TY - GEN
T1 - Computing Program Functions
AU - Mohammadi, Hessamaldin
AU - Ghardallou, Wided
AU - Linger, Richard C.
AU - Mili, Ali
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022
Y1 - 2022
N2 - Extracting the function of a program from a static analysis of its source code is a valuable capability in software engineering, but it has proved to be an elusive goal, due primarily to the difficulty of deriving the function of iterative statements. Several automated tools obviate this difficulty by unrolling the loops; but this is clearly an imperfect solution, especially in light of the fact that loops capture most of the computing power of a program, are the locus of most of its complexity, and the source of most of its faults. In this paper we discuss the design and ongoing implementation of an automated tool for deriving the function of a program in three steps: first, the source code is mapped onto an abstract syntax tree (AST), using standard parsing technology; then each node of the AST is mapped onto an equation between pre and post states; finally, these equations are submitted to a symbolic computation engine that extracts the final program state as a function of its initial state. Loop functions are derived by pattern matching against semantic recognizers, which capture the requisite programming knowledge and domain knowledge.
AB - Extracting the function of a program from a static analysis of its source code is a valuable capability in software engineering, but it has proved to be an elusive goal, due primarily to the difficulty of deriving the function of iterative statements. Several automated tools obviate this difficulty by unrolling the loops; but this is clearly an imperfect solution, especially in light of the fact that loops capture most of the computing power of a program, are the locus of most of its complexity, and the source of most of its faults. In this paper we discuss the design and ongoing implementation of an automated tool for deriving the function of a program in three steps: first, the source code is mapped onto an abstract syntax tree (AST), using standard parsing technology; then each node of the AST is mapped onto an equation between pre and post states; finally, these equations are submitted to a symbolic computation engine that extracts the final program state as a function of its initial state. Loop functions are derived by pattern matching against semantic recognizers, which capture the requisite programming knowledge and domain knowledge.
KW - Java
KW - Program verification
KW - invariantrelations
KW - program functions
KW - symbolic execution
UR - http://www.scopus.com/inward/record.url?scp=85134056393&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134056393&partnerID=8YFLogxK
U2 - 10.1145/3524482.3527655
DO - 10.1145/3524482.3527655
M3 - Conference contribution
AN - SCOPUS:85134056393
T3 - Proceedings - IEEE/ACM 10th International Conference on Formal Methods in Software Engineering, FormaliSE 2022
SP - 102
EP - 112
BT - Proceedings - IEEE/ACM 10th International Conference on Formal Methods in Software Engineering, FormaliSE 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE/ACM International Conference on Formal Methods in Software Engineering, FormaliSE 2022
Y2 - 18 May 2022 through 19 May 2022
ER -