Software maintenance is a complex process that requires the understanding and comprehension of software project details. It involves the understanding of the evolution of the software project, hundreds of software components and the relationships among software items in the form of inheritance, interface implementation, coupling and cohesion. Consequently, the aim of evolutionary visual software analytics is to support software project managers and developers during software maintenance. It takes into account the mining of evolutionary data, the subsequent analysis of the results produced by the mining process for producing evolution facts, the use of visualizations supported by interaction techniques and the active participation of users. Hence, this paper proposes an evolutionary visual software analytics tool for the exploration and comparison of project structural, interface implementation and class hierarchy data, and the correlation of structural data with metrics, as well as socio-technical relationships. Its main contribution is a tool that automatically retrieves evolutionary software facts and represent them using a scalable visualization design

García-Peñalvo, Francisco

González, Antonio

Therón, Roberto

Wermelinger, Michel

Yu, Yijun

English

Open Research Online

Open Research OnlineThe Open University’s repository of research publicationsand other research outputsMaleku: an evolutionary visual software analytics toolfor providing insights into software evolutionConference or Workshop ItemHow to cite:Gonza´lez, Antonio; Thero´n, Roberto; Garc´ıa-Pen˜alvo, Francisco; Wermelinger, Michel and Yu, Yijun (2011).Maleku: an evolutionary visual software analytics tool for providing insights into software evolution. In: 27thInternational Conference on Software Maintenance, 25-30 Sep 2011, Williamsburg VA, USA.For guidance on citations see FAQs.c© 2011 IEEEVersion: Accepted ManuscriptLink(s) to article on publisher’s website:http://www.cs.wm.edu/icsm2011/?page id=689Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyrightowners. For more information on Open Research Online’s data policy on reuse of materials please consult the policiespage.oro.open.ac.ukMaleku: an evolutionary visual software analyticstool for providing insights into software evolutionAntonio Gonza´lez-Torres, Roberto Thero´nand Francisco J. Garcı´a-Pen˜alvoDepartment of Computer SciencesUniversity of Salamanca, SpainEmail: fagtorres, theron, fgarciag@usal.esMichel Wermelinger and Yijun YuDepartment of ComputingThe Open University, UKEmail: fm.a.wermelinger, y.yug@open.ac.ukAbstract—Software maintenance is a complex process thatrequires the understanding and comprehension of softwareproject details. It involves the understanding of the evolution ofthe software project, hundreds of software components and therelationships among software items in the form of inheritance,interface implementation, coupling and cohesion. Consequently,the aim of evolutionary visual software analytics is to supportsoftware project managers and developers during software main-tenance. It takes into account the mining of evolutionary data,the subsequent analysis of the results produced by the miningprocess for producing evolution facts, the use of visualizationssupported by interaction techniques and the active participationof users. Hence, this paper proposes an evolutionary visualsoftware analytics tool for the exploration and comparison ofproject structural, interface implementation and class hierarchydata, and the correlation of structural data with metrics, aswell as socio-technical relationships. Its main contribution is atool that automatically retrieves evolutionary software facts andrepresent them using a scalable visualization design.I. INTRODUCTIONSoftware developers and managers often are faced withthe maintenance of large legacy applications and softwareprojects to which they usually do not provide support, eitherwithin their company or a client company. Consequently, theunderstanding of the evolution of such legacy applications orsoftware projects is a crucial task for software maintenance.Nevertheless, the maintenance process is usually compromiseddue to the lack of proper system documentation, which fre-quently is incomplete, outdated or it is not present [1].This research focuses on the application of evolutionaryvisual software analytics to the understanding of softwaresystems. It describes Maleku, a tool that automatically re-trieves software evolution details from software repositoriesand produces software evolution facts that are depicted usingsoftware evolution visualization techniques.Maleku uses two views: a matrix-like representation and asocial-network graph. The matrix view is a scalable and inter-active visualization for showing the correlation of structuraldata with metrics, programmer contributions, the creation ofsoftware items, socio-technical relationships, and inheritanceand interface implementation relationships.Evolutionary visual software analytics is a special appli-cation of visual analytics, and even more specifically ofvisual software analytics, to software evolution. Accordingly,evolutionary visual software analytics uses as reference thevisual analytics mantra [2], [3].The remainder of the paper is organized as follows: sectionII describes the tool architecture, while section III explainsthe designs of the visual representations used by Maleku,section IV briefly describes some scenarios when using thetool, section V briefly discuss some related works and finallysection VI presents the conclusions.II. ARCHITECTUREFigure 1 shows the architecture of Maleku. Such architec-ture is based on the evolutionary visual software analyticsprocess and it consist of five components: the knowledge ex-traction engine on a evolutionary basis, the software evolutionfacts, the data transformation engine for visualization models,the software evolution visualizations and the user itself.The knowledge extraction engine on a evolutionary basissupports the addition of modules for supporting new softwareconfiguration management systems (SCM) and allows config-uring connections to several different projects and softwarerepositories for extracting evolutionary details and carrying outsoftware evolution analysis. Its