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Performing Large Scale Software Engineering Studies: A Platform for Empirical Research
- 1. Performing Large Scale Software Engineering Studies Georgios Gousios
- 2. $whoami
- 3. SE = Empirical Sciecne
- 7. Observation
- 9. Models
- 13. 30 25 20 Number of Works 15 10 5 0 0 1 2 3 4 5 6 8 10 25 50 Sample sizes (number of projects)
- 14. Metric Gnome-VFS Evolution KDE SCM History 10y 9m 12y 4m 14y Num 5522 36835 >1200000 Revisions SCM Size 105 MB 1.4 GB 60 GB Num Emails 20 240 6252 (Nov 2008)
- 15. 400 300 GB 200 100 Others KDE 0 700 projects LSE (2003-2006) GenBank Dataset
- 16. RCS Postο¬x Bugzilla CVS MailMan SF.net Tracker SVN Jira Darcs Marc Gnats Git Hg
- 17. Researcherβs view Time 1. Go to project.org 2. Dowload SVN, Mail, Bug, ask for IRC logs 3. .....? 4. Publish research
- 18. Researcherβs view (some) Projectβs view Time 1. Go to project.org 1. Hm, a new visitor 2. Hey, she is mirroring our bugzilla 2. Dowload SVN, Mail, Bug, ask for IRC logs 3. .....? 3. .....? 4. Ban her! 4. Publish research
- 19. Researcherβs view (some) Projectβs view Time 1. Go to project.org 1. Hm, a new visitor 2. Hey, she is mirroring our bugzilla 2. Dowload SVN, Mail, Bug, ask for IRC logs 3. .....? 3. .....? 4. Ban her! 4. Publish research
- 20. How is empirical research done in mature disciplines?
- 22. Result Sharing
- 23. Replication
- 27. Our research: A platform for software engineering research
- 28. In our research 1. We examined the current situation 2. We propose a platform for large scale research 3. We validated its design with 2 case studies
- 29. Empirical = Model Study + Data + Metrics / Tools + Analysis Methods + Results analysis
- 30. Empirical = Model Study + Data + Metrics / Tools + Analysis Methods + Results analysis
- 31. Empirical = Model Study + Data + Metrics / Tools + Analysis Methods + Results analysis
- 32. Empirical = Model Study + Data + Metrics / Tools + Analysis Methods + Results analysis
- 33. Research methods 40 35 30 25 Number of Works 20 15 10 5 0 0 EXP FCS ECS CCS SUR Research Methods used
- 34. What sources of data are in use? 45 40 35 30 Number of Works 25 20 15 10 5 0 0 BTS SRC SF ECT SCM Data Source
- 35. What is the examined data size (in number of projects) ? 30 25 20 Number of Works 15 10 5 0 0 1 2 3 4 5 6 8 10 25 50 Sample sizes (number of projects)
- 36. Findings β’ Sample size very small β’ How can we extract generic results? β’ No experiment replication β’ Do we believe in each otherβs work or just ignore it? β’ We did not check the stats...
