1 / 32

Source code analysis with Columbus

Source code analysis with Columbus. Quality assessment Architecture reconstruction. Árpád Beszéde s Department of Software Engineering , University of Szeged , Hungary. Who we are. One of the leading SE research groups in Hungary http://www.inf.u-szeged.hu/sed/ Competences

alaire
Download Presentation

Source code analysis with Columbus

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Source code analysis with Columbus Quality assessment Architecture reconstruction Árpád Beszédes Department of Software Engineering, University of Szeged, Hungary

  2. Who we are • One of the leading SE research groups in Hungary • http://www.inf.u-szeged.hu/sed/ • Competences • Software quality • Software testing • Embedded systems • Networks • Open Source • .NET • Java Scalable Program Analysis - Dagstuhl Seminar

  3. Place of source code analysis Software maintenance / evolution of large systems Processes (e.g. issue m) Source code quality Monitor Test management IT operation performance Architecture Scalable Program Analysis - Dagstuhl Seminar

  4. References • Telecom, financial, other • Analyzed systems (1-30 MLOC) • Graphisoft ArchiCAD • Nuance-Scansoft Recognita • evoSoft • Erste Bank • Nokia S60 platform • Mozilla Firefox & Thunderbird • SUN, OpenOffice.org • Eclipse • NASA WorldWind • Etc. Scalable Program Analysis - Dagstuhl Seminar

  5. Source code-based QA methodology architecture Continuous measurement and monitoring is needed! Scalable Program Analysis - Dagstuhl Seminar

  6. Quality decrease of sw systems from: Roger Pressman - Software Engineering Software Engineering: A Practitioner's Approach, McGraw-Hill Scalable Program Analysis - Dagstuhl Seminar

  7. Columbus technology • Analysis of large sw systems • In the scope of regular maintenance • C/C++/C#/Java/SQL • Quality measurements, auditing • Reverse Engineering, architecture reconstruction • One-shot assessment • Continuous monitoring Scalable Program Analysis - Dagstuhl Seminar

  8. Some history • 1998-2001: Nokia Research Center • FrontEndART Software Ltd. • Further development • Industrial projects • Grants • 50-100 man-years Scalable Program Analysis - Dagstuhl Seminar

  9. Main components • Robust source code parsers • Analysis methodologies • Representation metamodels designed for maintenance tasks (language schemas) • Programming interfaces (API) • Extensions: CFG, call graph, DU, support for dynamic analysis (testing), etc. • Back ends • Code measurement • Reverse engineering • Standalone or SDK integration, command-line, API • SourceAudit, SourceDoc (previously Columbus/CAN) • Monitoring subsystem: SourceInventory (was Monitor) Scalable Program Analysis - Dagstuhl Seminar

  10. Reverse Engineering • SourceDoc tool • Creation of UML logical views of the analyzed system • Class diagrams • In standard XMI format • can be loaded e.g. into Rational Rose • Automatic generation of HTML documentation • Class-level • Hyperlinked • Design pattern usage detection • Detecting architecture-level dependencies • “Superlinking” • Among physical components (e.g. exe, dll) • E.g. function calls, includes Scalable Program Analysis - Dagstuhl Seminar

  11. “Bad smell” detection • SourceAudit tool • Finds code fragments that • might be problematic • and error-prone, • so it needs refactoring • e.g.: Feature Envy: a function which does not use its own class, but relies on others Scalable Program Analysis - Dagstuhl Seminar

  12. Clone detection • Finds duplicated code fragments (copy/paste, clones) • Clones can cause many hard-to-find bugs • The detection can be scaled • from exact match • to similar code fragments • Uses efficient flat-tree based recognition • Language independent Scalable Program Analysis - Dagstuhl Seminar

  13. Code checking • Checking conformance to coding rules • Some of them indicate bugs • The rules • check the coding style • extend the warning capabilities of the compiler • check typical implementation errors • new rules can be added easily (C++ API) • General good practice rules • Company specific rules • Integration of other checkers’ results • Integration with MS Visual Studio and Eclipse • Command-line operation Scalable Program Analysis - Dagstuhl Seminar

