Experience report: How do structural dependencies influence change propagation? An empirical study

Oliva, Gustavo Ansaldi; Gerosa, Marco Aurélio

doi:10.1109/issre.2015.7381818

Cited by 10 publications

(15 citation statements)

References 16 publications

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“…Based on their experiments they conclude "any metric which uses dependencies alone to pass judgment on the evolvability of a piece of Java software is thus unreliable". Their claim is further substantiated by the work of Ajienka and Capiluppi [1], and Oliva and Gerosa [19]. In particular, Cafeo et al [6] observed a strong correlation between co-changes and dependencies.…”

Section: Related Workmentioning

confidence: 86%

“…This motivated Gall, Hajek and Jazayeri [11], and others [7,22] to define coupling and cohesion in terms of co-change relations. Geipel and Schweitzer [12] and the subsequent work [1,6,19] shows that the nature of the interplay between static dependencies and co-changes is not completely understood although reasonably strong correlation exists between the two. Nevertheless, co-changes encompass a wide array of dependencies [6,11,12].…”

Section: Introductionmentioning

confidence: 99%

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A design structure matrix approach for measuring co-change-modularity of software products

Benkoczi

Gaur

Hossain

et al. 2018

Proceedings of the 15th International Conference on Mining Software Repositories

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Several authors have quantified the modularity of software systems in terms of coupling and cohesion metrics. Most of these approaches focus on functional and procedural dependencies in the system. Although highly relevant at the design phase, these static dependencies alone do not account for how a software product evolves over time. Instead, this is also dictated by logical and hidden dependencies between system files. To a large extent, the co-change (co-commit) relation captures these different types of dependencies. In this paper, we define two measures of co-change-modularity of a software product based on a weighted design structure matrix (DSM). The first metric, called the weighted propagation cost, uses matrix exponential to measure how changes to one system file potentially affect the whole product. The second metric, called the weighted clustering cost, uses the output of the first metric to measure the partitionability of the system based on the co-change relation. In addition, we provide a visual representation of how the co-change structure of a system evolves over time. We discuss the theoretical foundation of our work and highlight its advantages over existing methodologies. We apply our approach to GNU Octave and show the findings to be consistent with the available literature on the evolution of Octave. Our analysis is extensible and applicable to a range of scenarios including open source systems.

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Section: Related Workmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

A design structure matrix approach for measuring co-change-modularity of software products

Benkoczi

Gaur

Hossain

et al. 2018

Proceedings of the 15th International Conference on Mining Software Repositories

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…In earlier studies, co-evolution of OO software classes has been studied in relation to structural coupling [2,3,4,5] and software quality [6,7]. Some of these studies showed that most of the structurally coupled related entities in software projects do not co-evolve, and the other way round [2,4,5]. Figure 1 illustrates what has been proposed in the past, and for a smaller subset of classes: analysing the direction of the relationship between coevolution and structural coupling for 12 Linux kernel modules [3], Yu identified a linear and directional relationship between the co-evolution and structural coupling.…”

Section: Introductionmentioning

confidence: 99%

“…According to that work, structural coupling does not bring about independent evolution: if software classes are evolved independently, there will be no correlation between structural coupling and co-evolution data. In addition, according to Oliva and Gerosa [5], controlling coupling levels in practice is still challenging. One of the reasons is that the extent to which changes propagate via structural dependencies is still not clear.…”

Section: Introductionmentioning

confidence: 99%

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Understanding the interplay between the logical and structural coupling of software classes

Ajienka

Capiluppi

2017

Journal of Systems and Software

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During the lifetime of object-Oriented (OO) software systems, new classes are added to increase functionality, also increasing the inter-dependencies between classes. Logical coupling depicts the change dependencies between classes, while structural coupling measures source code dependencies induced via the system architecture. The relationship or dependency between logical and structural coupling have been debated in the past, but no large study has confirmed yet their interplay. In this study, we have analysed 79 open-source software projects of different sizes to investigate the interplay between the two types of coupling. First, we quantified the overlapping or intersection of structural and logical class dependencies. Second, we statistically computed the correlation between the strengths of logical and structural dependencies. Third, we propose a simple technique to determine the stability of OO software systems, by clustering the pairs of classes as "stable" or "unstable", based on their co-change pattern. The results from our statistical analysis show that although there is no strong evidence of a linear correlation between the strengths of the coupling types, there is substantial evidence to conclude that structurally coupled class pairs usually include logical dependencies. However, not all co-changed class pairs are also linked by structural dependencies. Finally, we identified that only a low proportion of structural coupling shows excessive instability in the studied OSS projects.

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An empirical study on the interplay between semantic coupling and co-change of software classes

2017

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Software systems continuously evolve to accommodate new features and interoperability relationships between artifacts point to increasingly relevant software change impacts. During maintenance, developers must ensure that related entities are updated to be consistent with these changes. Studies in the static change impact analysis domain have identified that a combination of source code and lexical information outperforms using each one when adopted independently. However, the extraction of lexical information and the measure of how loosely or closely related two software artifacts are, considering the semantic information embedded in their comments and identifiers has been carried out using somewhat complex information retrieval (IR) techniques. The interplay between software semantic and change relationship strengths has also not been extensively studied. This work aims to fill both gaps by comparing the effectiveness of measuring semantic coupling of OO software classes using (i) simple identifier based techniques and (ii) the word corpora of the entire classes in a software system. Afterwards, we empirically investigate the interplay between semantic and change coupling. The empirical results show that: (1) identifier based methods have more computational efficiency but cannot always be used interchangeably with corpora-based methods of computing semantic coupling of classes and (2) there is no correlation between semantic and change coupling. Furthermore we found that (3) there is a directional relationship between the two, as over 70% of the semantic dependencies are also linked by change coupling but not vice versa.

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Experience report: How do structural dependencies influence change propagation? An empirical study

Cited by 10 publications

References 16 publications

A design structure matrix approach for measuring co-change-modularity of software products

A design structure matrix approach for measuring co-change-modularity of software products

Understanding the interplay between the logical and structural coupling of software classes

An empirical study on the interplay between semantic coupling and co-change of software classes

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