John Rusnak

Analyzing the Evolution of Large-Scale Software Systems Using Design Structure Matrices and Design Rule Theory: Two Exploratory Cases

Designers have long recognized the value of modularity, but important software modularity principles have remained informal. According to Baldwin and Clarks (2000) design rule theory (DRT) , modular architectures add value to system designs by creating options to improve the system by substituting or experimenting on individual modules. In this paper, we examine the design evolution of two software product platforms through the modeling lens of DRT and design structure matrices (DSMs). We show that DSM models and DRT precisely explain how real- world modularization activities in one case allowed for different rates of evolution in different software modules and in another case conferred distinct strategic advantages on a firm by permitting substitution of an at-risk software module without substantial change to the rest of the system. Our results provide positive evidence that DSM and DRT can inform important aspects of large-scale software structure and evolution, having the potential to guide software architecture design activities.

Hidden Structure: Using Network Methods to Map System Architecture

In this paper, we describe an operational methodology for characterizing the architecture of complex technical systems and demonstrate its application to a large sample of software releases. Our methodology is based upon directed network graphs, which allows us to identify all of the direct and indirect linkages between the components in a system. We use this approach to define three fundamental architectural patterns, which we label core–periphery, multi-core, and hierarchical. Applying our methodology to a sample of 1286 software releases from 17 applications, we find that the majority of releases possess a “core–periphery” structure. This architecture is characterized by a single dominant cyclic group of components (the “Core”) that is large relative to the system as a whole as well as to other cyclic groups in the system. We show that the size of the Core varies widely, even for systems that perform the same function. These differences appear to be associated with different models of development – open, distributed organizations develop systems with smaller Cores, while closed, co-located organizations develop systems with larger Cores. Our findings establish some “stylized facts” about the fine-grained structure of large, real-world technical systems, serving as a point of departure for future empirical work.