Software Traceability Research Articles

An Interview with Martin Robillard - 2024 SIGSOFT Awardee

Martin Robillard received the 2024 SIGSOFT Influential Educator Award for his significant contributions to hands-on software design education, including a textbook (Introduction to Software Design with Java) and a learner-focused software modeling tool (JetUML). He is currently a Professor in the School of Computer Science at McGill University, Montréal, Canada, he is a Distinguished Member of the ACM and a Fellow of the Alexander von Humboldt Foundation. He received his Ph.D. in Computer Science from the University of British Columbia. His research interests fall within the area of software engineering, focussing on human-centred software development. He was awarded six ACM SIGSOFT Distinguished Paper Awards for his work on recommendation systems, software traceability, and software documentation. Recently, he has been working on software documentation generation, test suite quality, and information privacy.

Covid-19: The impact of lockdown on the dispensing of hospital drugs to outpatients

In response to the COVID-19 pandemic, France was under lockdown for the first time from March 17 to May 10, 2020. The aim of this work is to study the impact of lockdown on outpatients’ visits to the hospital pharmacy to collect chronic medication, in order to highlight the pharmaceutical classes concerned and to assess whether a decrease in medication adherence could be observed. Retrospectively, using hospital dispensing traceability software, the dispensing of drugs during the eight weeks of lockdown was compared with that during the two eight-week periods before and after lockdown. Evolutions in the number of medicine lines dispensed and outpatient visits were analyzed over the three time periods, according to pharmaceutical classes. A specific analysis was performed between drugs only available at the hospital pharmacy and drugs available at both the community and hospital pharmacy. During lockdown, 67% of patients still came regularly, but a significant decrease in the average number of lines dispensed was observed. 15% of regular patients limited their visits during this period. Patients taking drugs available at both the community and hospital pharmacy were significantly more impacted than those taking drugs that could only be dispensed at the hospital pharmacy. On the other hand, age is not a factor associated with the restriction of visits. Lockdown affected the visits to the hospital pharmacy of at least one in ten regular outpatients. Sending hospital drugs to community pharmacies and the help of home health care providers limited therapeutic disruptions.

MTLink: Adaptive multi-task learning based pre-trained language model for traceability link recovery between issues and commits

Traceability links between issues and commits (issue-commit links recovery (ILR)) play a significant role in software maintenance tasks by enhancing developers’ observability in practice. Recent advancements in large language models, particularly pre-trained models, have improved the effectiveness of automated ILR. However, these models’ large parameter sizes and extended training time pose challenges in large software projects. Besides, existing methods often overlook the association and distinction among artifacts, leading to the generation of erroneous links. To mitigate these problems, this paper proposes a novel link recovery method called MTLink. It utilizes multi-teacher knowledge distillation (MTKD) to compress the model and employs an adaptive multi-task strategy to reduce information loss and improve link accuracy. Experiments are conducted on four open-source projects. The results show that (i) MTLink outperforms state-of-the-art methods; (ii) The multi-teacher knowledge distillation maintains accuracy despite model size reduction; (iii) The adaptive multi-task tracing method effectively handles confusion caused by similar artifacts and balances each task. In conclusion, MTLink offers an efficient solution for ILR in software traceability. The code is available at https://zenodo.org/records/10321150.

Why don’t we trace? A study on the barriers to software traceability in practice

Researchers have proposed numerous tools, methods, and techniques for establishing and maintaining software traceability. Despite its acknowledged importance, researchers argue that traceability is still “a sought-after, yet often elusive quality in software-intensive systems”. We have little evidence regarding how creating, managing, and using traceability links vary depending on factors such as organizational contexts, software development practices, and project types. We conduct an empirical study where software development practitioners express their perception regarding the value of software traceability. Via an online survey, 55 participants provided information related to their current traceability practices and needs. Furthermore, we interviewed 14 practitioners to gain a more in-depth understanding. Our study investigates the effect of two independent variables: the software development paradigm and the type of developed software system. Among the several identified findings, our analysis reveals that, although the traceability costs are an inhibitor for adopting more mature traceability practices, the respondents believe that the expected benefits still outweigh envisioned costs. Traceability is mainly performed manually: not only are automated trace retrieval tools scarce, but their offered automation is not expected to replace human involvement.

