Measuring architecture quality by structure plus history analysis

Schwanke, Robert W.; Xiao, Lu; Cai, Yuanfang

doi:10.1109/icse.2013.6606638

Cited by 34 publications

(25 citation statements)

References 21 publications

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“…The collected data, moreover, contains numerous zeroes (i.e., files that do not change or do not have defects). The same phenomena have also been observed by other researchers [34], [36], [45]. In fact, it has been shown that the distribution of fault data over modules in real systems are highly unbalanced [45].…”

Section: B Underlying Characteristics Of the Datasupporting

confidence: 70%

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A Study on the Role of Software Architecture in the Evolution and Quality of Software

Kouroshfar

Mirakhorli

Bagheri

et al. 2015

2015 IEEE/ACM 12th Working Conference on Mining Software Repositories

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Conventional wisdom suggests that a software system's architecture has a significant impact on its evolution. Prior research has studied the evolution of software using the information of how its files have changed together in their revision history. No prior study, however, has investigated the impact of architecture on the evolution of software from its change history. This is mainly because most open-source software systems do not document their architectures. We have overcome this challenge using several architecture recovery techniques. We used the recovered models to examine if co-changes spanning multiple architecture modules are more likely to introduce bugs than co-changes that are within modules. The results show that the co-changes that cross architectural module boundaries are more correlated with defects than co-changes within modules, implying that, to improve accuracy, bug predictors should also take the software architecture of the system into consideration.

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Section: B Underlying Characteristics Of the Datasupporting

confidence: 70%

“…The last project that we studied is an industrial software project, called System J, which is codename for a system that has also been the subject of a prior empirical study [36]. It is a two-year old development project, comprised of about 300 KSLOC of Java in 900 files, and structured in 165 Java packages.…”

Section: Executing the Analysismentioning

confidence: 99%

A Study on the Role of Software Architecture in the Evolution and Quality of Software

Kouroshfar

Mirakhorli

Bagheri

et al. 2015

2015 IEEE/ACM 12th Working Conference on Mining Software Repositories

Self Cite

View full text Add to dashboard Cite

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“…After examining how files change together in revision histories [18,22], we found that when a group of files frequently changes together, but they lack syntactical or architectural relationships, it often implies unencapsulated assumptions, implementation errors, or architectural problems. We term these modularity violations.…”

Section: Introductionmentioning

confidence: 98%

“…Although our recent industrial case study [18] revealed that architecture problems are the root cause of a large number of defects, the relationships between file error-proneness and architectural properties have been largely ignored by the software community.…”

Section: Introductionmentioning

confidence: 99%

“…The algorithm first identifies three layers: l1:(rc1-2), l2:(rc3-21), and l3:(rc22-32). Within l2, it then calculates two modules, m1:(3-10) and m2: (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21), and then recursively calculates the DRH structure within each module. For example, m2 is further calculated into a two-layer hierarchy: l4:(rc11-20) and l5:(rc21-21).…”

Section: Introductionmentioning

confidence: 99%

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Design rule spaces: a new form of architecture insight

Xiao

Cai

Kazman

2014

Proceedings of the 36th International Conference on Software Engineering

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In this paper, we investigate software architecture as a set of overlapping design rule spaces, formed by one or more structural or evolutionary relationships and clustered using our design rule hierarchy algorithm. Considering evolutionary coupling as a special type of relationship, we investigated (1) whether design rule spaces can reveal structural relations among error-prone files; (2) whether design rule spaces can reveal structural problems contributing to error-proneness. We studied three large-scale open source projects and found that error-prone files can be captured by just a few design rule sub-spaces. Supported by our tool, Titan, we are able to flexibly visualize design rule spaces formed by different types of relationships, including evolutionary dependencies. This way, we are not only able to visualize which error-prone files belong to which design rule spaces, but also to visualize the structural problems that give insight into why these files are error prone. Design rule spaces provide valuable direction on which parts of the architecture are problematic, and on why, when, and how to refactor.

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A case study on modularity violations in cyber‐physical systems

Xiao

Pennock

Cardoso

et al. 2020

Systems Engineering

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In recent years, cyber-physical systems (CPS) have been widely used in different problem domains.The hardware and software components in a CPS are deeply intertwined at various levels of abstraction under changing contexts to achieve the desired goals. One way to manage this complexity is through the use of modular architecture that enables portions of a CPS to be upgraded, replaced, or fixed in a plug-and-play manner. In practice, nominally modular architectures depart from this ideal. Thus, there is a need to identify, measure, and understand the causes of these departures. Techniques have been developed to accomplish this for pure software systems, but can these techniques be adapted to infer hardware-related modularity violations in a CPS? To investigate this question, we adapted methods from pure-software systems and analyzed two open-source CPS: OpenWrt and MD PnP. We found that the software architecture of these systems is well modularized. However, we were able to detect and measure modularity violations associated with hardware and other domain-related concepts. Furthermore, software components related to hardware were more likely to change frequently compared to general software components. Together, these findings suggest that it is feasible to identify a subset of hardwaredriven modularity violations using techniques adapted from pure software systems.

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Measuring architecture quality by structure plus history analysis

Cited by 34 publications

References 21 publications

A Study on the Role of Software Architecture in the Evolution and Quality of Software

A Study on the Role of Software Architecture in the Evolution and Quality of Software

Design rule spaces: a new form of architecture insight

A case study on modularity violations in cyber‐physical systems

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