Abstract (EN):
We analyzed the data from PSP training courses, involving approximately 3000 students, to determine the personal and non-personal factors that affect productivity performance. Regarding non-personal factors, by conducting a detailed per-phase analysis, we found both process changes and project complexity to be important factors explaining productivity variations throughout the sequence of programs. Regarding personal factors, we found significant variations among individuals that can be partially explained by personal experience and programming language used. We also show that an improved estimation model can be derived by taking into account these factors, leading to significant reductions in estimation errors. Understanding these factors is also useful to help analyzing the productivity of individual engineers.
Language:
English
Type (Professor's evaluation):
Scientific