Design‐code traceability for object‐oriented systems

Traceability is a key issue to ensure consistency among software artifacts of subsequent phases of the development cycle. However, few works have so far addressed the theme of tracing object oriented (OO) design into its implementation and evolving it. This paper presents an approach to checking the compliance of OO design with respect to source code and support its evolution. The process works on design artifacts expressed in the OMT (Object Modeling Technique) notation and accepts C++ source code. It recovers an “as is” design from the code, compares the recovered design with the actual design and helps the user to deal with inconsistencies. The recovery process exploits the edit distance computation and the maximum match algorithm to determine traceability links between design and code. The output is a similarity measure associated to design‐code class pairs, which can be classified as matched and unmatched by means of a maximum likelihood threshold. A graphic display of the design with different green levels associated to different levels of match and red for the unmatched classes is provided as a support to update the design and improve its traceability to the code.     

基于开发者协作关系和信息检索的需求跟踪系统

目前自动化需求跟踪的研究广泛使用文本信息检索技术。然而信息检索会遗漏一些文本不相似但是实际相关的软件制品,导致自动化跟踪的精度不高。针对上述问题,提出利用开发者协作关系来进行优化,研发了基于开发者协作关系和信息检索的需求跟踪系统。该系统在进行需求跟踪时,首先用信息检索推荐与需求文本上相似的代码,然后从代码提交日志中挖掘开发者协作关系,根据开发者协作关系再推荐相关代码,用户根据两次推荐的结果确定正确的需求代码跟踪关系。试验结果表明该系统能够找到信息检索遗漏的需求跟踪关系,能够提高自动化跟踪的准确性,节省跟踪时间。     

Estimating the number of remaining links in traceability recovery

Although very important in software engineering, establishing traceability links between software artifacts is extremely tedious, error-prone, and it requires significant effort. Even when approaches for automated traceability recovery exist, these provide the requirements analyst with a, usually very long, ranked list of candidate links that needs to be manually inspected. In this paper we introduce an approach called Estimation of the Number of Remaining Links (ENRL) which aims at estimating, via Machine Learning (ML) classifiers, the number of remaining positive links in a ranked list of candidate traceability links produced by a Natural Language Processing techniques-based recovery approach. We have evaluated the accuracy of the ENRL approach by considering several ML classifiers and NLP techniques on three datasets from industry and academia, and concerning traceability links among different kinds of software artifacts including requirements, use cases, design documents, source code, and test cases. Results from our study indicate that: (i) specific estimation models are able to provide accurate estimates of the number of remaining positive links; (ii) the estimation accuracy depends on the choice of the NLP technique, and (iii) univariate estimation models outperform multivariate ones.     

基于软件结构的文档与代码间可追踪性研究

正确建立软件文档与代码间的可追踪关系对程序理解、软件维护等非常重要。近年来,软件文档与代码间的可追踪性研究大多基于文本词汇相似度,没有充分利用软件文档和代码所蕴含的结构信息,针对这一问题提出了将软件结构信息与信息检索模型相结合进行文档与代码间可追踪性分析的方法。通过对文档和代码结构信息的分析,改善预处理效果,优化相似度计算过程,进而提高整体方法的有效性。实验结果表明,该方法比单纯基于信息检索的方法在查全率和查准率上都有所提高,而且能提取到更多的可追踪性链。     

功能需求到测试用例的可追溯性研究

软件开发主要由需求收集、设计、实现、测试和维护等几个阶段构成,其中维护始终是主要开销。在维护阶段,开发人员必须理解程序才能定位缺陷,而系统的需求和源代码、测试用例等之间的可追溯性连接能帮助减少开发人员在理解程序时的工作量。研究现有的功能定位技术和可追溯性方法,通过对现有方法的改进,提出了一种集成动态执行信息和IR技术的方案来建立需求到测试用例的可追溯性连接,用以辅助开发人员在维护阶段的工作。     

A scoped approach to traceability management

Traceability is the ability to describe and follow the life of a software artifact and a means for modeling the relations between software artifacts in an explicit way. Traceability has been successfully applied in many software engineering communities and has recently been adopted to document the transition among requirements, architecture and implementation. We present an approach to customize traceability to the situation at hand. Instead of automating tracing, or representing all possible traces, we scope the traces to be maintained to the activities stakeholders must carry out. We define core traceability paths, consisting of essential traceability links required to support the activities. We illustrate the approach through two examples: product derivation in software product lines, and release planning in software process management. By using a running software product line example, we explain why the core traceability paths identified are needed when navigating from feature to structural models and from family to product level and backward between models used in software product derivation. A feasibility study in release planning carried out in an industrial setting further illustrates the use of core traceability paths during production and measures the increase in performance of the development processes supported by our approach. These examples show that our approach can be successfully used to support both product and process traceability in a pragmatic yet efficient way.     