- 37. @ Only 20% of the tools and data reported in ICSE papers could be retrieved a year after publication
- 38. We need better empirical studies
- 39. Rigorous Evaluation Freely Available Empirical Data Tools and Results Sharing Better Empirical Studies Software Engineering Platform
- 40. A software engineering research platform
- 41. Ready made tools Formalised data formats Easily extensible A software engineering research platform Researcher Large scale Pre processed data community procesing
- 43. Alitheia Core
- 44. Platform
- 45. Platform Data
- 46. Platform Data Tools
- 47. Platform Data Tools Processing
- 49. Data Raw Data Metadata Tool Results Mailing Lists BTS SCM Processed raw data
- 50. Mirroring Root / project. Project 1 Project 2 Project 3 properties git svn mails bugs Standard Standard GIT SVN format bug<id> format .xml List 1 List 2 tmp cur new messageid.eml
- 51. Raw Data Mirroring Root / project. Project 1 Project 2 Project 3 properties git svn mails bugs Standard Standard GIT SVN format bug<id> format .xml List 1 List 2 tmp cur new messageid.eml
- 52. οοοο οοοοοοοοοο οοοοοο ο οοοοοοοοοοοοοοο οοοοοοοοο’οοοο οοο£οο¦ο ο ο οοο οοοο οοο οοοο οοοοοοοοοοοοο ο ο ο οο ο ο ο οο€οοο οοοοοοοοοο ο οοοοοοοοο₯οο ο οοοοοοο ο ο ο ο ο οοοοοοο‘ο οοοοοοοοοοοοοοοοο οοοο οοο οοοο οοοοοοοοο’οοοοοοοοοοο οοοοοοοοο οοοοοοο οο οοοο οοοοοοοοο¦οοο οοοο οοοοοοοοοο οοοοο οοοοο οοοοοοοοοο οοο οοο οοοο οοοοοοοοο οοοο¦οοο οοοοοοοοο ο οοοοοοοοοο οοοοοοοοοο οοοοοοοοοο οοοοοοοοοοοοοοοο οοοοοοοοοο οοοοοοοοοοοοο ο οοοοοοοο οοοοοοοοοοο οοοοοο£οοο οοοοοοοοο οοοοοοοοοοοο ο ο ο ο οοοοοοοοοοο οοοοοοοοοο¦ο οοοοοοοοοο¦ο ο ο οοοοοοοο‘οοοο ο ο ο ο ο ο ο ο ο οοοοοοο οοο οοοοοοοοοο ο οοοοοοοο οο‘οοοοοοοοο οοοοοοο οο οοοοοοοοοο οοο οοοο οοοοοοοο ο οοο οοοο οοοοοοο ο οοοοοοοο οοοοοοοοοο¦οοο οοοοοοο οοοο οοοοοοο¨οοοοοοο οοοο¦οοο οοοο οοοο οοο οοοοοοοοοοοοοοοο οοοοοοοοοοο οοοοοο οοοοοοοοοοοοο ο οο ο οοοοοοοο ο ο ο ο ο οο ο ο ο ο ο οοοοοοοοοοοοοοο ο ο οοοοοοοοοοοοο ο ο οοοοοοοοοο οοοοο οοοο ο ο ο ο ο ο οοοοοοοοοο οοο ο οο€οοο₯οοοοοοοοοοοοο οοοοοοο οο€οοοοοοοοοοοο οο οοοοοοο οο οοοοοοοοοοοοοοοοοοο οο οοοοοοοοοοοοοοοοοοοοοοοο οο οοοοοοοοοοοο οο‘οοοοοοοοοͺοοοοο οοοοοοοοοοοο οο‘οοοοοοοο¦ο οοοοοο οοοοοοοοο§οοοοοοοοο οοοοοοοοοοοο οοοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοο οοοοοοοοοοο οοοοοο©ο₯οοοο οοοοοοοοοοοο οοοοο οο‘οοοο οοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοοοοοο οοοοοοοοοοοο οοοοοοο οοοοοοοο οοο οοοοοοο’οοοο οοοοοο οοοοοοοοο οοοοοοοοοοοοοοοο οοοοο«οο ο ο οοοοοοο οοοοοοοοο οοοοοο οοοοο οοοοοοοο οοοοοοοοο οοοοοοο οο ο ο ο ο ο ο ο οοοοοοοοο§οοοο ο ο οοο οοοο ο ο ο ο οοοοοοοοοοοοοοο οοοοοοοοοο οο ο ο οοοοοοοοοοοοοοοοοοοοοο οο οοοοοοοοοοοοοοοο ο οοοοοοοοοοοοοοο οοοοο οο οο€οοο οοο οοοοο οοοοοοοο οοοοοοοοο οοοοοοο οοοοοοο οο οοοοο‘οοοοοοοο¦ο οοο οοοο οοο οοοο οοοοοοοοο οοοοοοοοο οοοοοοοο οοοοοο οοοοοοοοοοοοοοοο ο οοοοοοοοο οοοοοοοο§οοοο οοοοοοοο¨ο οοοο ο οοοοοο¦ο§οοοο ο ο οοοοοοοοο§οοοοοοοοοοοοο οο οοοοοοοοο‘οοοοοοοο¦ο οοοοοοοοο οοοοοοοοο οοοοοοοοοο§οοοο
