Introduction

This page presents how ITS-Tools do cope efficiently with the LTLFireability examination face to the other participating tools. In this page, we consider «Surprise» models.

The next sections will show chart comparing performances in terms of both memory and execution time.The x-axis corresponds to the challenging tool where the y-axes represents ITS-Tools' performances. Thus, points below the diagonal of a chart denote comparisons favorables to the tool while others corresponds to situations where the challenging tool performs better.

You might also find plots out of the range that denote the case were at least one tool could not answer appropriately (error, time-out, could not compute or did not competed).

ITS-Tools versus LTSMin

Some statistics are displayed below, based on 278 runs (139 for ITS-Tools and 139 for LTSMin, so there are 139 plots on each of the two charts). Each execution was allowed 1 hour and 16 GByte of memory. Then performance charts comparing ITS-Tools to LTSMin are shown (you may click on one graph to enlarge it).

On the chart below, denote cases where the two tools did computed all results without error, denote cases where the two tool did computed the same number of values (but not al values in the examination), denote cases where ITS-Tools computed more values than LTSMin, denote cases where ITS-Tools computed less values than LTSMin, denote the cases where at least one tool did not competed, denote the cases where at least one tool computed a bad value and denote the cases where at least one tool stated it could not compute a result or timed-out.

ITS-Tools wins when points are below the diagonal, LTSMin wins when points are above the diagonal.

ITS-Tools versus LoLA

Some statistics are displayed below, based on 278 runs (139 for ITS-Tools and 139 for LoLA, so there are 139 plots on each of the two charts). Each execution was allowed 1 hour and 16 GByte of memory. Then performance charts comparing ITS-Tools to LoLA are shown (you may click on one graph to enlarge it).

On the chart below, denote cases where the two tools did computed all results without error, denote cases where the two tool did computed the same number of values (but not al values in the examination), denote cases where ITS-Tools computed more values than LoLA, denote cases where ITS-Tools computed less values than LoLA, denote the cases where at least one tool did not competed, denote the cases where at least one tool computed a bad value and denote the cases where at least one tool stated it could not compute a result or timed-out.

ITS-Tools wins when points are below the diagonal, LoLA wins when points are above the diagonal.

ITS-Tools versus M4M.full

Some statistics are displayed below, based on 278 runs (139 for ITS-Tools and 139 for M4M.full, so there are 139 plots on each of the two charts). Each execution was allowed 1 hour and 16 GByte of memory. Then performance charts comparing ITS-Tools to M4M.full are shown (you may click on one graph to enlarge it).

On the chart below, denote cases where the two tools did computed all results without error, denote cases where the two tool did computed the same number of values (but not al values in the examination), denote cases where ITS-Tools computed more values than M4M.full, denote cases where ITS-Tools computed less values than M4M.full, denote the cases where at least one tool did not competed, denote the cases where at least one tool computed a bad value and denote the cases where at least one tool stated it could not compute a result or timed-out.

ITS-Tools wins when points are below the diagonal, M4M.full wins when points are above the diagonal.

ITS-Tools versus M4M.struct

Some statistics are displayed below, based on 278 runs (139 for ITS-Tools and 139 for M4M.struct, so there are 139 plots on each of the two charts). Each execution was allowed 1 hour and 16 GByte of memory. Then performance charts comparing ITS-Tools to M4M.struct are shown (you may click on one graph to enlarge it).

On the chart below, denote cases where the two tools did computed all results without error, denote cases where the two tool did computed the same number of values (but not al values in the examination), denote cases where ITS-Tools computed more values than M4M.struct, denote cases where ITS-Tools computed less values than M4M.struct, denote the cases where at least one tool did not competed, denote the cases where at least one tool computed a bad value and denote the cases where at least one tool stated it could not compute a result or timed-out.

ITS-Tools wins when points are below the diagonal, M4M.struct wins when points are above the diagonal.

ITS-Tools versus ITS-Tools.L

Some statistics are displayed below, based on 278 runs (139 for ITS-Tools and 139 for ITS-Tools.L, so there are 139 plots on each of the two charts). Each execution was allowed 1 hour and 16 GByte of memory. Then performance charts comparing ITS-Tools to ITS-Tools.L are shown (you may click on one graph to enlarge it).

On the chart below, denote cases where the two tools did computed all results without error, denote cases where the two tool did computed the same number of values (but not al values in the examination), denote cases where ITS-Tools computed more values than ITS-Tools.L, denote cases where ITS-Tools computed less values than ITS-Tools.L, denote the cases where at least one tool did not competed, denote the cases where at least one tool computed a bad value and denote the cases where at least one tool stated it could not compute a result or timed-out.

ITS-Tools wins when points are below the diagonal, ITS-Tools.L wins when points are above the diagonal.

ITS-Tools versus Irma.full

Some statistics are displayed below, based on 278 runs (139 for ITS-Tools and 139 for Irma.full, so there are 139 plots on each of the two charts). Each execution was allowed 1 hour and 16 GByte of memory. Then performance charts comparing ITS-Tools to Irma.full are shown (you may click on one graph to enlarge it).

On the chart below, denote cases where the two tools did computed all results without error, denote cases where the two tool did computed the same number of values (but not al values in the examination), denote cases where ITS-Tools computed more values than Irma.full, denote cases where ITS-Tools computed less values than Irma.full, denote the cases where at least one tool did not competed, denote the cases where at least one tool computed a bad value and denote the cases where at least one tool stated it could not compute a result or timed-out.

ITS-Tools wins when points are below the diagonal, Irma.full wins when points are above the diagonal.

ITS-Tools versus Irma.struct

Some statistics are displayed below, based on 278 runs (139 for ITS-Tools and 139 for Irma.struct, so there are 139 plots on each of the two charts). Each execution was allowed 1 hour and 16 GByte of memory. Then performance charts comparing ITS-Tools to Irma.struct are shown (you may click on one graph to enlarge it).

On the chart below, denote cases where the two tools did computed all results without error, denote cases where the two tool did computed the same number of values (but not al values in the examination), denote cases where ITS-Tools computed more values than Irma.struct, denote cases where ITS-Tools computed less values than Irma.struct, denote the cases where at least one tool did not competed, denote the cases where at least one tool computed a bad value and denote the cases where at least one tool stated it could not compute a result or timed-out.

ITS-Tools wins when points are below the diagonal, Irma.struct wins when points are above the diagonal.