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One of the difficulties in maintaining a large software system is the absence of documented business domain topics and correlation between these domain topics and source code. Without such a correlation, people without any prior application knowledge would find it hard to comprehend the functionality of the system. Latent Dirichlet Allocation (LDA), a(More)
—We present in this paper a new set of metrics that measure the quality of modularization of a non-object-oriented software system. We have proposed a set of design principles to capture the notion of modularity and defined metrics centered around these principles. These metrics characterize the software from a variety of perspectives: structural,(More)
—The metrics formulated to date for characterizing the modularization quality of object-oriented software have considered module and class to be synonymous concepts. But, a typical class in object-oriented programming exists at too low a level of granularity in large object-oriented software consisting of millions of lines of code. A typical module(More)
In the era of global outsourcing, maintenance and enhancement activities are performed in distributed locations. In most cases, the domain expertise is not available which increases the complexity to manifold. A critical success factor in such a scenario is to have a collaborative platform for managing and sharing the domain specific knowledge across(More)
—Developers of GPU kernels, such as FFT, linear solvers, etc, tune their code extensively in order to obtain optimal performance, making efficient use of different resources available on the GPU. Complex applications are composed of several such kernel components. The software engineering community has performed extensive research on component-based design(More)
This paper characterizes operational failures of a production Custom Package Good Software-as-a-Service (SaaS) platform. Events log collected over 283 days of in-field operation are used to characterize platform failures. The characterization is performed by estimating (i) common failure types of the platform, (ii) key factors impacting platform failures,(More)