Understanding, Analysis, and Handling of Software Architecture Erosion

Architecture erosion occurs when a software system's implemented architecture diverges from the intended architecture over time. Studies show erosion impacts development, maintenance, and evolution since it accumulates imperceptibly. Identifying early symptoms like architectural smells enables managing erosion through refactoring. However, research lacks comprehensive understanding of erosion, unclear which symptoms are most common, and lacks detection methods. This thesis establishes an erosion landscape, investigates symptoms, and proposes identification approaches. A mapping study covers erosion definitions, symptoms, causes, and consequences. Key findings: 1) "Architecture erosion" is the most used term, with four perspectives on definitions and respective symptom types. 2) Technical and non-technical reasons contribute to erosion, negatively impacting quality attributes. Practitioners can advocate addressing erosion to prevent failures. 3) Detection and correction approaches are categorized, with consistency and evolution-based approaches commonly mentioned.An empirical study explores practitioner perspectives through communities, surveys, and interviews. Findings reveal associated practices like code review and tools identify symptoms, while collected measures address erosion during implementation. Studying code review comments analyzes erosion in practice. One study reveals architectural violations, duplicate functionality, and cyclic dependencies are most frequent. Symptoms decreased over time, indicating increased stability. Most were addressed after review. A second study explores violation symptoms in four projects, identifying 10 categories. Refactoring and removing code address most violations, while some are disregarded.Machine learning classifiers using pre-trained word embeddings identify violation symptoms from code reviews. Key findings: 1) SVM with word2vec achieved highest performance. 2) fastText embeddings worked well. 3) 200-dimensional embeddings outperformed 100/300-dimensional. 4) Ensemble classifier improved performance. 5) Practitioners found results valuable, confirming potential.An automated recommendation system identifies qualified reviewers for violations using similarity detection on file paths and comments. Experiments show common methods perform well, outperforming a baseline approach. Sampling techniques impact recommendation performance

Warnings: Violation Symptoms Indicating Architecture Erosion

As a software system evolves, its architecture tends to degrade, and gradually impedes software maintenance and evolution activities and negatively impacts the quality attributes of the system. The main root cause behind architecture erosion phenomenon derives from violation symptoms (such as violations of architecture pattern). Previous studies focus on detecting violations in software systems using architecture conformance checking approaches. However, code review comments are also rich sources that may contain extensive discussions regarding architecture violations. In this work, we investigated the characteristics of architecture violation symptoms in code review comments from the developers' perspective. We employed a set of keywords related to violation symptoms to collect 606 (out of 21,583) code review comments from four popular OSS projects in the OpenStack and Qt communities. We manually analyzed the collected 606 review comments to provide the categories and linguistic patterns of violation symptoms, as well as the reactions how developers addressed them. Our findings show that: (1) 10 categories of violation symptoms are discussed by developers during the code review process; (2) The frequently-used terms of expressing violation symptoms are "inconsistent" and "violate", and the most frequently-used linguistic pattern is Problem Discovery; (3) Refactoring and removing code are the major measures (90%) to tackle violation symptoms, while a few violation symptoms were ignored by developers. Our findings suggest that the investigation of violation symptoms can help researchers better understand the characteristics of architecture erosion and facilitate the development and maintenance activities, and developers should explicitly manage violation symptoms, not only for addressing the existing architecture violations but also preventing future violations.Comment: Preprint accepted for publication in Information and Software Technology, 202

A feature-based classification of model repair approaches

Consistency management, the ability to detect, diagnose and handle inconsistencies, is crucial during the development process in Model-driven Engineering (MDE). As the popularity and application scenarios of MDE expanded, a variety of different techniques were proposed to address these tasks in specific contexts. Of the various stages of consistency management, this work focuses on inconsistency handling in MDE, particularly in model repair techniques. This paper proposes a feature-based classification system for model repair techniques, based on an systematic literature review of the area. We expect this work to assist developers and researchers from different disciplines in comparing their work under a unifying framework, and aid MDE practitioners in selecting suitable model repair approaches.Work financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF) through project "NORTE-01-0145-FEDER-000016"

Integrity static analysis of COTS/SOUP

This paper describes the integrity static analysis approach developed to support the justification of commercial off-the-shelf software (COTS) used in a safety-related system. The static analysis was part of an overall software qualification programme, which also included the work reported in our paper presented at Safecomp 2002. Integrity static analysis focuses on unsafe language constructs and “covert” flows, where one thread can affect the data or control flow of another thread. The analysis addressed two main aspects: the internal integrity of the code (especially for the more critical functions), and the intra-component integrity, checking for covert channels. The analysis process was supported by an aggregation of tools, combined and engineered to support the checks done and to scale as necessary. Integrity static analysis is feasible for industrial scale software, did not require unreasonable resources and we provide data that illustrates its contribution to the software qualification programme

Modeling collective rationality : an nonparametric test on experimental data.

We provide a .first nonparametric (revealed preference) test of the collective consumption model on the basis of experimental data. By using nonparametric testing tools and experimental data, we avoid the usual problems associated with parametric tests (e.g. non-verifiable parametric structure) and the use of ‘real life’ data sets (e.g. preference heterogeneity). In addition, our collective rationality test complements the existing nonparametric-experimental evidence on individual rationality. Focusing on dyads, we find that all observed consumption choices are consistent with the nonparametric collective rationality conditions. In fact, the consistency results for the parsimonious ‘egoistic’ collective consumption model (as a tool for describing dyads’ choice behavior) are closely similar to those for the individual rationality model (as a tool for describing individuals’.choice behavior). This suggest that for simple consumption decision settings, such as that considered in our experiment, the egoistic model may be useful for practical analysis. Still, our results also suggest that the more general collective consumption model, which accounts for consumption externalities and public consumption, can be useful even for modeling such simple decision settings. In fact, we can interpret that the appropriate model specification also depends on the specific dyad type (e.g. friends or partners; gender composition) and choice setting (e.g. public consumption or not) at hand.Collective consumption decisions; Generalized Axiom of Revealed Preference; Nonparametric analysis; Experimental data;

Principles in Patterns (PiP) : Project Evaluation Synthesis

Evaluation activity found the technology-supported approach to curriculum design and approval developed by PiP to demonstrate high levels of user acceptance, promote improvements to the quality of curriculum designs, render more transparent and efficient aspects of the curriculum approval and quality monitoring process, demonstrate process efficacy and resolve a number of chronic information management difficulties which pervaded the previous state. The creation of a central repository of curriculum designs as the basis for their management as "knowledge assets", thus facilitating re-use and sharing of designs and exposure of tacit curriculum design practice, was also found to be highly advantageous. However, further process improvements remain possible and evidence of system resistance was found in some stakeholder groups. Recommendations arising from the findings and conclusions include the need to improve data collection surrounding the curriculum approval process so that the process and human impact of C-CAP can be monitored and observed. Strategies for improving C-CAP acceptance among the "late majority", the need for C-CAP best practice guidance, and suggested protocols on the knowledge management of curriculum designs are proposed. Opportunities for further process improvements in institutional curriculum approval, including a re-engineering of post-faculty approval processes, are also recommended