Congratulations to our master's student, Li Lei, on the publication of his full paper titled "On Estimating the Feasible Solution Space of Multi-Objective Testing Resource Allocation" in ACM Transactions on Software Engineering and Methodology (TOSEM) (CCF A category).

The paper addresses the problem of multi-objective software testing resource allocation with cost and reliability constraints. It utilizes the convexity and concavity of the optimization objective functions. It employs the Lagrange multiplier method and segmented binary search to estimate the feasible solution space of the problem from both theoretical and algorithmic perspectives. The paper derives new, stricter variable upper and lower bounds, which can help software project managers determine the reasonableness of their constraint settings. Additionally, the derived constraints precisely enclose the tiny feasible solution space, aiding existing constraint-based multi-objective optimizers in searching within the solution space. Furthermore, to fully leverage these constraints, the paper proposes a generalized constraint handling approach that allows multi-objective optimizers to pull infeasible solutions back into the estimated solution space under theoretical guarantees, thereby efficiently exploring feasible solutions and improving software testing efficiency.

Previously, Li Lei published "New Reliability-Driven Bounds for Architecture-Based Multi-Objective Testing Resource Allocation" in IEEE Transactions on Software Engineering in April 2023, achieving coverage in two top-tier journals in the international software engineering field.

Links to the papers:

ACM TOSEM: https://dl.acm.org/doi/10.1145/3654444

IEEE TSE:https://ieeexplore.ieee.org/document/9960830