- 53. Metadata οοοο οοοοοοοοοο οοοοοο ο οοοοοοοοοοοοοοο οοοοοοοοο’οοοο οοο£οο¦ο ο ο οοο οοοο οοο οοοο οοοοοοοοοοοοο ο ο ο οο ο ο ο οο€οοο οοοοοοοοοο ο οοοοοοοοο₯οο ο οοοοοοο ο ο ο ο ο οοοοοοο‘ο οοοοοοοοοοοοοοοοο οοοο οοο οοοο οοοοοοοοο’οοοοοοοοοοο οοοοοοοοο οοοοοοο οο οοοο οοοοοοοοο¦οοο οοοο οοοοοοοοοο οοοοο οοοοο οοοοοοοοοο οοο οοο οοοο οοοοοοοοο οοοο¦οοο οοοοοοοοο ο οοοοοοοοοο οοοοοοοοοο οοοοοοοοοο οοοοοοοοοοοοοοοο οοοοοοοοοο οοοοοοοοοοοοο ο οοοοοοοο οοοοοοοοοοο οοοοοο£οοο οοοοοοοοο οοοοοοοοοοοο ο ο ο ο οοοοοοοοοοο οοοοοοοοοο¦ο οοοοοοοοοο¦ο ο ο οοοοοοοο‘οοοο ο ο ο ο ο ο ο ο ο οοοοοοο οοο οοοοοοοοοο ο οοοοοοοο οο‘οοοοοοοοο οοοοοοο οο οοοοοοοοοο οοο οοοο οοοοοοοο ο οοο οοοο οοοοοοο ο οοοοοοοο οοοοοοοοοο¦οοο οοοοοοο οοοο οοοοοοο¨οοοοοοο οοοο¦οοο οοοο οοοο οοο οοοοοοοοοοοοοοοο οοοοοοοοοοο οοοοοο οοοοοοοοοοοοο ο οο ο οοοοοοοο ο ο ο ο ο οο ο ο ο ο ο οοοοοοοοοοοοοοο ο ο οοοοοοοοοοοοο ο ο οοοοοοοοοο οοοοο οοοο ο ο ο ο ο ο οοοοοοοοοο οοο ο οο€οοο₯οοοοοοοοοοοοο οοοοοοο οο€οοοοοοοοοοοο οο οοοοοοο οο οοοοοοοοοοοοοοοοοοο οο οοοοοοοοοοοοοοοοοοοοοοοο οο οοοοοοοοοοοο οο‘οοοοοοοοοͺοοοοο οοοοοοοοοοοο οο‘οοοοοοοο¦ο οοοοοο οοοοοοοοο§οοοοοοοοο οοοοοοοοοοοο οοοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοο οοοοοοοοοοο οοοοοο©ο₯οοοο οοοοοοοοοοοο οοοοο οο‘οοοο οοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοοο οοοοοοοοοοοο οοοοοοοοοοοο οοοοοοο οοοοοοοο οοο οοοοοοο’οοοο οοοοοο οοοοοοοοο οοοοοοοοοοοοοοοο οοοοο«οο ο ο οοοοοοο οοοοοοοοο οοοοοο οοοοο οοοοοοοο οοοοοοοοο οοοοοοο οο ο ο ο ο ο ο ο οοοοοοοοο§οοοο ο ο οοο οοοο ο ο ο ο οοοοοοοοοοοοοοο οοοοοοοοοο οο ο ο οοοοοοοοοοοοοοοοοοοοοο οο οοοοοοοοοοοοοοοο ο οοοοοοοοοοοοοοο οοοοο οο οο€οοο οοο οοοοο οοοοοοοο οοοοοοοοο οοοοοοο οοοοοοο οο οοοοο‘οοοοοοοο¦ο οοο οοοο οοο οοοο οοοοοοοοο οοοοοοοοο οοοοοοοο οοοοοο οοοοοοοοοοοοοοοο ο οοοοοοοοο οοοοοοοο§οοοο οοοοοοοο¨ο οοοο ο οοοοοο¦ο§οοοο ο ο οοοοοοοοο§οοοοοοοοοοοοο οο οοοοοοοοο‘οοοοοοοο¦ο οοοοοοοοο οοοοοοοοο οοοοοοοοοο§οοοο
- 54. Tools
- 55. Tools Metric Metric Plug-in Job Metadata Web Cluster Metric Plug-in Metric Logging Schedul Updater services Service Plug-in Activator er DB Messagi Web Plug-in Parser Data Security Service ng Admin Admin Servic Access e SQO-OSS SQO-OSS SQO-OSS Project 1 PV svn mails bugs PV PV List 1 List 2 PV Project Mirror tmp cur new Metadata Storage
- 56. Tools public interface AlitheiaPlugin { String getVersion(); String getAuthor(); Date getDateInstalled(); String getName(); String getDescription(); List<Result> getResultIfAlreadyCalculated(DAObject o, List<Metric> l); List<Result> getResult(DAObject o, List<Metric> l); List<Metric> getAllSupportedMetrics(); List<Metric> getSupportedMetrics(Class<? extends DAObject> activationType); void run(DAObject o); boolean update(); boolean install(); boolean remove(); boolean cleanup(DAObject sp); String getUniqueKey(); Set<Class<? extends DAObject>> getActivationTypes(); List<Class<? extends DAObject>> getMetricActivationTypes (Metric m); Set<PluginConfiguration> getConfigurationSchema(); Set<String> getDependencies(); Map<MetricType.Type, SortedSet<Long>> getObjectIdsToSync(StoredProject sp, Metric m); }
