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Promoting Understanding of Logical Structures of File Systems

Promoting Understanding of Logical Structures of File Systems. Dr Ian Mitchell. Motivation and Objectives. Current Research/Tools Visualisation decomposed Is Visualisation helpful Experiment Contribution Challenges Problem Linked to motivation

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Promoting Understanding of Logical Structures of File Systems

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  1. Promoting Understanding of Logical Structures of File Systems Dr Ian Mitchell

  2. Motivation and Objectives • Current Research/Tools • Visualisation decomposed • Is Visualisation helpful • Experiment • Contribution • Challenges • Problem • Linked to motivation • How to visualise the logical structure of a file system • Motivation • “Learning is motivated by interest and understanding by visualisation” A.B. Garrett • “picture worth a 1000 words” • Difficulty in understanding Logical structure of initial file system • Use existing ideas to teach File Systems? • Or do we invent new ones?

  3. Visualisation Algorithms Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  4. Visualisation Algorithms Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  5. Visualisation Algorithms – Linear Structures Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  6. Visualisation Algorithms – Search Structures Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  7. Visualisation Algorithms – Other Data Structures Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  8. Visualisation Algorithms –Sorting Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  9. Visualisation Algorithms –Search Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  10. Visualisation Algorithms –Graphs Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  11. Visualisation Algorithms –Compression Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  12. Visualisation Algorithms –Memory Management Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  13. Visualisation Algorithms –Other Algorithms Source: Shaffer et al “Algorithm Visualisation: A report on the State of the Field“,SIGCSE'07.

  14. File Systems • Dead Analysis • Important • Confirming location of file • Content of the file • The provenance of the file • Verification of the file • Discovery of Evidence • Discovery of Hidden Data • Recovery • Problem • Scalability • Complex Algorithms • Hexidecimal/Little Endianness • Abstraction tools • Programme Design • Digital Investigation • File Systems Analysis • 24 week modules in parallel?

  15. Experiment – find Cluster2 (C2) • Cohort : 21 u/g • FAT16? • FAT32 is idiosyncratic • 32 is a misnomer • 28bit cluster chain - see MS White paper on FAT • Ubiquitous – 2GB • Cluster Analysis is 16 bit • FAT8 is obsolete • FAT12 is possible but floppy drives are slow • FAT 16 has 16 bit cluster chain analysis • C2 = R + F + F + R • C2  Size – Capacity • Four Stages • Acquisition • Locating and Identifying Parameters • Extracting values • Calculating Offset

  16. Conceptual - FAT16 and 2Gbyte Memory Stick Boot FAT1 FAT2 Root Content

  17. Factual - 0-35 Bytes of FAT12/16/32 Boot Sector

  18. Example – Boot Sector Bytes per Sector: 0x200 Size of Reserved Area: 0x02 EB 3C 90 4D 53 44 4F 53 – 35 2E 30 00 02 40 02 00 02 00 02 00 00 F8 EF 00 – 3F 00 FF 00 80 1F 00 00 Size of RD Size of FAT Number of FATs: 0x02

  19. Example – Boot Sector Bytes per Sector: 0x200 Size of Reserved Area: 0x02 EB 3C 90 4D 53 44 4F 53 – 35 2E 30 00 02 40 02 00 02 00 02 00 00 F8 EF 00 – 3F 00 FF 00 80 1F 00 00 Size of RD 00x0200 Size of FAT 00x00EF Number of FATs: 0x02

  20. Boot FAT1 FAT2 Root Content 2 239 239 32 241 Sector Cluster 0 2 480 512 3,907,711 2 61,051

  21. Confirmation - TSK FILE SYSTEM INFORMATION -------------------------------------------- File System Type: FAT16 OEM Name: MSDOS5.0 Volume ID: 0x3ed4054c Volume Label (Boot Sector): NO NAME Volume Label (Root Directory): 11 FAT File System Type Label: FAT16 Sectors before file system: 8064 File System Layout (in sectors) Total Range: 0 - 3907711 * Reserved: 0 - 1 ** Boot Sector: 0 * FAT 0: 2 - 240 * FAT 1: 241 - 479 * Data Area: 480 - 3907711 ** Root Directory: 480 - 511 ** Cluster Area: 512 - 3907711 METADATA INFORMATION -------------------------------------------- Range: 2 - 62515718 Root Directory: 2 CONTENT INFORMATION -------------------------------------------- Sector Size: 512 Cluster Size: 32768 Total Cluster Range: 2 - 61051 FAT CONTENTS (in sectors) -------------------------------------------- 512-575 (64) -> EOF

  22. Confirmation – FTK Imager

  23. Is PowerPoint Pointless? • Narayanan & Hegarty • Decomposition • Static Mental Model • Referential Connections • Causal Chain of Events • Dynamic Mental Model • Nap et al • “Effective visualisation requires learner engagement” Nap et al • Graphical Representation • Adaptation • Multiple Views • Performance Information • Execution History • Flexible Control • Learner Built • Data Sets • Support Dynamic Questions • Support Dynamic Feedback • Complement Visualisations with Explanations.

  24. Results • Reflector • Weblog • Non-assessed • Open agenda, although I start with a question • Post-it notes • Completion of sheets • Coursework • 6 weeks • No generic tool; combined tools; • ALVIS was confusing • Some Students like Java Code; others like the formula; some invented their own • Reassurance

  25. Contribution & Challenges • Developing Subject with under-developed tools • Reliance on commercial or traditional CS software • Dead Analysis & New File Systems to keep up with Hardware (disk size development is double Moore’s Law). • New Subject Domain • Commercial Software Requirements • Scalability • Open Source Software Requirements • Abstraction • Hexiphobic • Complexity

  26. Bibliography Alvis. http://eecs.wsu.edu/~ veupl/soft/alvis/index.htm. Exploring the Role of Visualization and Engagement in Computer Science Education, 2003. S. Edwards C. Shaer, M. Cooper. Algorithm visualisation: A report onthe state of the eld. In SIGCSE'07, March 2007. B. Carrier. The sleuth kit. http://www.thesleuthkit.org. A. B. Garrett. Visualization: A step to understanding. J. Chem. Educ.,25 (10), 1948. N. H. Narayanan and M. Hegarty. On designing comprehensible interactive hypermedia manuals. Int. Journal of Human-Computer Studies. N. Presmeg. Research on visualization in learning and teaching mathematics.1988. D. Schrimpsher S. Hansen, N. Narayanan and M. Hegarty. Empirical studies of animation-embedded hypermedia algorithm visualisations. Technical report, Auburn University, 1998. Breakpoint Software. Hexworkshop. http://www.hexworkshop.com. FAT: General Overview of On-Disk Format. Microsoft Corporation 2000.

  27. Boot FAT1 FAT2 Root Content

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