with professional developers to evaluate our technique. The results demonstrate the effectiveness of our technique. KEYWORDScode smell, impact analysis, issue tracking system, prefactoring INTRODUCTIONCode smell, as defined by Fowler, 1-3 is an indicator of design flaws or problems in the source code. Code smells of many types are summarized as smell catalogs. [1][2][3] Code elements that are affected by code smells are recommended for improved quality because they are likely to cause difficulties in the future, as discussed in the literature, eg, making the source code more difficult to understand and maintain or increasing code components' fault-proneness. Moreover, Yamashita et al 4 found that code smells can affect important maintainability aspects. Hermans and Aivaloglou 5 conducted a controlled experiment, which revealed that code smells influence the block-based programming performance of novice programmers.Developers can improve the code by removing the code smells from the elements.Many researchers have examined factors that can introduce code smells into the system. Tufano et al 6 conducted a large-scale empirical study, which revealed that the main activities that tend to introduce code smells are implementing features and enhancing existing ones. Moreover, they found that developers with high workloads and pressure are more likely to introduce a smelly code to the system. Vale et al 7 investigated the factors that can influence code smells based on a software developer's perspective. That investigation revealed that factors such as time pressure, bad design decisions, lack of business knowledge, inexperienced developers, little time for refactoring, and low priority assigned to software quality influence the severity of smelly codes.For issue-driven software development projects, development teams tend to adopt an issue tracking system such as Jira or Bugzilla to manage their lists of issues, so-called backlogs. Such issues can be anything related to software change requests, eg, bug fixing or feature implementation.Developers apply refactoring techniques to source codes before implementing changes ...

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On the use of developers’ context for automatic refactoring of software anti-patterns

Cited by 42 publications

References 65 publications

A Pattern Based Method for Simplifying a BPMN Process Model

A Pattern Based Method for Simplifying a BPMN Process Model

Toward a Smell-Aware Bug Prediction Model

Context‐based approach to prioritize code smells for prefactoring

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