TY - GEN
T1 - The case for software evolution
AU - Le Goues, Claire
AU - Forrest, Stephanie
AU - Weimer, Westley
PY - 2010
Y1 - 2010
N2 - Many software systems exceed our human ability to comprehend and manage, and they continue to contain unacceptable errors. This is an unintended consequence of Moore's Law, which has led to increases in system size, complexity, and interconnectedness. Yet, software is still primarily created, modified, and maintained by humans. The interactions among heterogeneous programs, machines and human operators has reached a level of complexity rivaling that of some biological ecosystems. By viewing software as an evolving complex system, researchers could incorporate biologically inspired mechanisms and employ the quantitative analysis methods of evolutionary biology. This approach could improve our understanding and analysis of software; it could lead to robust methods for automatically writing, debugging and improving code; and it could improve predictions about functional and structural transitions as scale increases. In the short term, an evolutionary perspective challenges several research assumptions, enabling advances in error detection, correction, and prevention.
AB - Many software systems exceed our human ability to comprehend and manage, and they continue to contain unacceptable errors. This is an unintended consequence of Moore's Law, which has led to increases in system size, complexity, and interconnectedness. Yet, software is still primarily created, modified, and maintained by humans. The interactions among heterogeneous programs, machines and human operators has reached a level of complexity rivaling that of some biological ecosystems. By viewing software as an evolving complex system, researchers could incorporate biologically inspired mechanisms and employ the quantitative analysis methods of evolutionary biology. This approach could improve our understanding and analysis of software; it could lead to robust methods for automatically writing, debugging and improving code; and it could improve predictions about functional and structural transitions as scale increases. In the short term, an evolutionary perspective challenges several research assumptions, enabling advances in error detection, correction, and prevention.
KW - Evolutionary computation
KW - Genetic programming
KW - Program repair
KW - Software engineering
UR - http://www.scopus.com/inward/record.url?scp=79951656469&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79951656469&partnerID=8YFLogxK
U2 - 10.1145/1882362.1882406
DO - 10.1145/1882362.1882406
M3 - Conference contribution
AN - SCOPUS:79951656469
SN - 9781450304276
T3 - Proceedings of the FSE/SDP Workshop on the Future of Software Engineering Research, FoSER 2010
SP - 205
EP - 209
BT - Proceedings of the FSE/SDP Workshop on the Future of Software Engineering Research, FoSER 2010
T2 - FSE/SDP Workshop on the Future of Software Engineering Research, FoSER 2010
Y2 - 7 November 2010 through 11 November 2010
ER -