Mon, Mar 01, 2021 @ 12:00 PM - 02:00 PM
PhD Candidate: Kan Qi
Prof. Barry Boehm (chair)
Prof. Paul Adler (outside)
Prof. Chao Wang
Title: Incremental Effort Estimation via Transaction Analysis
Accurate software cost and effort estimation is particularly important for many classes of software projects. Examples are projects with fixed budget, competitive bidding on prospective projects, or prioritization of candidate projects. Many organizations primarily rely on commercial or open-source cost estimation models, which have been calibrated on the actual sizes and costs of previous projects. Their key size parameter is generally the number of lines of code in the projects. This can be accurately determined via a code-count system on the previous projects, but there is no counterpart for estimating the lines of code in the system to be developed. One can try to break the system into pieces and estimate the lines of code in each piece but doing this accurately will generally require additional time and effort to design the system. Alternative early effort estimation methods such as story points, use case points, and function points involve determining the system's numbers and complexities of user stories, use cases, inputs, outputs, queries, and logical files, which again typically require additional time and effort to analyze the functionality and architecture. In summary, there are two limitations that prevent the existing effort estimation methods from being effectively used for early effort estimation. First, the existing methods require extensive manual analysis effort to acquire system information as their input. This makes it costly to apply the existing methods at the early stage of a software project. Secondly, the system information that the existing methods rely on as the input can usually only be retrieved from certain types of system specifications. This makes the existing methods only applicable at the development phases where the required types of system specifications are produced.
To address the first limitation, an automated transaction analysis method is proposed, which can be used to automatically retrieve transactional information from the typical early-phase artifacts produced in a software project; To address the second limitation, three phase-based effort estimation models are proposed, which utilize the retrieved transactional information to provide effort estimates at all the typical early phases of a software project. The evaluation results have shown that the automated transaction analysis method can be an effective replacement of manual transaction analysis with high transaction identification accuracy, and the phase-based effort estimation models can provide considerable estimation accuracy improvements over the existing effort estimation models and the later-phase effort estimation models can provide significant accuracy improvements over the earlier-phase effort estimation models.
Audiences: Everyone Is Invited
Contact: Lizsl De Leon