An Architectural Smells Detection Tool for C and C++ Projects

Biaggi, Andrea; Fontana, Francesca Arcelli; Roveda, Riccardo

doi:10.1109/seaa.2018.00074

Cited by 17 publications

(7 citation statements)

References 5 publications

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“…Another threat concerns the detection of the smells considered in this project which depends on the implementation offered by Arcan. This is partially mitigated, as the Arcan tool has already been used and evaluated in a number of studies [6], [26].…”

Section: Threats To Validitymentioning

confidence: 99%

Investigating Instability Architectural Smells Evolution: An Exploratory Case Study

Sas

Avgeriou

Fontana

2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Architectural smells may substantially increase maintenance effort and thus require extra attention for potential refactoring. While we currently understand this concept and have identified different types of such smells, we have not yet studied their evolution in depth. This is necessary to inform their prioritisation and refactoring. This study analyses the evolution of individual architectural smell instances over time, and the characteristics that define these instances. Three different types of architectural smells are taken into consideration and mined from a total of 524 versions across 14 different projects. The results show how different smell types differ in multiple aspects, such as their growth rate, the importance of the affected elements over time in the dependency network of the system, and the time each instance affects the system. They also cast valuable insights on what aspects are the most important to consider during prioritisation and refactoring activities.

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Section: Threats To Validitymentioning

confidence: 99%

Investigating Instability Architectural Smells Evolution: An Exploratory Case Study

Sas

Avgeriou

Fontana

2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

Self Cite

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“…This cannot be said for other tools available, as many of them are based on previous work of the very authors of the tools, and therefore may potentially be biased. Moreover, to guarantee that the results obtained by the ARCAN tool are indeed in line with the definitions provided by previous work, the tool was used and evaluated in a number of studies (Arcelli Fontana et al 2017b;Biaggi et al 2018;Sas et al 2019).…”

Section: Construct Validity This Aspect Of Validity Reflects To What ...mentioning

confidence: 89%

On the evolution and impact of architectural smells—an industrial case study

2022

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Architectural smells (AS) are notorious for their long-term impact on the Maintainability and Evolvability of software systems. The majority of research work has investigated this topic by mining software repositories of open source Java systems, making it hard to generalise and apply them to an industrial context and other programming languages. To address this research gap, we conducted an embedded multiple-case case study, in collaboration with a large industry partner, to study how AS evolve in industrial embedded systems. We detect and track AS in 9 C/C++ projects with over 30 releases for each project that span over two years of development, with over 20 millions lines of code in the last release only. In addition to these quantitative results, we also interview 12 among the developers and architects working on these projects, collecting over six hours of qualitative data about the usefulness of AS analysis and the issues they experienced while maintaining and evolving artefacts affected by AS. Our quantitative findings show how individual smell instances evolve over time, how long they typically survive within the system, how they overlap with instances of other smell types, and finally what the introduction order of smell types is when they overlap. Our qualitative findings, instead, provide insights on the effects of AS on the long-term maintainability and evolvability of the system, supported by several excerpts from our interviews. Practitioners also mention what parts of the AS analysis actually provide actionable insights that they can use to plan refactoring activities.

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“…Although many software analysis tools provide information on various metrics, there is a limitation in the number of open source tools which can detect design smells [36]. AI Reviewer identifies code and design smells for C++ projects [6].…”

Section: Related Workmentioning

confidence: 99%

Design Smell Detection and Analysis for Open Source Java Software

Imran

2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Software design smells are design attributes which violate the fundamental design principles. Design smells are a key cause of design debt. Although the activities of design smell identification and measurement are predominantly considered in current literature, those which identify and communicate which design smells occur more frequently in newly developing software and which ones are more dominant in established software have been studied to a limited extent. This research describes a mechanism for identifying the design smells that are more prevalent in developing and established software respectively. A tool is provided which is used for design smell detection by analyzing large volume of source code. More specifically, 164,609 Lines of Code (LoC) and 5,712 class files of six developing and 244,930 LoC and 12,048 class files of five established open source Java software are analyzed. Obtained results show that out of the 4,020 occurrences of smells which were made for nine preselected types of design smells, 1,643 design smells were detected for developing software, which mainly consisted of four specific types of smells. For established software, 2,397 design smells were observed which predominantly consisted of four other types of smells. The remaining design smell was equally prevalent in both developing and established software. Desirable precision values ranging from 72.9% to 84.1% were obtained for the tool.

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An Architectural Smells Detection Tool for C and C++ Projects

Cited by 17 publications

References 5 publications

Investigating Instability Architectural Smells Evolution: An Exploratory Case Study

Investigating Instability Architectural Smells Evolution: An Exploratory Case Study

On the evolution and impact of architectural smells—an industrial case study

Design Smell Detection and Analysis for Open Source Java Software

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