Open AccessApproach to mine influential functions based on software execution sequence
Author(s) -
Zhang Bing,
Huang Guoyan,
He Haitao,
Ren Jiadong
Publication year - 2017
Publication title -
iet software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.305
H-Index - 43
eISSN - 1751-8814
pISSN - 1751-8806
DOI - 10.1049/iet-sen.2016.0081
Subject(s) - computer science , software , trace (psycholinguistics) , rank (graph theory) , software development , process (computing) , software bug , software system , software construction , data mining , software sizing , software engineering , programming language , philosophy , linguistics , mathematics , combinatorics
In software system, there are some functions of great importance in controlling the whole process of software execution. When they are damaged, the software will suffer from catastrophic consequences caused by cascading failures. To accurately identify and protect these influential functions has become a necessary method in software security. Thus, in this study a new approach to efficiently mine influential functions based on software execution sequence is proposed. First, the authors design a novel modelling strategy by which software execution traces are modelled as sequential patterns. Owing to loops, patterns can occur multiple times in a trace, which leads to high cost of time and extreme complexity of the research. Then, an algorithm is designed to remove repetitive patterns in software and software influential nodes mining algorithm is put forward to mine influential functions in software and to rank them by the rank‐index. Finally, by comparatively analysing the top‐ten functions got from PageRank and those from Degree‐Based algorithm, the approach is proved to be an effective and accurate one which combines advantages of the two classic algorithms.