Architecture-sensitive heuristics for prioritizing critical code anomalies

Abstract

The progressive insertion of code anomalies in evolving software systems might lead to architecture degradation symptoms. Code anomalies are particularly harmful when they contribute to the architecture degradation. Although several approaches have been proposed aiming to detect anomalies in the source code, most of them fail to assist developers when prioritizing code anomalies critical to the architectural design. Blueprints of the architecture design are artifacts often available in industry software projects. However, such blueprints are rarely explored to support the prioritization of code anomalies in terms of their architecture relevance. This paper proposes and evaluates 2 sets of blueprintbased heuristics for supporting the prioritization of critical code anomalies. The prioritization is based on their potential impact on revealing architectural drift problems. The heuristics allow developers prioritizing critical code anomalies by exploiting architectural information provided in the blueprint. The contributions of this paper include: (i) a set of architecture sensitive heuristics to support developers when prioritizing critical code anomalies; (ii) an evaluation of the proposed heuristics in terms of their prioritization accuracy in 3 systems; and (iii) an empirical analysis on how the blueprints' information might enhance the prioritization of critical code anomalies, as opposed to existing heuristics strictly based on source code analysis.

An Empirical Analysis of Approach-Based Metrics Model for Architectural Erosion Detection

“…Therefore, the findings of the correlation between AM and the emergence of AE are consistent with the observations by 115 , besides, modularization metrics provide a better representation picture for fault prediction, design flaw detection, identifying source code anomalies and architectural degradation 116 , as well as improving architecture 117 with regard to the analysis of faults and changes that could be isolated and separated. Moreover, the results regarding the relationship between ABS and the occurrence of AE (B = 0.215, t = 3.356, p 0.001, F2 = 0.075) are consistent with the analysis and examination of the various study on architectural smells and their relationship to determine the presence of architectural erosion 55,56,59,60,118 and instability in order to identify hidden defects in software architecture 119 . Concerning hypothesis 8 (H8), it was determined that statistically indicates an occurrence of the AE ( B = 0.152, t = 3.313, p < 0.001, F2 = .074).This provides significant evidence supporting the hypothesis, which is in line with research showing that historical metrics may automatically discover violations of design principles 34 , high-performance forecasting of low architectural quality (i.e., architectural erosion) in architectural modules, and even in the case of rapid decay 19 , estimation of severity based on analysis of change over time 37 , as well as historical metrics for assessing and forecasting architecture quality condition 36 .…”

Characterizing the Architectural Erosion Metrics: A Systematic Mapping Study

“…Table 6 shows the quality assessment criteria. Lenhard et al [26] Sejfia [58] Mo et al [59] Maisikeli [60] Carvalho et al [61] Shahbazian et al [62] Behnamghader et al [63] Mohsin et al [64] Henrique et al [65] Fontana et al [66] Mo et al [67] De Oliveira Barros et al [68] Guimarães et al [69] Fontana et al [70] Zengyang et al [71] Ferreira et al [72] Macia et al [73] Guimaraes et al [74] Macia et al [75] Zude et al [76] Steff and Russo [77] Sangwan et al [78] Andrea and Thomas [79] Singh et al [80] An The score "Yes" =1 / "No" = 0 / "partial" = 0.5 QA 3…”

Exploring architecture blueprints for prioritizing critical code anomalies: Experiences and tool support

“…Due to the need of quantifying blueprints with regards to the corresponding source code, we have initially proposed 3 metrics (LOA, completeness, and consistency). 24 Furthermore, we deal with the mappings of a blueprint to source code. We provide definitions of the main concepts involved in our approach, which serve as a conceptual framework for Sections 4, 5, and 6.…”

“…Due to the need of quantifying blueprints with regards to the corresponding source code, we have initially proposed 3 metrics (LOA, completeness, and consistency) . Furthermore, we deal with the mappings of a blueprint to source code.…”