CS 452/652 Spring 2022 - Lecture 8

Track/Train Measurements

• train control assignments need velocity information
  • preparatory measurements can be taken without full kernel
  • start early before the tracks fill up!
• default turnout setting - use trap loops: small (left/right), medium, large
• middle turnouts: do not set to C/C! (can lead to derailment)

Data Representation

• word length 32 bits
• no floating point!
• if necessary, use fixed-point integer instead
• if necessary, use 64-bit 'long long' integers to hold temporary results during computation

Metrics

• time
  • fastest clock: 508 kHz
  • 32 bit can represent > 2 hours ⇒ sufficient
  • small numbers: 10ms tick
• location, distance
  • millimetre granularity sufficient
  • longest short path (without reverse): ~10.5m
    ⇒ 32-bit integer sufficient
  • keep in mind: size of train, location of pickup!
• velocity
  • distance in mm; velocity in mm/s
  • distance/velocity? fraction of second → scale up / rearrange
    • example: travel time in ticks for 10ms ticks
      • distance / (velocity / 100)
      • (distance / velocity) x 100
    • compute: (distance x 100) / velocity

Speed / Velocity

Basics

• speed: train setting 0-14
• velocity: actual travel distance per time
  1. non-linear with speed
  2. different for different trains
  3. different for different parts of track?
  4. changes over time (wear and tear)
  5. two velocities per speed level 1-13 - previous lower vs. higher
• handle at least 1. and 2. by measuring and storing velocity data
  • offline experiments → start now!
  • continuous online measurements?
  • data import/export?

Sensor Measurement

• assume ~70ms continuous sensor polling loop
• unknown (hopefully constant) measurement error
  • train controller box
  • signal latency
  • etc.
• variable measurement error: sensor trigger relative to polling loop → 0-70ms
• processing delays? later... (should be small with dedicated measurement program)

Speed Measurement

• velocity = distance / (stop - start)
• constant error in 'stop' and 'start' cancels out
• maximum variable error: up to 2x 70ms = 140ms (in theory)
• at speed of 0.5m/sec, this corresponds to 7cm
• use averaging (and deviations) to deal with uncertainty
• to be revisited...

Debugging

• often ad-hoc activity - reflect on it...
• fundamentally:
  • software: model ↔ implementation
  • debugging: reconcile model and implementation
  • (your) program vs. environment (soft- and hardware)
• what's in a bug?
  • error in model?
  • incorrect implementation?

  	Model	Implementation
  Program	Design	Coding
  Environment	Interface	Internals

• potential problems
  • design: your model is incorrect
  • coding: your implementation does not realize your model
  • interface: your understanding of the environment is incorrect
  • internals: there is an unknown bug in the environment (unlikely)
• debugging helps with
  • verifying design/interface
  • verifying coding/internals
• basic technique: inspect and compare → alert
• debugging strategy
  • rule out or confirm problems
  • start with most likely problem?
  • or start with most easy to rule out?

Experiments

• debugging fundamentally uses scientific methodology
  • build model → gather data → compare
  • repeat
• no amount of experimentation can ever prove a model correct!

Tools

• tracing, logging (print)
• checking (assert)
• snapshot inspection
• interactive debugging: breakpoints, single-stepping
  • post-mortem (reset keeps most RAM): gdb or custom software
• source or binary instrumentation
• stack backtrace? see 'man backtrace' on Linux
  • not available in newlib, you could re-implement...
• execution trace: str pc, <location>