  14. Code measurement – metrics • All popular metrics for procedural, OO, SQL languages • CK, size, complexity, coupling, cohesion, OO-ness, etc. • Interpretation of metrics? • E.g. different types of cyclomatic complexity • The metrics-based fault predictor model selects C++ classes that are liable to errors1 • successfully tested on Mozilla [1] Gyimóthy T, Ferenc R and Siket I. Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction. IEEE TSE vol.31, no.10, October 2005 Scalable Program Analysis - Dagstuhl Seminar

  15. Connectivity to other tools • ART (RSF) • {CPP|J|CS}ML (XML) • FAMIX XMI • GXL • Maisa (Prolog) • RSF • UML XMI • VCG • Machine readable CSV • Human readable txt Scalable Program Analysis - Dagstuhl Seminar

  16. Technical details • Own and commercial front ends • Analysis of complex systems: • Compiler wrapping technology • Standard schemas • OO-style • C++ API • High-level language independent model • Cross-module dependencies: superlinking Scalable Program Analysis - Dagstuhl Seminar

  17. Scalability? • Limited low-level analyses • Lightweight? • Problems of other kind • Common high-level model • Relatively easy system integration • Anything else you wanted to know? Scalable Program Analysis - Dagstuhl Seminar

  18. Monitoring subsystem • SourceInventory • The source code of the system is • downloaded automatically by the framework from a configuration management system (e.g. CVS) • analyzed, and the results are stored in a database • queries can be run and diagrams can be drawn from a web-based interface, which communicates with the database Scalable Program Analysis - Dagstuhl Seminar

  19. Monitoring subsystem (cont.) • Automatic alerts can be issued when indicators overrun critical thresholds • metric baselines • Internally: quality assessment • Customer: continuous measurement • Public databases: Mozilla, maemo, (OpenOffice, Eclipse) Scalable Program Analysis - Dagstuhl Seminar

  20. Screenshots (1) Scalable Program Analysis - Dagstuhl Seminar

  21. Screenshots (2) Scalable Program Analysis - Dagstuhl Seminar

  22. Screenshots (3) Scalable Program Analysis - Dagstuhl Seminar

  23. Screenshots (4) Scalable Program Analysis - Dagstuhl Seminar

  24. Screenshots (5) Scalable Program Analysis - Dagstuhl Seminar

  25. Screenshots (6) Scalable Program Analysis - Dagstuhl Seminar

  26. Screenshots (7) Scalable Program Analysis - Dagstuhl Seminar

  27. Screenshots (8) Scalable Program Analysis - Dagstuhl Seminar

  28. Screenshots (9) Scalable Program Analysis - Dagstuhl Seminar

  29. Nokia R&D projects • History • 1998 – TED projects: C++ to UML • 2005 – ART projects: Symbian platform • Architecture reconstruction of Symbian platform • Identification of “architectural erosion” • Quality measurement of Symbian platform • Metrics • Official Symbian coding guidelines (SourceAudit) • Quality measurement of maemo platform Scalable Program Analysis - Dagstuhl Seminar

  30. Technology extensions – 1 • SourceAudit coding rules (114) • general 'good practice' C++ coding rules • Symbian OS-specific rules • Nokia recommended rules • viability – the code will not work • reliability – the code may not work • maintainability – the code may be difficult to modify • readability – the code may be difficult to understand • reusability – the code may be less usable in conjunction with other code • convention – the code will be unconventional Scalable Program Analysis - Dagstuhl Seminar

  31. Technology extensions – 2 • Architecture cross-component dependencies • call: inter-component function calls • include: the same header file is included by two components • resource: the consumer’s serviceClass attribute equals to the provider’s interface_uid, the consumer’s contentType attribute equals to provider's default data item, and consumer's serviceCmd attribute equals to provider's opaque_data • publish & subscribe: if a component sets a property (category and key), and an other subscribes for this property then there is a P&S dependency between the two components • Dependency metrics, e.g. xCallIn, xCallOut, xInclude • Visualization Scalable Program Analysis - Dagstuhl Seminar

  32. Technology extensions – 3 • Build process (Symbian SDK) wrapping • Hides the original compiler with wrapper programs (e.g. gcc.exe) • After activating the SDKWrapper the project can be built as usual • creating abld.bat by ‘bldmake bldfiles’ and • building the project by ‘abld build …’ • Build scripts provided for linking and inter-component dependency computation • Difficulties: compiling resource files, excluding test components Scalable Program Analysis - Dagstuhl Seminar

More Related