- 57. Tools public interface AlitheiaPlugin { String getVersion(); String getAuthor(); Date getDateInstalled(); String getName(); String getDescription(); List<Result> getResultIfAlreadyCalculated(DAObject o, List<Metric> l); List<Result> getResult(DAObject o, List<Metric> l); List<Metric> getAllSupportedMetrics(); List<Metric> getSupportedMetrics(Class<? extends DAObject> activationType); void run(DAObject o); boolean update(); boolean install(); boolean remove(); boolean cleanup(DAObject sp); String getUniqueKey(); Set<Class<? extends DAObject>> getActivationTypes(); List<Class<? extends DAObject>> getMetricActivationTypes (Metric m); Set<PluginConfiguration> getConfigurationSchema(); Set<String> getDependencies(); Map<MetricType.Type, SortedSet<Long>> getObjectIdsToSync(StoredProject sp, Metric m); }
- 58. Tools @MetricDeclarations(metrics = { @MetricDecl(mnemonic="MNOF", activators={ProjectDirectory.class}, descr="Number of Source Code Files in Module"), @MetricDecl(mnemonic="MNOL", activators={ProjectDirectory.class}, descr="Number of lines in module", dependencies={"Wc.loc"}), @MetricDecl(mnemonic="AMS", activators={ProjectVersion.class}, descr="Average Module Size"), @MetricDecl(mnemonic="ISSRCMOD", activators={ProjectDirectory.class}, descr="Mark for modules containing source files") }) public class ModuleMetricsImplementation extends AbstractMetric { public void run(ProjectFile pf) throws AlreadyProcessingException {[...]} public void run(ProjectVersion pv) throws AlreadyProcessingException {[...]} public List<Result> getResult(ProjectFile pf, Metric m) { return getResult(pf, ProjectFileMeasurement.class, m, Result.ResultType.INTEGER); } public List<Result> getResult(ProjectVersion pv, Metric m) { return getResult(pv, ProjectVersionMeasurement.class, m, Result.ResultType.FLOAT); } }
- 59. public void run(ProjectFile pf) { // We do not support directories Tools if (pf.getIsDirectory()) { return; } InputStream in = fds.getFileContents(pf); if (in == null) { return; } // Create an input stream from the project file's content try { // Measure the number of lines in the project file LineNumberReader lnr = new LineNumberReader(new InputStreamReader(in)); int lines = 0; while (lnr.readLine() != null) { lines++; } lnr.close(); // Store the results Metric metric = Metric.getMetricByMnemonic("LOC"); ProjectFileMeasurement locm = new ProjectFileMeasurement(); locm.setMetric(metric); locm.setProjectFile(pf); locm.setWhenRun(new Timestamp(System.currentTimeMillis())); locm.setResult(String.valueOf(lines)); db.addRecord(locm); markEvaluation(metric, pf.getProjectVersion().getProject()); } catch (IOException e) { log.error(this.getClass().getName() + " IO Error <" + e + "> while measuring: " + pf.getFileName()); } }
- 60. Processing - The scmmap algorithm CPU
- 61. Processing - the idmap algorithm CPU
- 62. Processing - in clusters
- 63. Line counting speed 60 45 Minutes 30 15 0 Naive implementation Alitheia Core
- 64. New cluster node connects
- 65. Case Studies
- 66. Do intense conversations affect short-term project development?