Graph-Based Keyphrase Extraction for Software Traceability in Source Code and Documentation Mapping

Natural Language Processing (NLP) forms the basis of several computational tasks. However, when applied to the software system’s, NLP provides several irrelevant features and the noise gets mixed up while extracting features. As the scale of software system’s increases, different metrics are needed to assess these systems. Diagrammatic and visual representation of the SE projects code forms an essential component of Source Code Analysis (SCA). These SE projects cannot be analyzed by traditional source code analysis methods nor can they be analyzed by traditional diagrammatic representation. Hence, there is a need to modify the traditional approaches in lieu of changing environments to reduce learning gap for the developers and traceability engineers. The traditional approaches fall short in addressing specific metrics in terms of document similarity and graph dependency approaches. In terms of source code analysis, the graph dependency graph can be used for finding the relevant key-terms and keyphrases as they occur not just intra-document but also inter-document. In this work, a similarity measure based on context is proposed which can be employed to find a traceability link between the source code metrics and API documents present in a package. Probabilistic graph-based keyphrase extraction approach is used for searching across the different project files.

Applications of natural language processing in software traceability: A systematic mapping study

A key part of software evolution and maintenance is the continuous integration from collaborative efforts, often resulting in complex traceability challenges between software artifacts: features and modules remain scattered in the source code, and traceability links become harder to recover. In this paper, we perform a systematic mapping study dealing with recent research recovering these links through information retrieval, with a particular focus on natural language processing (NLP).Our search strategy gathered a total of 96 papers in focus of our study, covering a period from 2013 to 2021. We conducted trend analysis on NLP techniques and tools involved, and traceability efforts (applying NLP) across the software development life cycle (SDLC). Based on our study, we have identified the following key issues, barriers, and setbacks: syntax convention, configuration, translation, explainability, properties representation, tacit knowledge dependency, scalability, and data availability.Based on these, we consolidated the following open challenges: representation similarity across artifacts, the effectiveness of NLP for traceability, and achieving scalable, adaptive, and explainable models. To address these challenges, we recommend a holistic framework for NLP solutions to achieve effective traceability and efforts in achieving interoperability and explainability in NLP models for traceability.

A Systematic Mapping Study on Quality Attribute Traceability

Quality attribute traceability (QAT), as a sub-discipline of software traceability, ensures that quality attributes are considered in all phases of software development. QAT is one of the most critical and challenging research areas in requirement engineering. In recent years, several studies have been conducted on quality attribute traceability. However, researchers in this field have problems to identifying the research status of this field due to the lack of a comprehensive secondary study that reveals research trends and gaps. Evidence-based software engineering (EBSE) proposes systematic mapping study (SMS) and systematic literature review (SLR) methods for secondary studies on software engineering. In this paper we use the semantically enhanced SMS method in the QAT research area. In order to improve SMS, we introduce a concept classification approach. In this approach by using a QAT domain ontology, the keywords classification process is improved. The most important innovation of this study is the presentation of the QAT research tree. This research tree has been created by gathering research topics identified in this field along with existing gaps. Identified research topics include “QAT Approach,” “QAT Development,” “QAT Model,” “QAT Framework,” and “QAT Algorithm”. The results also indicate that “QAT Frameworks” is a research trend, and most recent studies have focused on this topic. On the other hand, “Trace Maintenance” and “Trace Integrity” are the research gaps in this field. In this article, active researchers, journals, conferences and countries in the field of QAT are also introduced. We also introduce a set of tools that facilitate the SMS process.

Applications of Natural Language Processing in Software Traceability: A Systematic Mapping Study

Applications of Natural Language Processing in Software Traceability: A Systematic Mapping Study

A Multi-Objective Dragongfly Optimization for Requirement Traceability Establishment

Software traceability is a crucial component of various exact software development process and it is needed for various component certification and approval process in security system. With the tremendous growth of system, traceability is considered as a recent research topic. The traceability is a software development process that is indefinable. Various manufacturers struggle in predicting the appropriate traceability degree for their needs and produce the appropriate set of traceability links. The effort, cost, and discipline have to be maintained with tracking links with the faster development of software systems that are extremely higher. Also, it produces various advantages in practical realization; as it can be either ad-hoc or not properly defined traceability process, produces poor training or lack of effectual tool support. Moreover, the traceability process has to be determined as it can diminish the development effort and to enhance the development process. Generally, traceability research is based on empirical investigations for exploring newer investigational queries or to compute newer tracing methods. Here, this work concentrates on traceability, functional requirements, link establishment. It shows a better trade-off among the prevailing approaches.

Developing Critical Aerospace Embedded Systems with Distributed Teams Using Agile Methodologies

This work proposes a set of complementary practices to agile methodologies, aiming at adapting them to the development of critical aerospace embedded systems by distributed teams. To identify the main gaps in this context, two approaches are used. The first one confronts the main activities required by aerospace standards for the development of critical embedded systems with a set of compiled agile practices derived from a review of the most common agile methodologies. The second one confronts the same set of compiled agile practices with the main problems of distributed development. The two approaches resulted in the identification of four gaps related to software integration, software traceability, communication management, and organizational differences. One complementary practice is then proposed for each gap. Two case studies were performed to assess the gaps and evaluate the proposed practices. Both emulate the development of critical embedded systems by distributed teams using agile methodologies. The case studies were performed with and without the use of the complementary practices. The results confirmed three of the four identified gaps and pointed to a clear contribution of the complementary practices.

