A Systematic Aspect-Oriented Refactoring and Testing Strategy, and its Application to JHotDraw

Aspect oriented programming aims at achieving better modularization for a system's crosscutting concerns in order to improve its key quality attributes, such as evolvability and reusability. Consequently, the adoption of aspect-oriented techniques in existing (legacy) software systems is of interest to remediate software aging. The refactoring of existing systems to employ aspect-orientation will be considerably eased by a systematic approach that will ensure a safe and consistent migration. In this paper, we propose a refactoring and testing strategy that supports such an approach and consider issues of behavior conservation and (incremental) integration of the aspect-oriented solution with the original system. The strategy is applied to the JHotDraw open source project and illustrated on a group of selected concerns. Finally, we abstract from the case study and present a number of generic refactorings which contribute to an incremental aspect-oriented refactoring process and associate particular types of crosscutting concerns to the model and features of the employed aspect language. The contributions of this paper are both in the area of supporting migration towards aspect-oriented solutions and supporting the development of aspect languages that are better suited for such migrations.Comment: 25 page

06302 Abstracts Collection -- Aspects For Legacy Applications

From 26.07.06 to 29.07.06, the Dagstuhl Seminar 06302 ``Aspects For Legacy Applications\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Flux compactifications and supersymmetry breaking in 6D gauged supergravity

We review on a recent construction of the on-shell supersymmetric brane action for the codimension-two branes with nonzero tension in the flux compactification of a 6D chiral gauged supergravity. On dimesionally reducing on 4D gauged supergravity for a new supersymmetric unwarped background with conical branes, we consider the modulus stabilization for determining the soft masses of the scalars localized on the branes and show that the bulk U(1)_R provides a new mechanism for mediating the SUSY breaking.Comment: 12 pages, no figures, Invited review for Modern Physics Letters A, Published versio

Types and concept analysis for legacy systems

We combine type inference and concept analysis in order to gain insight into legacy software systems. Type inference for Cobol yields the types for variables and program parameters. These types are used to perform mathematical concept analysis on legacy systems. We have developed ConceptRefinery, a tool for interactively manipulating concepts. We show how this tools facilitates experiments with concept analysis, and lets reengineers employ their knowedge of the legacy system to refine the results of concept analysis

Towards Extending the Range of Bugs That Automated Program Repair Can Handle

Modern automated program repair (APR) is well-tuned to finding and repairing bugs that introduce observable erroneous behavior to a program. However, a significant class of bugs does not lead to such observable behavior (e.g., liveness/termination bugs, non-functional bugs, and information flow bugs). Such bugs can generally not be handled with current APR approaches, so, as a community, we need to develop complementary techniques. To stimulate the systematic study of alternative APR approaches and hybrid APR combinations, we devise a novel bug classification system that enables methodical analysis of their bug detection power and bug repair capabilities. To demonstrate the benefits, we analyze the repair of termination bugs in sequential and concurrent programs. The study shows that integrating dynamic APR with formal analysis techniques, such as termination provers and software model checkers, reduces complexity and improves the overall reliability of these repairs.Comment: Accepted for publication in the 22nd IEEE International Conference on Software Quality, Reliability and Security (QRS 2022

The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification

The use of modern Natural Language Processing (NLP) techniques has shown to be beneficial for software engineering tasks, such as vulnerability detection and type inference. However, training deep NLP models requires significant computational resources. This paper explores techniques that aim at achieving the best usage of resources and available information in these models. We propose a generic approach, EarlyBIRD, to build composite representations of code from the early layers of a pre-trained transformer model. We empirically investigate the viability of this approach on the CodeBERT model by comparing the performance of 12 strategies for creating composite representations with the standard practice of only using the last encoder layer. Our evaluation on four datasets shows that several early layer combinations yield better performance on defect detection, and some combinations improve multi-class classification. More specifically, we obtain a +2 average improvement of detection accuracy on Devign with only 3 out of 12 layers of CodeBERT and a 3.3x speed-up of fine-tuning. These findings show that early layers can be used to obtain better results using the same resources, as well as to reduce resource usage during fine-tuning and inference.Comment: The content in this pre-print is the same as in the CRC accepted for publication in the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023

A common framework for aspect mining based on crosscutting concern sorts

The increasing number of aspect mining techniques proposed in literature calls for a methodological way of comparing and combining them in order to assess, and improve on, their quality. This paper addresses this situation by proposing a common framework based on crosscutting concern sorts which allows for consistent assessment, comparison and combination of aspect mining techniques. The framework identifies a set of requirements that ensure homogeneity in formulating the mining goals, presenting the results and assessing their quality. We demonstrate feasibility of the approach by retrofitting an existing aspect mining technique to the framework, and by using it to design and implement two new mining techniques. We apply the three techniques to a known aspect mining benchmark and show how they can be consistently assessed and combined to increase the quality of the results. The techniques and combinations are implemented in FINT, our publicly available free aspect mining tool