Software modernization has been extensively researched, primarily focusing on observing the associated phenomena, and providing technical solutions to facilitate the modernization process. Software modernization is claimed to be successful when the modernization is completed using those technical solutions. Very limited research, if any, is reported with an aim at documenting the post-modernization impacts, i.e., whether any of the pre-modernization business goals are in fact achieved after modernization. In this research, we attempt to address this relative absence of empirical study through five retrospective software modernization case studies. We use an explanatory case study approach to document the pre-modernization business goals, and to decide whether those goals have been achieved. The intended benefits for each of the five cases we considered were all (partially) met, and in most cases fully. Moreover, many cases exhibited a number of unintended benefits, and some reported detrimental effects of modernization.

Topic modeling has seen a surge in use for software comprehension. Although the models inferred from the source code are a great source of knowledge, they fail to fully capture the conceptual relationships between the topics. Here we investigate the use of interactive topic modeling for source code analysis by feeding-in information from the end-users, including developers and architects, to refine the inferred topic models. We have implemented a web-based toolkit called ITMViz to provide support to interpret the topic models, and use the results to cluster modules together. A medium-sized Java project is used to evaluate our approach in understanding the software system.

Unsupervised software clustering is the problem of automatically decomposing the software system into meaningful units. Some approaches solely rely on the structure of the system, such as the module dependency graph, to decompose the software systems into cohesive groups of modules. Other techniques focus on the informal knowledge hidden within the source code itself to retrieve the modular architecture of the system. However both techniques in the case of large systems fail to produce decompositions that correspond to the actual architecture of the system. To overcome this problem, we propose a novel approach to clustering software systems by incorporating knowledge from different viewpoints of the system, such as the knowledge embedded within the source code as well as the structural dependencies within the system, to produce a clustering. In this setting, we adopt a search-based approach to the encoding of multi-view clustering and investigate two approaches to tackle this problem, one based on a linear combination of objectives into a single objective, the other a multi-objective approach to clustering. We evaluate our approach against a set of substantial software systems. The two approaches are evaluated on a dataset comprising of 10 Java open source projects. Finally, we propose two techniques based on interpolation and hierarchical clustering to combine different results obtained to yield a single result for single-objective and multi-objective encodings, respectively.

Existing research in legacy system modernization has traditionally focused on technical challenges, and takes the standpoint that legacy systems are obsolete, yet crucial for an organization's operation. Nonetheless, it remains unclear whether practitioners in the industry also share this perception. This paper describes the outcome of an exploratory study in which 26 industrial practitioners were interviewed on what makes a software system a legacy system, what the main drivers are that lead to the modernization of such systems, and what challenges are faced during the modernization process. The findings of the interviews have been validated by means of a survey with 198 respondents. The results show that practitioners value their legacy systems highly, the challenges they face are not just technical, but also include business and organizational aspects.

Legacy systems are vitally important for the continuation of business in an enterprise as they support complex core business processes. However, legacy systems have several well-known disadvantages such as being inflexible and hard to maintain, so momentum is growing to evolve those systems into new technology environments. Recently, service-oriented architecture has emerged as a promising architectural style that enables existing legacy systems to expose their functionality as services, without making significant changes to the legacy systems themselves. A significant number of the legacy to service migration approaches address the technical perspective (i.e., supporting technology) to expose the legacy code as services. The other approaches focus on determining the feasibility of the migration that includes economical and technical feasibility, based on the characteristics of existing legacy system and the requirements of the target SOA system. In this paper, a legacy to SOA migration method that does not single out the migration feasibility and technical perspectives, but combines these two perspectives of migration, is proposed. Method engineering is used to develop the migration method by reusing method fragments from existing service-oriented development methods. Then, concept slicing is used to develop the service by extracting the relevant parts of the legacy code. The method is evaluated and enhanced by interviewing experts and further validated with two case studies. The method is found to be appropriate and effective in extracting services from legacy code with the aim of reusing these services in new configurations.