API-Based and Information-Theoretic Metrics for Measuring the Quality of Software Modularization

Abstract

Abstract-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, architectural, and notions such as the similarity of purpose and commonality of goals. (By structural, we are referring to intermodule coupling-based notions, and by architectural, we mean the horizontal layering of modules in large software systems.) We employ the notion of API (Application Programming Interface) as the basis for our structural metrics. The rest of the metrics we present are in support of those that are based on API. Some of the important support metrics include those that characterize each module on the basis of the similarity of purpose of the services offered by the module. These metrics are based on information-theoretic principles. We tested our metrics on some popular open-source systems and some large legacy-code business applications. To validate the metrics, we compared the results obtained on human-modularized versions of the software (as created by the developers of the software) with those obtained on randomized versions of the code. For randomized versions, the assignment of the individual functions to modules was randomized.

Measuring Architecture Sustainability

“…· Distance from Main Sequence (to improve modifiability): fraction of modules that are either concrete and stable (i.e., difficult to maintain) or abstract and unstable (i.e., difficult to use) · Module Interaction Stability Index (to improve layering): percentage of modules that depend on modules with higher instability · Layer Organization Index (to improve layering): extent to which module dependencies skip adjacent layers · Normalized Testability Index (to make testing more efficient): extent to which modules are independently testable · Module Interaction Index (to improve API usage): effectiveness of how a module's API functions are used · API Function Usage Index (to improve API usage): averaged percentage of the ratio of non-API functions to API functions · Module Size Uniformity Index (to limit the sizes of modules): extent of heterogeneously sized modules · Module Size Boundedness Index (to limit the sizes of modules): extent of module sizes differing from a maximum size threshold · State Access Violation Index (to reduce internal variable usage): extent to which state variables are accessed directly across module boundaries · Association-Induced Coupling (to reduce internal variable usage): extent of coupling between modules due to class association These metrics are formally defined in literature (e.g., [9], [10]) but have not been widely used in practice. All metrics are normalized between zero and one, where one is the best achievable value.…”

Sustainability evaluation of software architectures

“…Sarkar et al [64] categorized several modularization metrics for higher-level software structures according to their adherence to well-known design principles, such as similarity of purpose, encapsulation, and layering. We reuse these generic principles in our review, but include more metrics.…”

“…The latter helps to analyse whether the metric can be determined automatically using tools. Additionally, we categorized the metrics according to common modularization design principles [64]:…”

Android Malware Detection Using Kullback-Leibler Divergence

“…The outlier values are detected using KLD. Sarkar [SARKAR, S. et al 2007] applied information theoretic measure including KLD to measure the quality of modularization in nonobject oriented software systems. Fukui ] measured the similarity of events based on KLD and applied it in the domain of fuel-cell study.…”