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Alexander Egyed

Publications and source records attributed to Alexander Egyed.

At least 19 recordsLinked to original sources
arXiv2026

An Extensive Replication Study of the ABLoTS Approach for Bug Localization

Bug localization is the task of recommending source code locations (typically files) that contain the cause of a bug and hence need to be changed to fix the bug. Along these lines, information retrieval-based bug localization (IRBL) approaches have been adopted, which identify the most bug-prone files from the source code space. In current practice, a series of state-of-the-art IRBL techniques leverage the combination of different components (e.g., similar reports, version history, and code structure) to achieve better performance. ABLoTS is a recently proposed approach with the core component, TraceScore, that utilizes requirements and traceability information between different issue reports (i.e., feature requests and bug reports) to identify buggy source code snippets with promising results. To evaluate the accuracy of these results and obtain additional insights into the practical applicability of ABLoTS, we conducted a replication study of this approach with the original dataset and also on two extended datasets (i.e., additional Java dataset and Python dataset). The original dataset consists of 11 open source Java projects with 8,494 bug reports. The extended Java dataset includes 16 more projects comprising 25,893 bug reports and corresponding source code commits. The extended Python dataset consists of 12 projects with 1,289 bug reports. While we find that the TraceScore component, which is the core of ABLoTS, produces comparable or even better results with the extended datasets, we also find that we cannot reproduce the ABLoTS results, as reported in its original paper, due to an overlooked side effect of incorrectly choosing a cut-off date that led to test data leaking into training data with significant effects on performance.

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arXiv2025

Refactoring $\neq$ Bug-Inducing: Improving Defect Prediction with Code Change Tactics Analysis

Just-in-time defect prediction (JIT-DP) aims to predict the likelihood of code changes resulting in software defects at an early stage. Although code change metrics and semantic features have enhanced prediction accuracy, prior research has largely ignored code refactoring during both the evaluation and methodology phases, despite its prevalence. Refactoring and its propagation often tangle with bug-fixing and bug-inducing changes within the same commit and statement. Neglecting refactoring can introduce bias into the learning and evaluation of JIT-DP models. To address this gap, we investigate the impact of refactoring and its propagation on six state-of-the-art JIT-DP approaches. We propose Code chAnge Tactics (CAT) analysis to categorize code refactoring and its propagation, which improves labeling accuracy in the JIT-Defects4J dataset by 13.7%. Our experiments reveal that failing to consider refactoring information in the dataset can diminish the performance of models, particularly semantic-based models, by 18.6% and 37.3% in F1-score. Additionally, we propose integrating refactoring information to enhance six baseline approaches, resulting in overall improvements in recall and F1-score, with increases of up to 43.2% and 32.5%, respectively. Our research underscores the importance of incorporating refactoring information in the methodology and evaluation of JIT-DP. Furthermore, our CAT has broad applicability in analyzing refactoring and its propagation for software maintenance.

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arXiv2024

Model-based Maintenance and Evolution with GenAI: A Look into the Future

Model-Based Engineering (MBE) has streamlined software development by focusing on abstraction and automation. The adoption of MBE in Maintenance and Evolution (MBM&E), however, is still limited due to poor tool support and a lack of perceived benefits. We argue that Generative Artificial Intelligence (GenAI) can be used as a means to address the limitations of MBM&E. In this sense, we argue that GenAI, driven by Foundation Models, offers promising potential for enhancing MBM&E tasks. With this possibility in mind, we introduce a research vision that contains a classification scheme for GenAI approaches in MBM&E considering two main aspects: (i) the level of augmentation provided by GenAI and (ii) the experience of the engineers involved. We propose that GenAI can be used in MBM&E for: reducing engineers' learning curve, maximizing efficiency with recommendations, or serving as a reasoning tool to understand domain problems. Furthermore, we outline challenges in this field as a research agenda to drive scientific and practical future solutions. With this proposed vision, we aim to bridge the gap between GenAI and MBM&E, presenting a structured and sophisticated way for advancing MBM&E practices.