components are the monitor ofnew revisions, the source code extractor, the source code parserand the metadata and software evolution analysis engine.The monitor of new revisions is a process that continuouslymonitors the addition of new revisions to software projects andnotifies about new revisions to the source code extractor. Then,the source code extractor starts extracting source code fromthe software repository and invokes the source code parserfor collecting details about the software project structure, thehierarchy of classes, the coupling relationships and the sourcecode and metrics raw data for calculating metrics for classesand methods. Finally, the metadata and software evolutionanalysis engine takes the outcomes produced by the sourcecode parser and query additional details from the softwarerepository. Then, it applies an exhaustive software evolutionanalysis and stores the results in the software evolution factsand structure evolution database.The software evolution facts that have been taken intoaccount for the visualizations presented later are the softwareitem lifelines, the evolution metrics, the socio-technical rela-tionships and some architectural/structural relationships suchFig. 1. Evolutionary visual software analytics architecture of Malekuas inheritance, interface implementation and the correlation ofstructural data with metrics. Therefore, the data transformationengine for visualization models transforms the software evo-lution facts data structures into the appropriate data structuresthat are used by software evolution visualizations. Therefore,the visualizations included in Maleku are embedded into anEclipse plugin and make use of a matrix-like representation,a timeline and socio-technical views that are supported by asocial-network graph and the use of colors for representingprogrammer’s contributions.The knowledge extraction engine and the software evolutionfacts database are server side components with a graphical in-terface. While the data transformation engine is a middlewareprocess that is configured using a graphical interface and isexecuted automatically when it detects new additions to thesoftware evolution facts database.III. VISUAL REPRESENTATIONSA matrix-like representation has been chosen as the mainview for being a simple structure widely known by program-mers and because it allows establishing relationships amongmultivariate elements easily. The cells of the matrix representa-tion, with the packages and software items in the rows and thetime units in the columns, are used for the correlation of detailsassociated to the corresponding package or software item.Basically, the evolution details that are correlated with theproject structure are programmer contributions, the creationof software items, the addition or removal of inheritanceor interface implementation relationships and software itemmetrics.The interactions supported by the matrix view include thepossibility of zoom-in and zoom-out, the fisheye distortion,the reorder of project structure elements and the capability offiltering out nodes from the structure. In addition, it supportsyear selection from the timeline for depicting data accordingto associated months and in the socio-technical view. More-over, the user has the possibility to choose how metrics andprogrammers are represented by selecting between relative orabsolute value representations.The visual representation of the project structure is made upof all the packages and software items that have been addedto the project during its evolution. This allows to correlateall software items involved in the evolution process withprogrammers, metrics and architectural relationships such asinheritance and interface implementation relationships. Figure3(a) shows on the left side the current project structure ofjEdit in the Eclipse workbench, while on the right side isdisplayed the visual representation depicting the project andits corresponding structure, including packages and softwareitems that are no longer part of the current project version.Additionally, Figure 3(b) illustrates that source code files couldbe expanded for showing the software items they contain. Suchdesign feature allows to depict the lifeline of software itemsand packages using an intuitive approach, as shown in Figure2. The details view on the right shows that the performedactivities on the file macos.Delegate.java were carried outbetween 2003 and 2008. Moreover, those packages currentlyare not part of the latest version of the project, which iscorroborated when reviewing the project structure on theEclipse workbench, as shown in Figure 3(a). So, the lifeline ofa package or software item is determined by the representationof programmer activity in the matrix view.Another visualization key feature is the representation ofinheritance and interface implementation, which is depictedin Figure 3(c). Foldable tree nodes are used for representingsoftware item inheritance and implementation relationships.Figure 4 shows that the establishment of inheritance andinterface implementation relationships are depicted by a greenoval and its termination is represented by a red oval. Inaddition, the location of associated software items is explicitlyindicated (Java, current project or external library).Software item metrics are represented using bar chartswith the aim of highlighting changes (see Figure 5). Similarto the representation of programmer contributions, metricsare represented using relative and absolute areas. Relativerepresentation takes into consideration the software item withthe highest metric value for calculating the chart height, whilethe absolute representation only takes into consideration thehighest metric value associated to the software item.Fig. 2. Main view of the visualizationsThe other included view in the visual representation designis the socio-technical view (see Figure 2), which is subor-dinated to the matrix view. When users select a time unitin the matrix view the associated data are loaded into thesocio-technical view. Loaded data represent the socio-technicalrelationships that are derived from the modification of softwareitems. Such relationships are established from the softwareitems that programmers have modified in common. The nodesof