Fluorescent dot peen marking for insuring oil steel pipes traceability

“VKO “Simvol” designs and produces marking equipment, reading equipment and traceability software. Fluorescent dot-peen marking (FDMP) is an improved version of dot peen marking (DPM) technology. In FDPM technology information dots are filled with special material – fluorescent composition. Various fluorescent compositions provide high stability of marking in different aggressive media, such as moisture, salt and acid solutions, oils, lubricants or high temperatures. 2D barcode Data Matrix makes the marking machine readable, even if some of the dots are damaged.

Automated Fine Grained Traceability Links Recovery between High Level Requirements and Source Code Implementations

Software Traceability has been a matter of discussion in the Software Engineering community for a long time. The process of keeping and recover traces among software artifacts in any system represents a fundamental aspect to properly perform software maintenance tasks and requirements compliance verification. Furthermore, there exist application contexts where this becomes a mandatory process, for instance, banking and healthcare. Software traceability has dedicated efforts in proposing alternatives to recover lost traceability links in a coarse-grained and middle-grained detail by so far, however, proposed techniques are not enough to meet the desired levels of granularity in critical contexts. In this work we propose a fine-grained traceability algorithm designed to recover traces between high level requirements written in human natural language and source code statements where they are implemented. We tested our approach in four open-source healthcare systems to trace constraints requirements specified by the HIPAA law, and we evaluated the results as presented is this paper.

Empirical studies on software traceability: A mapping study

AbstractDuring the last decades, software traceability has been studied in a large number of studies, from different perspectives (e.g., how to create traces and what are its benefits). This large body of knowledge needs to be better explored and exploited by both practitioners and researchers: We need an overview of different aspects of traceability and a structured way to assess and compare existing work in order to extend it with new research or apply it in practice, Thus, we have conducted a secondary study on this large corpus of primary studies, focusing on empirical studies on software traceability, without setting any further restrictions in terms of investigating a specific domain or concrete artifacts. The study explores the goals of existing approaches and the empirical methods used for their evaluation. Its main contributions are the investigation of (a) the type of artifacts linked through traceability approaches; (b) the benefits of using artifact traceability approaches; (c) the ways of measuring their benefit; and (d) the research methods used. The results of the study suggest that (i) requirements artifacts are dominant in traceability; (ii) the research corpus focuses on the proposal of novel techniques for establishing traceability; and (iii) the main benefits are the improvement of software correctness and maintainability. Finally, although many studies include some empirical validation, there is still room for improvements and research methods that can be used more extensively. The obtained results are discussed under the prism of both researchers and practitioners and are compared against the state‐of‐the‐art.

A Testability and Observability Framework to Assure Traceability Requirements on System of Systems

The advance in the digital world has caused a growth of complexity in innovation. Traditional approaches to innovation, based on reductionism, face greater difficulties. That is why we have witnessed the growth of those known as System of Systems (SoS). There is a wide variety of methodologies and domains of application in the literature to form framed solutions in the context of SoS, but there is no unified consensus for its use and even less when it comes to agile environments of continuous integration and deployment in which traceability requirements are critical. In recent years, the need to have traceability software that continuously records and monitors the trace of the entities that interact with it has become an essential feature. In addition, over the years there has been evidence of errors caused by poor traceability control. Therefore, this document presents an agile framework that aims to guarantee the traceability of a SoS from the early stages. This framework unifies the discovery, development and operations, providing full coverage in the conformation of the solution. Finally, we present a case study as future work, which is based on the application of our framework on smart laboratories for assisted reproduction.

SST'19 - Software and Systems Traceability

Traceability is the ability to relate di erent artifacts during the development and operation of a system to each other. It enables program comprehension, change impact analysis, and facilitates the cooperation of engineers from di erent disciplines. The 10th International Workshop on Software and Systems Traceability (former International Workshop on Traceability in Emerging Forms of Software Engineering, TEFSE), explored the role and impact of traceability in modern software and systems development. The event brought together researchers and practitioners to examine the challenges of recovering, maintaining, and utilizing traceability for the myriad forms of software and systems engineering artifacts. SST'19 was a highly interactive working event focused on discussing the main problems related to software traceability in particular in the context of opportunities and challenges posed by the recent progress in Arti cial Intelligence techniques and proposing possible solutions for such problems.

