Feature-Interaction Aware Configuration Prioritization for Configurable Code

Abstract

Unexpected interactions among features induce most bugs in a configurable software system. Exhaustively analyzing all the exponential number of possible configurations is prohibitively costly. Thus, various sampling techniques have been proposed to systematically narrow down the exponential number of legal configurations to be analyzed. Since analyzing all selected configurations can require a huge amount of effort, fault-based configuration prioritization, that helps detect faults earlier, can yield practical benefits in quality assurance. In this paper, we propose COPRO, a novel formulation of feature-interaction bugs via common program entities enabled/disabled by the features. Leveraging from that, we develop an efficient feature-interactionaware configuration prioritization technique for a configurable system by ranking the configurations according to their total number of potential bugs. We conducted several experiments to evaluate COPRO on the ability to detect configuration-related bugs in a public benchmark. We found that COPRO outperforms the state-of-the-art configuration prioritization techniques when we add them on advanced sampling algorithms. In 78% of the cases, COPRO ranks the buggy configurations at the top 3 positions in the resulting list. Interestingly, COPRO is able to detect 17 not-yet-discovered feature-interaction bugs.

A Data Mining Technique to Improve Configuration Prioritization Framework for Component-Based Systems: An Empirical Study

“…Therefore, most component-based systems are a combination of previously built components that are relevant to the same domain of new products' development. Currently, for the implementation of reused components, and features to manage requirements of new products, different configurations of components are enabled by the developing team [36,44]. As software products in the advanced intelligent technology era are a combination of software and hardware with a large number of customization options (for example, a searching browser provides different options like setting, home, sign in, history, language, pop up window, etc.…”

“…As software products in the advanced intelligent technology era are a combination of software and hardware with a large number of customization options (for example, a searching browser provides different options like setting, home, sign in, history, language, pop up window, etc. for the users and every user has own options selection scheme) to use products in several ways [27,36]. Hence, the configuration is the customization options in software and hardware products for tailoring functional and non-functional requirements of components-based systems.…”

“…The interaction of configuration and their features with other configurations' features creates ambiguity and errors due to improper prioritization and selection of features or configuration to fulfil system requirements [6,29,36,47]. For a configurable system, to correctly identify and manage the requirements, and to avoid reuse of irrelevant requirements of other applications, it is necessary to improve the structuring, and prioritization process of configurable systems requirements, with the active participation of stakeholders [15,30,34].…”

“…The main issues in the prioritization of configurable applications are the incompleteness, inconsistency, ambiguous configurations, inefficient Figure 1 Configurable system organization adaptation to changes, and tracing components in all phases of software development due to an inadequate configuration prioritization (CP) process. Therefore, prioritization of configuration in components-based systems is an important activity for correct and accurate reuse, and structuring of configuration in a continuous software evolution environment [2,15,36]. Therefore, CP is an important and critical activity for requirements configuration identification, prioritization, and validation before software release [1,17,32].…”

“…Consequently, in the present era large and complex information is being generated which increases the need for data mining during the software development process. Application of data mining helps in improving software quality and productivity but still, different challenges exist like inconsistency, ambiguities, incompleteness, etc., during information attribution extraction [26,36]. Therefore, different types of algorithms are required to extract accurately different aspects of information like text, sequence, graph, etc., mining.…”