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arXiv2024

Contemporary Software Modernization: Perspectives and Challenges to Deal with Legacy Systems

Software modernization is an inherent activity of software engineering, as technology advances and systems inevitably become outdated. The term "software modernization" emerged as a research topic in the early 2000s, with a differentiation from traditional software evolution. Studies on this topic became popular due to new programming paradigms, technologies, and architectural styles. Given the pervasive nature of software today, modernizing legacy systems is paramount to provide users with competitive and innovative products and services. Despite the large amount of work available in the literature, there are significant limitations: (i) proposed approaches are strictly specific to one scenario or technology, lacking flexibility; (ii) most of the proposed approaches are not aligned with the current modern software development scenario; and (iii) due to a myriad of proposed modernization approaches, practitioners may be misguided on how to modernize legacies. In this work, our goal is to call attention to the need for advances in research and practices toward a well-defined software modernization domain. The focus is on enabling organizations to preserve the knowledge represented in legacy systems while taking advantages of disruptive and emerging technologies. Based on this goal, we put the different perspectives of software modernization in the context of contemporary software development. We also present a research agenda with 10 challenges to motivate new studies.

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arXiv2024

TRIAD: Automated Traceability Recovery based on Biterm-enhanced Deduction of Transitive Links among Artifacts

Traceability allows stakeholders to extract and comprehend the trace links among software artifacts introduced across the software life cycle, to provide significant support for software engineering tasks. Despite its proven benefits, software traceability is challenging to recover and maintain manually. Hence, plenty of approaches for automated traceability have been proposed. Most rely on textual similarities among software artifacts, such as those based on Information Retrieval (IR). However, artifacts in different abstraction levels usually have different textual descriptions, which can greatly hinder the performance of IR-based approaches (e.g., a requirement in natural language may have a small textual similarity to a Java class). In this work, we leverage the consensual biterms and transitive relationships (i.e., inner- and outer-transitive links) based on intermediate artifacts to improve IR-based traceability recovery. We first extract and filter biterms from all source, intermediate, and target artifacts. We then use the consensual biterms from the intermediate artifacts to extend the biterms of both source and target artifacts, and finally deduce outer and inner-transitive links to adjust text similarities between source and target artifacts. We conducted a comprehensive empirical evaluation based on five systems widely used in other literature to show that our approach can outperform four state-of-the-art approaches, and how its performance is affected by different conditions of source, intermediate, and target artifacts. The results indicate that our approach can outperform baseline approaches in AP over 15% and MAP over 10% on average.

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arXiv2023

Defining and executing temporal constraints for evaluating engineering artifact compliance

Engineering processes for safety-critical systems describe the steps and sequence that guide engineers from refining user requirements into executable code, as well as producing the artifacts, traces, and evidence that the resulting system is of high quality. Process compliance focuses on ensuring that the actual engineering work is followed as closely as possible to the described engineering processes. To this end, temporal constraints describe the ideal sequence of steps. Checking these process constraints, however, is still a daunting task that requires a lot of manual work and delivers feedback to engineers only late in the process. In this paper, we present an automated constraint checking approach that can incrementally check temporal constraints across inter-related engineering artifacts upon every artifact change thereby enabling timely feedback to engineers on process deviations. Temporal constraints are expressed in the Object Constraint Language (OCL) extended with operators from Linear Temporal Logic (LTL). We demonstrate the ability of our approach to support a wide range of higher level temporal patterns. We further show that for constraints in an industry-derived use case, the average evaluation time for a single constraint takes around 0.2 milliseconds.

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arXiv2023

Validation-Driven Development

Formal methods play a fundamental role in asserting the correctness of requirements specifications. However, historically, formal method experts have primarily focused on verifying those specifications. Although equally important, validation of requirements specifications often takes the back seat. This paper introduces a validation-driven development (VDD) process that prioritizes validating requirements in formal development. The VDD process is built upon problem frames - a requirements analysis approach - and validation obligations (VOs) - the concept of breaking down the overall validation of a specification and linking it to refinement steps. The effectiveness of the VDD process is demonstrated through a case study in the aviation industry.