ARES: An Agile Requirements Specification Process for Regulated Environments

Agile methods have provided significant contributions to Software Engineering. This work presents a new process for Software Requirements Specification, integrating Agile Properties and regulated environments, such as aviation, medical, nuclear and automotive, among others. The Software in Regulated Environments (SRE) involves plan-driven methods with needed documentation to ensure safety, reliability, security, and discipline. This paper proposes a balance between agile and plan-driven methods. We define a new process, which explores and investigates the usage of agile methods in SRE. The scope of this paper is Requirements Engineering, which is considered as a set of activities involved in the management, elicitation, documentation, and maintenance of requirements. The Adile Requirements Specification (ARES) process contains four methods, 13 activities, and some required artifacts to ensure compliance with the following six relevant Software Standards for regulated environments: RTCA DO-178C, IEC 62304:2015, ECSS-E-ST-40C, IEC 61508-3, ISO/IEC/IEEE 12207, and IAEA SSG-39. The process evaluation was performed using two experiments: a Cockpit Display System (CDS) and a Healthcare Information System (HIS). These experiments were measured with appropriate metrics to ensure improvements in Software Requirements Specification and traceability among artifacts. The experimental results revealed that the ARES process works better than the original Scrum for Software in Regulated Environments. The ARES process can also be integrated with traditional software life cycles (Waterfall, V, and Incremental and Iterative), when applied in the Requirements Engineering phase.

An enhanced latent semantic indexing with term frequency-inverse document frequency variant for software traceability

This paper proposes an improved Latent Semantic Indexing (LSI) with Term Frequency-Inverse Document Frequency (TFIDF) variant for software traceability. The main advantage of the method is the simplicity and accuracy of the algorithm such that it can produce high precision and recall. The accuracy of tracing precise links between software artefacts is achieved by feeding the LSI with TF-IFDF variant that halves the TF and IDF values, thus increases the probability of yielding precise links. To test the accuracy of the proposed method, two case studies were evaluated, namely Mushroom Management System (MMS) and Robotic Wheelchair System (RWS). The superiority of the proposed method over a conventional LSI is confirmed by 409.09%, 900.00%, and 620.00% improvements for precision, recall, and harmonic mean scores, respectively, in MMS case study, at cosine threshold of 0.94. It is anticipated that the method could be beneficial in the design of a practical and accurate system for retrieving precise software traceability links.

An Improved Approach based on Balanced Keyword Weight to Traceability Recovery

Software traceability recovery has become more and more important to the software life cycle recent days with the increasing complexity of software system. However, it is a tedious and error-prone task by manual. Many researchers have devoted themselves in building and predicting traceability links. In this paper, we approach a novel method to calculate text similarity and improve our results by a learning to rank method. And a couple of experiments are conducted to verify our method.

Training of Hand Rehabilitation Using Low Cost Exoskeleton and Vision-Based Game Interface

Motivating game-based training have the potential to improve therapy for people with neurological impairments. In recent years, the serious games have become extremely useful tools in rehabilitation field. They aim to stimulate the mobility of the body through an immersive experience that puts the user in interactive virtual environment. This paper is concerned about developing a customized augmented reality system for stroke rehabilitation. This will be done through integrating an interactive serious game interface with a hand exoskeleton device. This game-based rehabilitation system allows users to carry out physical rehabilitation therapies using a natural user interface based on Kinect’s skeletal tracking features and the electromyography (EMG) sensor. During game playing, the interactive user interface provides useful real-time feedback information such as the time required to grasp a desired dynamic virtual object, and the assigned score and thus the ability of the proposed system to provide a compensatory action regarding the dynamic behavior of the virtual target. The main goal of the developed virtual environment is to create positive influences on the rehabilitation process. Patient movement information and signals obtained from the developed exoskeleton device are used together to monitor the rehabilitation progress. The developed exoskeleton hand is a 3D printed low cost device suitable for grasping tasks that can be used even for domestic stroke patients. The developed exoskeleton device is not only a mechanical system able to perform the rehabilitation act but also it presents an effective tracking and traceability software solution. The EMG signals measured during hand motion are used to detect the intention of hand opening or closing which in turn will actuate the mechanical structure to accomplish the desired task. Parameters and results of patients’ exercises are stored and analyzed when needed to evaluate patients’ progress. The developed system is tested experimentally and it is able to restore the functions of the upper limb and mainly give patients more motivation to undergo the rehabilitation exercises.

Proposed Methodology using Design Development Research (DDR) Improving Traceability Model with Test Effort Estimation

Software maintenance is an important activity in software development lifecycle. Any changes during the maintenance phase have impact on cost and time. Thus, to minimize cost and time, a test effort estimation is crucial. This research will produce an automate tool that can help the software manager or a maintainer to search for the coverage artefact before and after a changes request. Software quality engineer can determine the test coverage from new changes which can support in cost estimation, effort and schedule estimation. In an ongoing research project, we are developing software traceability model with test effort estimation. In this paper we described the development methodology which includes 3 major phases: requirement analysis, design and development, and finally the usability analysis of the proposed model.