- 67. How do we identify intense discussions 100000 120000 Number of messages Levels of thread depth 90000 100000 80000 70000 80000 60000 Occurences Occurences 50000 60000 40000 40000 30000 20000 20000 10000 0 0 0 5 10 15 20 25 0 5 10 15 20 25 Number of messages per thread Thread depth
- 68. Hypotheses β’ H1: Number of messages and thread depth are dependent variables β’ H2: We can identify intense discussions by identifying threads in top depth and msg/ thread quartiles β’ H3: Intense discussions affect the repositoryβs source line intake
- 69. Method β’ Import projects in Alitheia Core β’ Develop metric plug-in to count the variables we are interested in β’ 3 metrics β’ Emails from 60 projects, ~1,2 * 10^6 emails, 679427 threads β’ Plug-in loc: 270 lines
- 70. 100 Fit function (0.55 + 1.59x) 80 Number of Messages 60 40 20 0 0 5 10 15 20 25 30 35 40 45 50 Thread depth H1: R^2 = 0.70
- 71. 100 Fit function (0.55 + 1.59x) 80 Number of Messages 60 40 20 0 0 5 10 15 20 25 30 35 40 45 50 Thread depth H1: R^2 = 0.70
- 72. β’ H2: 99 discussion threads β’ H3 3: Project Avogadro ΞotEffect 622 Deskbar-Applet -103 FreeBSD -34 Gnome-Network -106 Gnome-Utils -263 GTK+ 183 Sabayon -244 Vala -356 LSR 1150 Meld 27
- 73. β’ H2: 99 discussion threads β’ H3 3: Project Avogadro ΞotEffect 622 Deskbar-Applet -103 FreeBSD -34 Gnome-Network -106 Gnome-Utils -263 GTK+ 183 Sabayon -244 Vala -356 LSR 1150 Meld 27
- 74. β’ H2: 99 discussion threads β’ H3 3: Project Avogadro ΞotEffect 622 Deskbar-Applet -103 FreeBSD -34 Gnome-Network -106 Gnome-Utils -263 GTK+ 183 Sabayon -244 Vala -356 LSR 1150 Meld 27
- 75. Does the number of programmers affect code maintainability?
- 76. Hypotheses β’ H1: Number of programmers affects code maintainability at the project level β’ H2: Number of programmers affects code maintainability at the directory level.
- 77. Method β’ Per langauge β’ C & Java (risky) β’ Plug-ins that calculate β’ Number of developers per period of time β’ Halstead & McCabe (700 lines) β’ Omarβs Maintainability Index (240 lines) β’ Data from 213 projects
- 78. Maintainability at the project level R^2 = 0.04
- 79. Maintainability at the project level R^2 = 0.04
- 80. Maintainability at the module level R^2 = 0.05
- 81. Maintainability at the module level R^2 = 0.05
- 82. Per language C: R^2 = 0.08 Java: R^2 = 0.07
- 83. Per language C: R^2 = 0.08 Java: R^2 = 0.07
- 84. Why do we need large scale research?
