An Empirical Study of Maintainability in Aspect-Oriented System Evolution Using Coupling Metrics

Shen, Haihao; Zhang, Sai; Zhao, Jianjun

doi:10.1109/tase.2008.17

Cited by 17 publications

(16 citation statements)

References 5 publications

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“…Earlier research on fine-grained metrics for AOP [5,20,21] has suggested that they might be more effective as indicators of certain external quality attributes, such as maintainability or fault-proneness. This assumption might hold for specific cases in the context of faultproneness.…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…However, differently from our study, they did not correlate the proposed metrics with faultproneness of the modules, but with other attributes of the programs (such as LOCC -Lines of Class Code). More recently, Shen et al [20] extended their prior work in a study that evaluates their metrics when applied to check the maintainability of evolving AO programs. Again, the target of the study was different from ours: while they evaluated the relation of a set of metrics with the maintainability of AO programs, we evaluated the relation of a set of metrics with the fault-proneness of AO programs.…”

Section: Related Workmentioning

confidence: 99%

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An empirical evaluation of coupling metrics on aspect-oriented programs

Burrows

Ferrari

Garcia

et al. 2010

Proceedings of the 2010 ICSE Workshop on Emerging Trends in Software Metrics

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Coupling metrics received increased recognition by objectoriented (OO) software developers when they were found to be indicators of important quality attributes, such as faultproneness. However, there is no consensus on which coupling metrics are effective quality indicators for emerging development paradigms, such as Aspect-Oriented Programming (AOP). AOP aims to improve software quality by providing significantly different decomposition mechanisms, such as pointcut, advice and intertype declarations. Therefore, it is not obvious if quality indicators for AOP can be derived from direct extensions of classical OO metrics. However, empirical studies of AOP do often rely on classical coupling metrics. Despite the recent adoption of AOP in industrial projects, coupling metrics have been rarely evaluated as useful indicators of fault-proneness in this context. This paper analyses the effectiveness of coupling metrics as indicators of fault-proneness in aspect-oriented (AO) systems. We collected faults from several releases of a real-world AO system. We applied and compared existing metrics for coupling and other internal attributes. We have also considered a novel metric that quantifies specific dependencies in AO software not captured by existing metrics. The results show that coupling metrics, which are not directives of object-oriented metrics, tended to be superior indicators of fault-proneness.

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Section: Analysis and Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

An empirical evaluation of coupling metrics on aspect-oriented programs

Burrows

Ferrari

Garcia

et al. 2010

Proceedings of the 2010 ICSE Workshop on Emerging Trends in Software Metrics

View full text Add to dashboard Cite

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“…Their framework includes measures of size, coupling, cohesion, and lexical SoC. Then, a number of studies (Benestad et al 2006;Greenwood et al 2007;Hoffman and Eugster 2009;Katić et al 2013;Kulesza et al 2006;Lobato et al 2008;Mguni and Ayalew 2013;Shen et al 2008) used those metrics as predictors of the maintenance effort. Unfortunately, using Sant'Anna's framework to compare evolvability between OO and AO software is problematic due to several reasons.…”

Section: Measuring Maintainability Of Ao Softwarementioning

confidence: 99%

“…The granularity of the change set differed among studies from the coarser file or module level to the finer operation or statement level. A fair balance among different granularity levels was obtained by Shen et al (2008) who adapted the approach introduced by Ryder and Tip (2001). At the core of this approach is the ability to transform source code edits into a collection of atomic changes, which captures the semantic differences between two successive releases of a program.…”

Section: Measuring Maintainability Of Ao Softwarementioning

confidence: 99%

“…Our set of atomic changes was as follows: add an empty module, delete a module, add an empty method, change body of method, delete a method, add/delete an attribute, change an attribute initializer, add an empty advice, change an advice body, delete an advice, add an empty pointcut, change a pointcut body, delete a pointcut, introduce an empty method, change an introduced method body, delete an introduced method, introduce an attribute, delete an introduced attribute, change an introduced attribute initializer, add/delete a soften exception declaration, add/delete an aspect precedence, add/delete a hierarchy declaration, change an access level modifier. This set of atomic changes was adapted from Shen et al (2008). Note that we took into account changes to access modifiers and we considered the deletion of a whole non-empty element as one atomic change.…”

Section: Variables and Hypothesesmentioning

confidence: 99%

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An empirical study on the impact of AspectJ on software evolvability

Przybyłek

2017

Empir Software Eng

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Since its inception in 1996, aspect-oriented programming (AOP) has been believed to reduce the effort required to maintain software systems by replacing cross-cutting code with aspects. However, little convincing empirical evidence exists to support this claim, while several studies suggest that AOP brings new obstacles to maintainability. This paper discusses two controlled experiments conducted to evaluate the impact of AspectJ (the most mature and popular aspect-oriented programming language) versus Java on software evolvability. We consider evolvability as the ease with which a software system can be updated to fulfill new requirements. Since a minor language was compared to the mainstream, the experiments were designed so as to anticipate that the participants were much more experienced in one of the treatments. The first experiment was performed on 35 student subjects who were asked to comprehend either Java or AspectJ implementation of the same system, and perform the corresponding comprehension tasks. Participants of both groups achieved a high rate of correct answers without a statistically significant difference between the groups. Nevertheless, the Java group significantly outperformed the AspectJ group with respect to the average completion time. In the second experiment, 24 student subjects were asked to implement (in a noninvasive way) two extension scenarios to the system that they had already known. Each subject evolved either the Java version using Java or the AspectJ version using AspectJ. We found out that a typical AspectJ programmer needs significantly fewer atomic changes to implement the change scenarios than a typical Java programmer, but we did not observe a significant difference in completion time. The overall result indicates that AspectJ has a different effect on two sub-characteristics of the evolvability: understandability and changeability. While AspectJ decreases the former, it improves one aspect of the latter.Empir Software Eng

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