<p>Selecting a software testing strategy entails weighing several attributes (cost, time, test coverage, and resource utilization) and selecting from a range of testing strategies. It's called a multi-attribute decision-making (MADM) problem because, to choose the best testing strategy, it's necessary to compare alternatives based on several competing attributes. More, various attributes of software testing strategy contain dual aspects, for instance, test coverage has a positive aspect, “assurance”, and a negative aspect, “limitation”. Therefore, in this manuscript, we deduce an approach of MADM by using generalized bipolar fuzzy aggregation operators (AOs) that are generalized bipolar fuzzy (G-BF) weighted averaging (G-BFWA), G-BF ordered weighted averaging (G-BFOWA), G-BF weighted geometric (G-BFOWG), and G-BF ordered weighted geometric (G-BFOWG) operators, which are also developed in this manuscript. After that, in this manuscript, we discuss a case study, “software testing strategy selection” by utilizing the anticipated approach of MADM, and reveal that the devised theory is perfect for capturing dual aspects of the attributes. In the end, we do the comparative study by comparing the anticipated work with certain prevailing work to interpret the dominance and supremacy of the deduced theory.</p>