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arXiv2022

Using Consensual Biterms from Text Structures of Requirements and Code to Improve IR-Based Traceability Recovery

Traceability approves trace links among software artifacts based on whether two artifacts are related by system functionalities. The traces are valuable for software development, but are difficult to obtain manually. To cope with the costly and fallible manual recovery, automated approaches are proposed to recover traces through textual similarities among software artifacts, such as those based on Information Retrieval (IR). However, the low quality & quantity of artifact texts negatively impact the calculated IR values, thus greatly hindering the performance of IR-based approaches. In this study, we propose to extract co-occurred word pairs from the text structures of both requirements and code (i.e., consensual biterms) to improve IR-based traceability recovery. We first collect a set of biterms based on the part-of-speech of requirement texts, and then filter them through the code texts. We then use these consensual biterms to both enrich the input corpus for IR techniques and enhance the calculations of IR values. A nine-system-based evaluation shows that in general, when solely used to enhance IR techniques, our approach can outperform pure IR-based approaches and another baseline by 21.9% & 21.8% in AP, and 9.3% & 7.2% in MAP, respectively. Moreover, when used to collaborate with another enhancing strategy from different perspectives, it can outperform this baseline by 5.9% in AP and 4.8% in MAP.

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arXiv2022

Trace Refinement in B and Event-B

Traces are used to show whether a model complies with the intended behavior. A modeler can use trace checking to ensure the preservation of the model behavior during the refinement process. In this paper, we present a trace refinement technique and tool called BERT that allows designers to ensure the behavioral integrity of high-level traces at the concrete level. The proposed technique is evaluated within the context of the B and Event-B methods on industrial-strength case studies from the automotive domain.

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arXiv2022

Balanced Knowledge Distribution among Software Development Teams -- Observations from Open-Source and Closed-Source Software Development

In software development teams, developer turnover is among the primary reasons for project failures as it leads to a great void of knowledge and strain for the newcomers. Unfortunately, no established methods exist to measure how knowledge is distributed among development teams. Knowing how this knowledge evolves and is owned by key developers in a project helps managers reduce risks caused by turnover. To this end, this paper introduces a novel, realistic representation of domain knowledge distribution: the ConceptRealm. To construct the ConceptRealm, we employ a latent Dirichlet allocation model to represent textual features obtained from 300k issues and 1.3M comments from 518 open-source projects. We analyze whether the newly emerged issues and developers share similar concepts or how aligned the developers' concepts are with the team over time. We also investigate the impact of leaving members on the frequency of concepts. Finally, we evaluate the soundness of our approach to closed-source software, thus allowing the validation of the results from a practical standpoint. We find out that the ConceptRealm can represent the high-level domain knowledge within a team and can be utilized to predict the alignment of developers with issues. We also observe that projects exhibit many keepers independent of project maturity and that abruptly leaving keepers harm the team's concept familiarity.

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arXiv2022

Application of Validation Obligations to Security Concerns

Our lives become increasingly dependent on safety- and security-critical systems, so formal techniques are advocated for engineering such systems. One of such techniques is validation obligations that enable formalizing requirements early in development to ensure their correctness. Furthermore, validation obligations help hold requirements consistent in an evolving model and create assurances about the model's completeness. Although initially proposed for safety properties, this paper shows how the technique of validation obligations enables us to also reason about security concerns through an example from the medical domain.