- 85. Project ΞotEffect Banshee -1121 Deskbar-Applet -103 FreeBSD -34 Gnome-Power-Manager -773 Gnome-Utils -263 GTranslator -230 Sabayon -244 Vala -356
- 86. 1 R2 0.9 0.8 0.7 Correlation Co-efficient 0.6 0.5 0.4 0.3 0.2 0.1 0 R^2 at the module level for all projects
- 87. TODO
- 88. Replication of published studies
- 89. Platform Data validation
- 90. Repositories for tools, data and results
- 91. The SoftEng cloud project
- 92. Thank you! http://www.sqo-oss.org Georgios Gousios gousiosg@aueb.gr
Editor's Notes
- \n
- \n
- Software engineering and is an empirical science as it tries to explain phenomena that occur in software development using data that are a result of it.\n
- This statement is not mine but belongs to Vic Basilli and other people that said or implied it before him or worked with him or followed his recommendation and started a new and exciting research area, the MSR. So being an empirical science software engineering has to follow the steps of scientific method\n
- This statement is not mine but belongs to Vic Basilli and other people that said or implied it before him or worked with him or followed his recommendation and started a new and exciting research area, the MSR. So being an empirical science software engineering has to follow the steps of scientific method\n
- As required by the scientific method we observe the behaviour or the data...\n
- We formulate hypotheses...\n
- And we build models ....\n
- Validate or invalidate those hypotheses by running them against data from the real world. As an empirical science, we are in constant need for data\n
- While in other empirical fields it is difficult and expensive to get empirical data, for example consider medicine,\n in software engineering we have the OSS movement which produces vast quantities \nso the question that comes into mind is &#x201C;can we use all that free data to do research with?&#x201D;\n
- This may sound like a rhetorical question, but data shows that it is not. \n
- From a systematic review we have done, most software engineering papers (even those in good journals and conferences) are validating their hypotheses with data from just a couple of projects\n
- Trying to explain why, let&#x2019;s have a look at some project numbers first. The largest project repository than one can work with is KDE at ~50GB of data. In a talk, Audris Mockus said that he collected more than 1TB of data\n
- If we compare to other empirical sciences \n
- The other great problem is that of original data disparity. Most research so far was done with CVS and Bugzilla. In reality, there are a lot of tools that store process data \n
- Then there is the problem of non co-operating projects, which is OK because running and maintaining the infrastructures researchers almost never give back to the community\n
- Then there is the problem of non co-operating projects, which is OK because running and maintaining the infrastructures researchers almost never give back to the community\n
- Then there is the problem of non co-operating projects, which is OK because running and maintaining the infrastructures researchers almost never give back to the community\n
- So let&#x2019;s see how is research done in more mature discilines\n
- The have large data sets that are pre-processed. Researchers most of the time do not have to download new data and massage them before starting conducting experimets. the Flossmole project has shown the way\n
- Researchers share their results in the form of workshops and conferences, competitions and more significantly tools that produce them\n
- They also do not take forgranted everything published as they replicate the studies and the findings. We can give the example of medicine here.\n
- And most important of all, most other empirical research disciplines have research platforms. Shared tools that permit researchers to conduct research using standardised input and output formats on standardized datasets.\n
- But most of them are already using machines like this (and get funding) to do their experiments on shared research infrastructures\n
- Or request huge amounts of funding for building machines like this\n
- \n
- \n
- By reading more than 300 papers and conducting a systematic review of more than 70 randomly selected\n
- By reading more than 300 papers and conducting a systematic review of more than 70 randomly selected\n
- By reading more than 300 papers and conducting a systematic review of more than 70 randomly selected\n
- By reading more than 300 papers and conducting a systematic review of more than 70 randomly selected\n
