Software Defect Prediction via Attention-Based Recurrent Neural Network

Algorithm 2

Encoding ASTs’ string vectors.

Input: ASTs’ string vectors , the fixed length of each vector m;

Output: integer vectors ;

(1)

Initialize a list V, a dict and a dict ;

(2)

for do

(3)

for do

(4)

if not in tokFreq.keys then

(5)

;

(6)

end

(7)

;

(8)

end

(9)

end

(10)

Creating a list sorted in descending order of token frequency which contains tuples of each token and its corresponding frequency;

(11)

for do

(12)

;

(13)

; // establishing a dict of the ordered tokens to map them into integers

(14)

end

(15)

for do

(16)

for do

(17)

;

(18)

end

(19)

if then

(20)

Adding 0s into ;

(21)

end

(22)

else if then

(23)

for do

(24)

; // finding the index of the lowest token frequency ; // deleting the token

(25)

end

(26)

end

(27)

Adding into V;

(28)

end

(29)

return V;

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