diff --git a/src/algorithms/audioproblems/humdetector.cpp b/src/algorithms/audioproblems/humdetector.cpp
index 421455eab..c7d6fee2c 100644
--- a/src/algorithms/audioproblems/humdetector.cpp
+++ b/src/algorithms/audioproblems/humdetector.cpp
@@ -323,7 +323,7 @@ AlgorithmStatus HumDetector::process() {
     peakBins[j] = salienceBins;
     peakSaliences[j] = salienceValues;
 
-    if (not salienceBins.empty())
+    if (!salienceBins.empty())
       peakBinsNotEmpty = true;
   }
 
diff --git a/src/algorithms/machinelearning/tensorflowpredict.cpp b/src/algorithms/machinelearning/tensorflowpredict.cpp
index 5b8a02ebc..b41f5c552 100644
--- a/src/algorithms/machinelearning/tensorflowpredict.cpp
+++ b/src/algorithms/machinelearning/tensorflowpredict.cpp
@@ -72,13 +72,13 @@ void TensorflowPredict::configure() {
   _savedModel = parameter("savedModel").toString();
   _graphFilename = parameter("graphFilename").toString();
 
-  if ((_savedModel.empty()) and (_graphFilename.empty()) and (_isConfigured)) {
+  if ((_savedModel.empty()) && (_graphFilename.empty()) && (_isConfigured)) {
     E_WARNING("TensorflowPredict: You are trying to update a valid configuration with invalid parameters. "
               "If you want to update the configuration specify a valid `graphFilename` or `savedModel` parameter.");
   };
 
   // Do not do anything if we did not get a non-empty model name.
-  if ((_savedModel.empty()) and (_graphFilename.empty())) return;
+  if ((_savedModel.empty()) && (_graphFilename.empty())) return;
 
   _tags = parameter("tags").toVectorString();
 
diff --git a/src/algorithms/standard/vectorrealtotensor.cpp b/src/algorithms/standard/vectorrealtotensor.cpp
index 44b1918af..0550502a0 100644
--- a/src/algorithms/standard/vectorrealtotensor.cpp
+++ b/src/algorithms/standard/vectorrealtotensor.cpp
@@ -63,7 +63,7 @@ void VectorRealToTensor::configure() {
   _timeStamps = shape[2];
   _frame.setAcquireSize(_timeStamps);
 
-  if ((shape[0] == -1) or (shape[0] == 0)) {
+  if ((shape[0] == -1) || (shape[0] == 0)) {
     _accumulate = true;
   }
 
@@ -218,7 +218,7 @@ AlgorithmStatus VectorRealToTensor::process() {
     
     // or if we have reached the end of the stream with lastBatchModel = "push"
     // and there are not enough patches to fill a regular batch.   
-    } else if (shouldStop() and _acc.size() < _shape[0]) {
+    } else if (shouldStop() && _acc.size() < _shape[0]) {
       reshapeBatch = true;
     }
 
diff --git a/src/algorithms/tonal/key.cpp b/src/algorithms/tonal/key.cpp
index 0603b3b75..adc6797e7 100644
--- a/src/algorithms/tonal/key.cpp
+++ b/src/algorithms/tonal/key.cpp
@@ -505,7 +505,7 @@ void Key::resize(int pcpsize) {
 // just like a cross-correlation
 Real Key::correlation(const vector<Real>& v1, const Real mean1, const Real std1, const vector<Real>& v2, const Real mean2, const Real std2, const int shift) const
 {
-  if (std1 == static_cast<Real>(0.0) or std2 == static_cast<Real>(0.0))
+  if (std1 == static_cast<Real>(0.0) || std2 == static_cast<Real>(0.0))
   {
     return 0.0;
   }