- By reading more than 300 papers and conducting a systematic review of more than 70 randomly selected\n
- \n
- \n
- \n
- \n
- Our results are reinforced by a similar study that Carlo Gezzi did for his ICSE 2009 keynote\n
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- &#x397; &#x3C0;&#x3C1;&#x3CC;&#x3C4;&#x3B1;&#x3C3;&#x3AE; &#x3BC;&#x3B1;&#x3C2; &#x3B3;&#x3B9;&#x3B1; &#x3BA;&#x3B1;&#x3BB;&#x3CD;&#x3C4;&#x3B5;&#x3C1;&#x3B5;&#x3C2; &#x3B5;&#x3BC;&#x3C0;&#x3B5;&#x3B9;&#x3C1;&#x3B9;&#x3BA;&#x3AD;&#x3C2; &#x3BC;&#x3B5;&#x3BB;&#x3AD;&#x3C4;&#x3B5;&#x3C2; &#x3B5;&#x3AF;&#x3BD;&#x3B1;&#x3B9; &#x3B2;&#x3B1;&#x3C3;&#x3B9;&#x3C3;&#x3BC;&#x3AD;&#x3BD;&#x3B7; &#x3C3;&#x3B5; 4 &#x3B1;&#x3C1;&#x3C7;&#x3AD;&#x3C2;:\n-&#x395;&#x3BD;&#x3C4;&#x3B1;&#x3C4;&#x3B9;&#x3BA;&#x3AE; &#x3B5;&#x3C0;&#x3B1;&#x3BB;&#x3AE;&#x3B8;&#x3B5;&#x3C5;&#x3C3;&#x3B7; &#x3C4;&#x3C9;&#x3BD; &#x3B9;&#x3B4;&#x3B5;&#x3CE;&#x3BD;\n-&#x395;&#x3BB;&#x3B5;&#x3CD;&#x3B8;&#x3B5;&#x3C1;&#x3B1; &#x3B4;&#x3B9;&#x3B1;&#x3B8;&#x3AD;&#x3C3;&#x3B9;&#x3BC;&#x3B1; &#x3B4;&#x3B5;&#x3B4;&#x3BF;&#x3BC;&#x3AD;&#x3BD;&#x3B1; &#x3C0;&#x3B5;&#x3B9;&#x3C1;&#x3B1;&#x3BC;&#x3B1;&#x3C4;&#x3B9;&#x3C3;&#x3BC;&#x3BF;&#x3CD;\n-&#x394;&#x3B9;&#x3B5;&#x3C5;&#x3BA;&#x3CC;&#x3BB;&#x3C5;&#x3BD;&#x3C3;&#x3B7; &#x3C4;&#x3B7;&#x3C2; &#x3B4;&#x3B9;&#x3B1;&#x3BA;&#x3AF;&#x3BD;&#x3B7;&#x3C3;&#x3B7;&#x3C2; &#x3B1;&#x3C0;&#x3BF;&#x3C4;&#x3B5;&#x3BB;&#x3B5;&#x3C3;&#x3BC;&#x3AC;&#x3C4;&#x3C9;&#x3BD; &#x3BA;&#x3B1;&#x3B9; &#x3B5;&#x3C1;&#x3B3;&#x3B1;&#x3BB;&#x3B5;&#x3AF;&#x3C9;&#x3BD;\n
- By saying the work platform, several requirements appear in front of us\n
- By saying the work platform, several requirements appear in front of us\n
- By saying the work platform, several requirements appear in front of us\n
- By saying the work platform, several requirements appear in front of us\n
- By saying the work platform, several requirements appear in front of us\n
- By saying the work platform, several requirements appear in front of us\n
- All those reasons led our research group to the SQO-OSS project, which produced the Alitheia Core tool. The project&#x2019;s aim was to produce software quality analysis tools, but the original targets strayed towards creating infrastructures rather than the tools themselves\n
- All those reasons led our research group to the SQO-OSS project, which produced the Alitheia Core tool. The project&#x2019;s aim was to produce software quality analysis tools, but the original targets strayed towards creating infrastructures rather than the tools themselves\n
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- This is the interface each plugin metric must satisfy\n
- This is how a metric plug-in looks like\n
- This is the implementation of the line counting plug-in I &#x2018;ve presented you earlier on, minus some bureaucracy (constructors, imports etc). Just about 20 Locs to retrieve a file from a revision, read its lines and store results in a database. This is comparable to a shell or python script, but it is way much faster. The abstractions Alitheia Core are very high level and cross platform and this is why the overhead it adds in algorithm implementation is minimal\n
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- This is our cluster: Left a 3 thread processing node + project server, middle a 6 thread processing core, bottom mirroring and storage of raw data, file server, database and 8 processing threads to keep the CPUs busy while I/O, right web server + 16 slow processing threads. To scale, we just need more processing nodes.\n
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- Another example of the cluster on its knees - Linear scalability display: The screen of the database server running just the database while other nodes start connecting: Queries Per Second increase is almost linear and load equals to processor cores -> the machine is saturated. \n
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- &#x3A4;&#x3B1; &#x3AF;&#x3B4;&#x3B9;&#x3B1; &#x3B1;&#x3C0;&#x3BF;&#x3C4;&#x3B5;&#x3BB;&#x3AD;&#x3C3;&#x3BC;&#x3B1;&#x3C4;&#x3B1;\n
- Now the interesting bit\n
- Selected results from the first case study\n
- Now imagine that I wanted to publish a paper or to present results to get money from a grant what would I do?\n
- I hope I &#x2018;ve persuaded you about the usefulness of such studies, let see what we have to do from now on\n
- Having such a huge data base I think that we can refute several existing works :-)\n
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