JSpIRIT: a flexible tool for the analysis of code smells

Vidal, Santiago; Vázquez, Hernán C.; Díaz-Pace, J. Andrés; Marcos, Claudia; Garcia, Alessandro; Oizumi, Willian

doi:10.1109/sccc.2015.7416572

Cited by 55 publications

(35 citation statements)

References 12 publications

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“…The relevance of our idea and concrete solution have been recognized by the software engineering community. We published our results in three international conferences [Oizumi et al 2016] (Qualis A1), [Vidal et al 2015], and [Vidal et al 2016]; a symposium [Oizumi et al 2014a]; an international journal ; and a workshop [Oizumi et al 2014b, Albuquerque et al 2014. Awards.…”

Section: Discussionmentioning

confidence: 99%

Synthesis of Code Anomalies: Revealing Design Problems in the Source Code

Oizumi¹,

Garcia²

2016

Anais Do XXIX Concurso De Teses E Dissertações (CTD 2016)

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Design problems affect most software projects and make their maintenance expensive and impeditive. Thus, the identification of potential design problems in the source code – which is very often the only available and upto-date artifact in a project – becomes essential in long-living software systems. This identification task is challenging as the reification of design problems in the source code tend to be scattered through several code elements. However, stateof-the-art techniques do not provide enough information to effectively help developers in this task. In this work, we address this challenge by proposing a new technique to support developers in revealing design problems. This technique synthesizes information about potential design problems, which are materialized in the implementation under the form of syntactic and semantic anomaly agglomerations. Our evaluation shows that the proposed synthesis technique helps to reveal more than 1200 design problems across 7 industry-strength systems, with a median precision of 71% and a median recall of 78%. The relevance of our work has been widely recognized by the software engineering community through 2 awards and 7 publications in international and national venues.

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Section: Discussionmentioning

confidence: 99%

Synthesis of Code Anomalies: Revealing Design Problems in the Source Code

Oizumi¹,

Garcia²

2016

Anais Do XXIX Concurso De Teses E Dissertações (CTD 2016)

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“…[70] and [143] instead present solutions for detecting smells in the design of a single service (specified in UML and ARCHERY, respectively). [9], [67] and [159] focus on identifying smells in the structuring of the sources of a service, and propose refactorings for resolving detected smells. All such approaches however differ from ours, as they focus on the design of a single service, while our approach focuses on the architectural smells due to the interactions among all components forming a microservice-based application.…”

Section: Related Workmentioning

confidence: 99%

Analysing and Deploying (Micro)service-Based Applications

Neri

2020

Communications in Computer and Information Science

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“…Other papers presenting code smell detection strategies are listed by Sharma and Spinellis [7]. Among the classified detection methods there are also strategies based on software metrics, like [32][33][34][35]. However, again, studies focus on the identification of code smells using manually defined code smell detection rules.…”

Section: Research Background and Related Workmentioning

confidence: 99%

“…Among the most known code smells are Brain Class, God Class, Brain Method and Feature Envy presented by Lanza and Marinescu [16]. They also present identification rules and some of them are implemented in Jdeodorand [36] and JSpIRIT [34]. The results of the conducted identification presented in [12], shows that the intersection between identified entities, using different detection methods and/or tools, is very small.…”

Section: Research Background and Related Workmentioning

confidence: 99%

Towards a Reliable Identification of Deficient Code with a Combination of Software Metrics

2018

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Different challenges arise while detecting deficient software source code. Usually a large number of potentially problematic entities are identified when an individual software metric or individual quality aspect is used for the identification of deficient program entities. Additionally, a lot of these entities quite often turn out to be false positives, i.e., the metrics indicate poor quality whereas experienced developers do not consider program entities as problematic. The number of entities identified as potentially deficient does not decrease significantly when the identification of deficient entities is carried out by applying code smell detection rules. Moreover, the intersection of entities identified as allegedly deficient among different code smell detection tools is small, which suggests that the implementation of code smell detection rules are not consistent and uniform. To address these challenges, we present a novel approach for identifying deficient entities that is based on applying the majority function on the combination of software metrics. Program entities are assessed according to selected quality aspects that are evaluated with a set of software metrics and corresponding threshold values derived from benchmark data, considering the statistical distributions of software metrics values. The proposed approach was implemented and validated on projects developed in Java, C++ and C#. The validation of the proposed approach was done with expert judgment, where software developers and architects with multiple years of experiences assessed the quality of the software classes. Using a combination of software metrics as the criteria for the identification of deficient source code, the number of potentially deficient object-oriented program entities proved to be reduced. The results show the correctness of quality ratings determined by the proposed identification approach, and most importantly, confirm the absence of false positive entities.

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JSpIRIT: a flexible tool for the analysis of code smells

Cited by 55 publications

References 12 publications

Synthesis of Code Anomalies: Revealing Design Problems in the Source Code

Synthesis of Code Anomalies: Revealing Design Problems in the Source Code

Analysing and Deploying (Micro)service-Based Applications

Towards a Reliable Identification of Deficient Code with a Combination of Software Metrics

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