Introduction

This page presents how Irma.struct 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 Irma.struct' 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).

Irma.struct versus LTSMin

Some statistics are displayed below, based on 278 runs (139 for Irma.struct 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 Irma.struct 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 Irma.struct computed more values than LTSMin, denote cases where Irma.struct 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.

Irma.struct wins when points are below the diagonal, LTSMin wins when points are above the diagonal.

Irma.struct versus LoLA

Some statistics are displayed below, based on 278 runs (139 for Irma.struct 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 Irma.struct 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 Irma.struct computed more values than LoLA, denote cases where Irma.struct 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.

Irma.struct wins when points are below the diagonal, LoLA wins when points are above the diagonal.

Irma.struct versus M4M.full

Some statistics are displayed below, based on 278 runs (139 for Irma.struct 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 Irma.struct 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 Irma.struct computed more values than M4M.full, denote cases where Irma.struct 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.

Irma.struct wins when points are below the diagonal, M4M.full wins when points are above the diagonal.

Irma.struct versus M4M.struct

Some statistics are displayed below, based on 278 runs (139 for Irma.struct 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 Irma.struct 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 Irma.struct computed more values than M4M.struct, denote cases where Irma.struct 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.

Irma.struct wins when points are below the diagonal, M4M.struct wins when points are above the diagonal.

Irma.struct versus ITS-Tools

Some statistics are displayed below, based on 278 runs (139 for Irma.struct and 139 for ITS-Tools, 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 Irma.struct to ITS-Tools 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 Irma.struct computed more values than ITS-Tools, denote cases where Irma.struct computed less values than ITS-Tools, 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.

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

Irma.struct versus ITS-Tools.L

Some statistics are displayed below, based on 278 runs (139 for Irma.struct 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 Irma.struct 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 Irma.struct computed more values than ITS-Tools.L, denote cases where Irma.struct 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.

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

Irma.struct versus Irma.full

Some statistics are displayed below, based on 278 runs (139 for Irma.struct 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 Irma.struct 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 Irma.struct computed more values than Irma.full, denote cases where Irma.struct 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.

Irma.struct wins when points are below the diagonal, Irma.full wins when points are above the diagonal.