TY - GEN
T1 - Automated requirements traceability
T2 - 2010 18th IEEE International Requirements Engineering Conference, RE2010
AU - Cuddeback, David
AU - Dekhtyar, Alex
AU - Hayes, Jane Huffman
PY - 2010
Y1 - 2010
N2 - The requirements traceability matrix (RTM) supports many software engineering and software verification and validation (V&V) activities such as change impact analysis, reverse engineering, reuse, and regression testing. The generation of RTMs is tedious and error-prone, though, thus RTMs are often not generated or maintained. Automated techniques have been developed to generate candidate RTMs with some success. When using RTMs to support the V&V of mission- or safety-critical systems, however, a human analyst must vet the candidate RTMs. The focus thus becomes the quality of the final RTM. This paper investigates how human analysts perform when vetting candidate RTMs. Specifically, a study was undertaken at two universities and had 26 participants analyze RTMs of varying accuracy for a Java code formatter program. The study found that humans tend to move their candidate RTM toward the line that represents recall = precision. Participants who examined RTMs with low recall and low precision drastically improved both.
AB - The requirements traceability matrix (RTM) supports many software engineering and software verification and validation (V&V) activities such as change impact analysis, reverse engineering, reuse, and regression testing. The generation of RTMs is tedious and error-prone, though, thus RTMs are often not generated or maintained. Automated techniques have been developed to generate candidate RTMs with some success. When using RTMs to support the V&V of mission- or safety-critical systems, however, a human analyst must vet the candidate RTMs. The focus thus becomes the quality of the final RTM. This paper investigates how human analysts perform when vetting candidate RTMs. Specifically, a study was undertaken at two universities and had 26 participants analyze RTMs of varying accuracy for a Java code formatter program. The study found that humans tend to move their candidate RTM toward the line that represents recall = precision. Participants who examined RTMs with low recall and low precision drastically improved both.
KW - Decision support
KW - Information retrieval
KW - Requirements
KW - Traceability
UR - http://www.scopus.com/inward/record.url?scp=78650376710&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650376710&partnerID=8YFLogxK
U2 - 10.1109/RE.2010.35
DO - 10.1109/RE.2010.35
M3 - Conference contribution
AN - SCOPUS:78650376710
SN - 9780769541624
T3 - Proceedings of the 2010 18th IEEE International Requirements Engineering Conference, RE2010
SP - 231
EP - 240
BT - Proceedings of the 2010 18th IEEE International Requirements Engineering Conference, RE2010
Y2 - 27 September 2010 through 1 October 2010
ER -