the graph represent to programmers and their size thenumber of contributions they have been made. In addition,edges represent the relationships among programmers andtheir thickness represent the number of software items theyhave modified in common. Node colors represent programmersand are associated to the colors used in the matrix view.IV. SCENARIOSThe visual representations included in Maleku have beenintegrated into Eclipse as a plugin, shown in Figure 2.The interaction path, followed by users, starts with theselection, from a popup menu, of the view that they wantto display in the Eclipse workbench. From this point users in-teract with the visualization and the interaction path branches.So, several scenarios are possible according to maintenanceneeds. The following scenarios are some practical examplesin which Maleku visualizations could be applied.Scenario 1: A bug has been reported and the project man-ager has to assign a programmer to solve it. Once the projectmanager has analyzed who is the most suitable programmerfor solving the reported issue, the project manager realizesthat the developer in charge of the components in which theproblem is localized is on vacations. Then, the project managerfollows the next steps:1) Open the matrix view for the complete project or a givenpackage and then it opens the socio-technical view.2) Select a recent time unit, with a considerable number ofactivities, from the timeline in the matrix view.3) The socio-technical view is updated with the data asso-ciated to the selected time unit.4) The project manager selects the programmer that isin a sick leave from the socio-technical view and itsrelationships with programmers that have changed thesame highlighted software items.5) Then, the project manager determines which program-mer is the most suitable for solving the opened issue.Scenario 2: Programmers are in the middle of a softwareproject refactoring and they have to review how changesmade by other programmers affect inheritance and interfaceimplementation relationships. Programmers follow the nextsteps after opening the matrix view for the complete projector a given interesting package:1) Choose the source code file that contains the softwareitem in which the programmer is interested and expandit to review the relationships of such software item.2) Expand the software item and examine its inheritanceand interface implementation relationships to determineif changes have occurred: which relationships have beenestablished and which have been terminated.The tool and video demos are downloadable from analiti-cavisual.com/maleku.Fig. 3. Project structure and file contents. (a) Project structure representation. (b) Software items contained by a file. (c) Inheritance and interface implementationrelationships.Fig. 4. Inheritance and interface implementation relationships, including expanded years and metric values.Fig. 5. Metrics representation.V. RELATED WORKSThe use of timelines in software evolution visualization isoften linked to the representation of software project hierar-chies shown with treemaps, graphs, radial layouts and conetrees. Two related approaches to our work that have beenapplied to visualize software project hierarchies are [4] and [5].At a higher level of granularity are the evolution visualizationsof Pinzger et al. [6] and Voinea et al. [7], which scalably showthe evolution of metrics over thousands of software artifactsand hundreds of changes.VI. CONCLUSIONSThe design has taken into account several needs to be in-formed about the evolution of software projects. Some concernwhich programmers are participating in the development ofspecific part of a project, others concern when the project hastaken place and when the solution becomes stable. It also caninform the software maintainers about which programmer hascreated more revisions and new files, and how developers arecollaborating or working separated from one anotherThe tool has been tested successfully with several opensource projects in a lab environment by some expert users.The answers provided to our initial users by the proposedvisual representations has been satisfactory.VII. ACKNOWLEDGEMENTSThis work was supported by Spanish Government projectTIN2010-21695-C02-01, by the Castilla y Leo´n RegionalGovernment through GR47, by the Ministerio de Ciencia eInnovacio´n of Spain under project FI2010-16234 and also bythe Ministry of Science and Technology (MICIT) of CostaRica.REFERENCES[1] G. C. Murphy and D. Notkin, “Reengineering with reflection models: Acase study,” IEEE Computer, vol. 30, no. 8, pp. 29–36, 1997.[2] D. A. Keim, F. Mansmann, J. Schneidewind, J. Thomas, and H. Ziegler,“Visual analytics: Scope and challenges,” pp. 76–90, 2008.[3] K. Puolama¨ki, A. Bertone, R. The´ron, O. Huisman, J. Johansson,S. Miksch, P. Papapetrou, and S. Rinzivillo, Mastering the InformationAge Solving Problems with Visual Analytics. Eurographics Association,2010, ch. Data Mining, pp. 39–56.[4] B. Cornelissen, D. Holten, A. Zaidman, L. Moonen, J. J. van Wijk, andA. van Deursen, “Understanding execution traces using massive sequenceand circular bundle views,” in Proceedings of the 15th IEEE InternationalConference on Program Comprehension. Washington, DC, USA: IEEEComputer Society, 2007, pp. 49–58.[5] J. Garcı´a, A. Gonza´lez Torres, D. A. Go´mez Aguilar, R. Thero´n, and F. J.Garcı´a Pen˜alvo, “A visual analytics tool for software project structure andrelationships among classes,” in Proceedings of the 10th InternationalSymposium on Smart Graphics, ser. SG ’09. Berlin, Heidelberg:Springer-Verlag, 2009, pp. 203–212.[6] M. Pinzger, H. Gall, M. Fischer, and M. Lanza, “Visualizing multipleevolution metrics,” in Proceedings of the 2005 ACM symposium onSoftware visualization, ser. SoftVis ’05. New York, NY, USA: ACM,2005, pp. 67–75.[7] L. Voinea and A. Telea, “Cvsgrab: Mining the history of large softwareprojects,” in EUROVIS - Eurographics /IEEE VGTC Symposium onVisualization, 2006.

Maleku: an evolutionary visual software analytics tool for providing insights into software evolution

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Maleku: an evolutionary visual software analytics tool for providing insights into software evolution

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