A framework for cost-effective dependence-based dynamic impact analysis

Abstract

Dynamic impact analysis can greatly assist developers with managing software changes by focusing their attention on the effects of potential changes relative to concrete program executions. While dependence-based dynamic impact analysis (DDIA) provides finer-grained results than traceability-based approaches, traditional DDIA techniques often produce imprecise results, incurring excessive costs thus hindering their adoption in many practical situations.In this paper, we present the design and evaluation of a DDIA framework and its three new instances that offer not only much more precise impact sets but also flexible cost-effectiveness options to meet diverse application needs such as different budgets and levels of detail of results. By exploiting both static dependencies and various dynamic information including method-execution traces, statement coverage, and dynamic points-to data, our techniques achieve that goal at reasonable costs according to our experiment results. Our study also suggests that statement coverage has generally stronger effects on the precision and cost-effectiveness of DDIA than dynamic points-to data.

Do code data sharing dependencies support an early prediction of software actual change impact set?

“…A number of previous works focuses on the analysis of structural dependence, most of which leverage the call dependencies among entities (most notably methods and classes) and Program Dependence Graph (PDG) as indicators for change impact set. Our work belongs to this category.…”

DistIA: a cost-effective dynamic impact analysis for distributed programs

“…To accomplish this task, method-level dynamic impact-prediction techniques of various cost-effectiveness tradeoffs (e.g., [4,11,13]) seem to be able to offer the developer many options. However, since there is no explicit dependencies between S and C, existing approaches would predict impacts within the local component (i.e., where the changes are located; S in this case) only.…”

“…Therefore, despite of its known imprecision, impact analysis using execute-after relations like EAS remains a viable option, especially for users who desire getting a safe approximation of impacts quickly, such as the developer in the above example scenario. In fact, to the best of our knowledge, EAS is still the most efficient dynamic impact analysis to date [11,13,14]. Thus, as the first attempt exploring efficient dynamic impact analysis for distributed systems, we start with an EAS-based approach in this work.…”

“…A complementary approach would be to reduce local impacts, such as through static-dependence-based pruning as in [11]. It is straightforward to incorporate such approaches in DISTIA to further improve its effectiveness, but that will largely increase the cost as well [13].…”

“…Dynamic impact analysis has been extensively investigated [40], resulting in a rich and diverse set of relevant techniques and tools (e.g., [4,11,13,39]). However, most existing approaches address sequential programs only, with fewer targeting concurrent yet centralized software [25,27,35,65] and very few applicable to distributed systems.…”