Automatic Package Coupling and Cycle Minimization

Abdeen, Hani; Ducasse, Sté́phane; Sahraoui, Houari; Alloui, Ilham

doi:10.1109/wcre.2009.13

Cited by 74 publications

(67 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In total 10 data-sets are formed. Each data-set comprises of 6 traditional packagelevel metric described by R.C Martin [2],4 package quality metrics defined by Abdeen et al [10] for fault-proneness of packages, source code bug warnings of priority 1 identified by FindBugs and code rules violation warnings of priority 1 reported by PMD.…”

Section: Data Setsmentioning

confidence: 99%

“…Post-release fault data of subjects was obtained from public repositories, i.e., Eclipse Bug Data 9 and PROMISE 10 . For package modularization metrics, experiment study consists of 23 versions of two different open source software systems.…”

Section: Data Setsmentioning

confidence: 99%

“…Furthermore, the existing approaches of software modularization for changing the structure of package entail costly maintenance overhead, complicating its understandability and comprehension [8], [9]. Abdeen et al recently proposed a package level metrics suite which support the modularization of source code architecture using existing package structure, thus without affecting prevalent software design adversely [10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluating Dependency based Package-level Metrics for Multi-objective Maintenance Tasks

Shaikh¹,

Jalbani²,

Ansari³

et al. 2017

ijacsa

View full text Add to dashboard Cite

Abstract-Role of packages in organization and maintenance of software systems has acquired vital importance in recent research of software quality. With an advancement in modularization approaches of object oriented software, packages are widely considered as re-usable and maintainable entities of objectoriented software architectures, specially to avoid complicated dependencies and insure software design of well identified services. In this context, recently research study of H. Abdeen on automatic optimization of package dependencies provide composite frame of metrics for package quality and overall source code modularization. There is an opportunity to conduct comprehensive empirical analysis over proposed metrics for assessing their usefulness and application for fault-prediction, design flaw detection, identification of source code anomalies and architectural erosion. In this paper, we examine impact of these dependency optimization based metrics in wide spectrum of software quality for single package and entire software modularization. Our experimental work is conducted over open source software systems through statistical methodology based on cross validation fault-prediction and correlation. We conclude with empirical evidence that dependency based package modularization metrics provide more accurate view for predicting fault-prone packages and improvement of overall software structure. Thus, application of these metrics can help the developers and software practitioners to insure proactive management of the source code dependencies and avoid design flaws during software development.

show abstract

Section: Data Setsmentioning

confidence: 99%

Section: Data Setsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating Dependency based Package-level Metrics for Multi-objective Maintenance Tasks

Shaikh¹,

Jalbani²,

Ansari³

et al. 2017

ijacsa

View full text Add to dashboard Cite

show abstract

“…Mitchell and Mancoridis [Mitchell and Mancoridis 2006] use the same technique in Bunch, a tool supporting automatic system decomposition. Search-based approaches are also used in several other works [Harman et al 2002;Praditwong et al 2011;Seng et al 2005;Abdeen et al 2009]. In particular, Harman et al [Harman et al 2002] and Seng et al [Seng et al 2005] use a single-objective genetic algorithm to improve the subsystem decomposition of a software system, where the fitness function is defined using a combination of quality metrics.…”

Section: Related Workmentioning

confidence: 99%

Improving software modularization via automated analysis of latent topics and dependencies

Bavota

Gethers

Oliveto

et al. 2014

ACM Trans. Softw. Eng. Methodol.

102

View full text Add to dashboard Cite

Oftentimes, during software maintenance the original program modularization decays, thus reducing its quality. One of the main reasons for such architectural erosion is suboptimal placement of source code classes in software packages. To alleviate this issue, we propose an automated approach to help developers improve the quality of software modularization. Our approach analyzes underlying latent topics in source code as well as structural dependencies to recommend (and explain) refactoring operations aiming at moving a class to a more suitable package. The topics are acquired via Relational Topic Models (RTM), a probabilistic topic modeling technique. The resulting tool, coined as R3 (Rational Refactoring via RTM), has been evaluated in two empirical studies. The results of the first study conducted on nine software systems indicate that R3 provides a coupling reduction from 10% to 30% among the software modules. The second study with 62 developers confirms that R3 is able to provide meaningful recommendations (and explanations) for move class refactoring. Specifically, more than 70% of the recommendations were considered meaningful from a functional point of view.

show abstract

“…It should be noted that we do not oppose fingerprints to other techniques; on the contrary, we see them as complementary. For example, independently of this work and this article, we developed complementary tools to help dealing with packages such as Package Blueprints (which is based on a zoom-out visualization and ordering of internal references between packages) [DPS + 07]; Orion (which supports the prediction of change impact) [LDDK09] and a Simulated Annealing search-based technique to help maintainers find good alternative modularizations [ADSA09]. Maintainers can then use the fingerprints to compare the results, understand the alternatives, and choose the most suitable modularization.…”

Section: Hints For Code Improvements and Fingerprint Limitationsmentioning

confidence: 99%

Package Fingerprints: A visual summary of package interface usage

Abdeen

Ducasse

Pollet

et al. 2010

Information and Software Technology

Self Cite

View full text Add to dashboard Cite

Context: Object-oriented languages such as Java, Smalltalk, and C++ structure their programs using packages. Maintainers of large systems need to understand how packages relate to each other, but this task is complex because packages often have multiple clients and play different roles (class container, code ownership. . . ). Several approaches have been proposed, among which the use of cohesion and coupling metrics. Such metrics help identify candidate packages for restructuring; however, they do not help maintainers actually understand the structure and interrelationships between packages.Objectives: In this paper, we use pre-attentive processing as the basis for package visualization and see to what extent it could be used in package understanding.Method: We present the package fingerprint, a 2D visualization of the references made to and from a package. The proposed visualization offers a semantically rich, but compact and zoomable views centered on packages. We focus on two views (incoming and outgoing references) that help users understand how the package under analysis is used by the system and how it uses the system.Results: We applied these views on four large systems: Squeak, JBoss, Azureus, and ArgoUML. We obtained several interesting results, among which, the identification of a set of recurring visual patterns that help maintainers: (a) more easily identify the role of and the way a package is used within the system (e.g., the package under analysis provides a set of layered services), and, (b) detect either problematic situations (e.g., a single package that groups together a large number of basic services) or opportunities for better package restructuring (e.g., removing cyclic dependencies among packages). The visualization generally scaled well and the detection of different patterns was always possible.Conclusion: The proposed visualizations and patterns proved to be useful in understanding and maintaining the different systems we addressed. To generalize to other contexts and systems, a real user study is required.

show abstract

Automatic Package Coupling and Cycle Minimization

Cited by 74 publications

References 28 publications

Evaluating Dependency based Package-level Metrics for Multi-objective Maintenance Tasks

Evaluating Dependency based Package-level Metrics for Multi-objective Maintenance Tasks

Improving software modularization via automated analysis of latent topics and dependencies

Package Fingerprints: A visual summary of package interface usage

Contact Info

Product

Resources

About