在C ++中迭代地图时，SIGSEGV信号

Question

I am trying to fix this for about 5 days and no luck, every solution I tried failed.

I found some cause of the SIGSEGV below but nothing helped What is SIGSEGV run time error in C++?

Ok, here is the code. I have 2 instances, which contain some keywords-features and their scores

I want to get their eucleidian distance, which means I have to save all the keywords for each of the instances, then find the diffs for the keywords of the first one with those of the second and then find the diffs for the remaining of the second instance. What I want is while iterating the first map, to be able to delete elements from the second. The following method is called multiple times as we have two message collections, and every message from the first one is compared with every message from the second.

I have this code but it suddenly stops although I checked it is working for some seconds with multiple cout I put in some places

Note that this is for a university task so I cannot use boost and all those tricks. But I would like to know the way to bypass the problem I am into.

float KNNClassifier::distance(const Instance& inst1, const Instance& inst2) {   
map<string,unsigned> feat1;
map<string,unsigned> feat2;
for (unsigned i=0; i<inst1.getNumberOfFeatures(); i++) {
  feat1[inst1.getFeature(i)]=i;
}
for (unsigned i=0; i<inst2.getNumberOfFeatures(); i++) {
  feat2[inst2.getFeature(i)]=i;
}
float dist=0;

map<string,unsigned>::iterator it;
for (it=feat1.begin(); it!=feat1.end(); it++) {
  if (feat2.find(it->first)!=feat2.end()) {//if and only if it exists in inst2
    dist+=pow( (double) inst1.getScore(it->second) - inst2.getScore(feat2[it->first]) , 2.0);
    feat2.erase(it->first);
  }
  else {
    dist+=pow( (double) inst1.getScore(it->second) , 2.0);
  }
}

for (it=feat2.begin(); it!=feat2.end(); it++) {//for the remaining words
  dist+=pow( (double) inst2.getScore(it->second) , 2.0);
}
feat1.clear(); feat2.clear(); //ka8arizoume ta map gia thn epomenh xrhsh
return sqrt(dist);    
}

and I also tried this idea in order to not have to delete something but it suddenly stops too.

float KNNClassifier::distance(const Instance& inst1, const Instance& inst2) {
map<string,unsigned> feat1;
map<string,unsigned> feat2;
map<string,bool> exists;
for (unsigned i=0; i<inst1.getNumberOfFeatures(); i++) {
  feat1[inst1.getFeature(i)]=i;
}
for (unsigned i=0; i<inst2.getNumberOfFeatures(); i++) {
  feat2[inst2.getFeature(i)]=i;
  exists[inst2.getFeature(i)]=false;
  if (feat1.find(inst2.getFeature(i))!=feat1.end()) {
    exists[inst2.getFeature(i)]=true;
  }
}
float dist=0;
map<string,unsigned>::iterator it;
for (it=feat1.begin(); it!=feat1.end(); it++) {
  if (feat2.find(it->first)!=feat2.end()) {
    dist+=pow( (double) inst1.getScore(it->second) - inst2.getScore(feat2[it->first]) ,      2.0);
  }
  else {
    dist+=pow( (double) inst1.getScore(it->second) , 2.0);
  }
}

for (it=feat2.begin(); it!=feat2.end(); it++) {
  if(it->second==false){//if it is true, it means the diff was done in the previous iteration
    dist+=pow( (double) inst2.getScore(it->second) , 2.0);
  }
}

feat1.clear(); feat2.clear(); exists.clear();
return sqrt(dist);
}

Answer 1

The code per se seems to be OK (the error I thought I spotted earlier wasn't one). However, there may be an easier approach:

1. Instead of looking up the string from the first set in the second set, it would be possible to move through the two lists simultanously and advance the iterator to the smaller element or both iterators if they use the same string. The corresponding computation is done directly in each case.
2. I would personally use two sorted std::vector<std::pair<std::string, unsigned int> > for this but std::map<std::string, unsigned int> works as well.

I don't have access to your Instance class and, thus, haven't tested it but something like the below should work.

struct compare1st {
    bool operator()(std::pair<std::string, unsigned int> const& p1,
                    std::pair<std::string, unsigned int> const& p2) const {
        return p1.first < p2.first;
    }
};

std::vector<std::pair<std::string, unsigned int> > fill(Instance const& inst) {
    std::vector<std::pair<std::string, unsigned int> > rc;
    for (unsigned int i(0), end(inst.getNumberOfFeatures()); i != end; ++i) {
        rc.push_back(std::make_pair(inst.getFeature(i), i));
    }
    std::sort(rc.begin(), rc.end(), compare1st());
    return rc;
}
double square(double d) { // pow(d, 2.0) is fairly expensive
    return d * d;
}

float KNNClassifier::distance(const Instance& inst1, const Instance& inst2) {   
    typedef std::pair<std::string, unsigned int> Pair;
    std::vector<Pair> feat1 = fill(inst1);
    std::vector<Pair> feat2 = fill(inst2);

    std::vector<Pair>::const_iterator it1(feat1.begin()), end1(feat1.end());
    std::vector<Pair>::const_iterator it2(feat2.begin()), end2(feat2.end());
    double result(0.0);
    while (it1 != end1 && it2 != end2) {
        if (it1 != end1 && (it2 == end2 || it1->first < it2->first)) {
            result += square(inst1.getScore((it1++)->second);
        }
        else if (it2 != end2 && (it1 == end1 || it2->first < it1->first))
            result += square(inst2.getScore((it2++)->second);
        }
        else {
            result += square(inst1.getScore((it1++)->second)
                             -  inst2.getScore((it2++)->second);
        }
    }
    return sqrt(result);
}