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arXiv2022

Semantic Clone Detection via Probabilistic Software Modeling

Semantic clone detection is the process of finding program elements with similar or equal runtime behavior. For example, detecting the semantic equality between the recursive and iterative implementation of the factorial computation. Semantic clone detection is the de facto technical boundary of clone detectors. In recent years, this boundary has been tested using interesting new approaches. This article contributes a semantic clone detection approach that detects clones that have 0% syntactic similarity. We present Semantic Clone Detection via Probabilistic Software Modeling (SCD-PSM) as a stable and precise solution to semantic clone detection. PSM builds a probabilistic model of a program that is capable of evaluating and generating runtime data. SCD-PSM leverages this model and its model elements for finding behaviorally equal model elements. This behavioral equality is then generalized to semantic equality of the original program elements. It uses the likelihood between model elements as a distance metric. Then, it employs the likelihood ratio significance test to decide whether this distance is significant, given a pre-specified and controllable false-positive rate. The output of SCD-PSM are pairs of program elements (i.e., methods), their distance, and a decision on whether they are clones or not. SCD-PSM yields excellent results with a Matthews Correlation Coefficient greater than 0.9. These results are obtained on classical semantic clone detection problems such as detecting recursive and iterative versions of an algorithm, but also on complex problems used in coding competitions.

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arXiv2021

Do Communities in Developer Interaction Networks align with Subsystem Developer Teams? An Empirical Study of Open Source Systems

Studies over the past decade demonstrated that developers contributing to open source software systems tend to self-organize in "emerging" communities. This latent community structure has a significant impact on software quality. While several approaches address the analysis of developer interaction networks, the question of whether these emerging communities align with the developer teams working on various subsystems remains unanswered. Work on socio-technical congruence implies that people that work on the same task or artifact need to coordinate and thus communicate, potentially forming stronger interaction ties. Our empirical study of 10 open source projects revealed that developer communities change considerably across a project's lifetime (hence implying that relevant relations between developers change) and that their alignment with subsystem developer teams is mostly low. However, subsystems teams tend to remain more stable. These insights are useful for practitioners and researchers to better understand developer interaction structure of open source systems.

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arXiv2021

Team-oriented Consistency Checking of Heterogeneous Engineering Artifacts

Consistency checking of interdependent heterogeneous engineering artifacts, such as requirements, specifications, and code, is a challenging task in large-scale engineering projects. The lack of team-oriented solutions allowing a multitude of project stakeholders to collaborate in a consistent manner is thus becoming a critical problem. In this context, this work proposes an approach for team-oriented consistency checking of collaboratively developed heterogeneous engineering artifacts.

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arXiv2021

TaskAllocator: A Recommendation Approach for Role-based Tasks Allocation in Agile Software Development

In this paper, we propose a recommendation approach -- TaskAllocator -- in order to predict the assignment of incoming tasks to potential befitting roles. The proposed approach, identifying team roles rather than individual persons, allows project managers to perform better tasks allocation in case the individual developers are over-utilized or moved on to different roles/projects. We evaluated our approach on ten agile case study projects obtained from the Taiga.io repository. In order to determine the TaskAllocator's performance, we have conducted a benchmark study by comparing it with contemporary machine learning models. The applicability of the TaskAllocator was assessed through a plugin that can be integrated with JIRA and provides recommendations about suitable roles whenever a new task is added to the project. Lastly, the source code of the plugin and the dataset employed have been made public.

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arXiv2021

Validation Obligations: A Novel Approach to Check Compliance between Requirements and their Formal Specification

Traditionally, practitioners use formal methods pre-dominately for one half of the quality-assurance process: verification (do we build the software right?). The other half -- validation (do we build the right software?) -- has been given comparatively little attention. While verification is the core of refinement-based formal methods, where each new refinement step must preserve all properties of its abstract model, validation is usually postponed until the latest stages of the development, when models can be automatically executed. Thus mistakes in requirements or in their interpretation are caught too late: usually at the end of the development process. In this paper, we present a novel approach to check compliance between requirements and their formal refinement-based specification during the earlier stages of development. Our proposed approach -- "validation obligations" -- is based on the simple idea that both verification and validation are an integral part of all refinement steps of a system.

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