Applying a smoothing filter to improve IR-based traceability recovery processes: An empirical investigation

ContextTraceability relations among software artifacts often tend to be missing, outdated, or lost. For this reason, various traceability recovery approaches—based on Information Retrieval (IR) techniques—have been proposed. The performances of such approaches are often influenced by “noise” contained in software artifacts (e.g., recurring words in document templates or other words that do not contribute to the retrieval itself).AimAs a complement and alternative to stop word removal approaches, this paper proposes the use of a smoothing filter to remove “noise” from the textual corpus of artifacts to be traced.MethodWe evaluate the effect of a smoothing filter in traceability recovery tasks involving different kinds of artifacts from five software projects, and applying three different IR methods, namely Vector Space Models, Latent Semantic Indexing, and Jensen–Shannon similarity model.ResultsOur study indicates that, with the exception of some specific kinds of artifacts (i.e., tracing test cases to source code) the proposed approach is able to significantly improve the performances of traceability recovery, and to remove “noise” that simple stop word filters cannot remove.ConclusionsThe obtained results not only help to develop traceability recovery approaches able to work in presence of noisy artifacts, but also suggest that smoothing filters can be used to improve performances of other software engineering approaches based on textual analysis.     

DCTracVis: a system retrieving and visualizing traceability links between source code and documentation

It is well recognized that traceability links between software artifacts provide crucial support in comprehension, efficient development, and effective management of a software system. However, automated traceability systems to date have been faced with two major open research challenges: how to extract traceability links with both high precision and high recall, and how to efficiently visualize links for complex systems because of scalability and visual clutter issues. To overcome the two challenges, we designed and developed a traceability system, DCTracVis. This system employs an approach that combines three supporting techniques, regular expressions, key phrases, and clustering, with information retrieval (IR) models to improve the performance of automated traceability recovery between documents and source code. This combination approach takes advantage of the strengths of the three techniques to ameliorate limitations of IR models. Our experimental results show that our approach improves the performance of IR models, increases the precision of retrieved links, and recovers more correct links than IR alone. After having retrieved high-quality traceability links, DCTracVis then utilizes a new approach that combines treemap and hierarchical tree techniques to reduce visual clutter and to allow the visualization of the global structure of traces and a detailed overview of each trace, while still being highly scalable and interactive. Usability evaluation results show that our approach can effectively and efficiently help software developers comprehend, browse, and maintain large numbers of links.     

多层次的软件演化追踪关系逆向恢复

软件资产追踪关系逆向恢复是软件维护和逆向工程领域的一个重要研究内容。然而,大多数现有的资产追踪研究都是针对同一软件版本内的追踪关系。与已有的研究工作不同,文中主要关注多个层次(变更文档层、配置管理层、实现代码层)上的演化信息之间的追踪关系逆向恢复。这些演化信息之间追踪关系的恢复对于理解软件演化和维护过程、学习并借鉴软件维护知识都具有重要的意义。针对不同层次演化信息的特点,提出了一种结合关键字检索和启发式规则的演化信息追踪关系逆向恢复方法,并针对一个开源软件系统的演化过程进行了实验分析。     

Event-based traceability for managing evolutionary change

Although the benefits of requirements traceability are widely recognized, the actual practice of maintaining a traceability scheme is not always entirely successful. The traceability infrastructure underlying a software system tends to erode over its lifetime, as time-pressured practitioners fail to consistently maintain links and update impacted artifacts each time a change occurs, even with the support of automated systems. This paper proposes a new method of traceability based upon event-notification and is applicable even in a heterogeneous and globally distributed development environment. Traceable artifacts are no longer tightly coupled but are linked through an event service, which creates an environment in which change is handled more efficiently, and artifacts and their related links are maintained in a restorable state. The method also supports enhanced project management for the process of updating and maintaining the system artifacts.     

TracIMo: a traceability introduction methodology and its evaluation in an Agile development team

Requirements Engineering - Software traceability, the ability to relate software development artifacts such as requirements, design models and code to each other, is an important aspect in software...     

Enhancing software artefact traceability recovery processes with link count information

ContextThe intensive human effort needed to manually manage traceability information has increased the interest in using semi-automated traceability recovery techniques. In particular, Information Retrieval (IR) techniques have been largely employed in the last ten years to partially automate the traceability recovery process.AimPrevious studies mainly focused on the analysis of the performances of IR-based traceability recovery methods and several enhancing strategies have been proposed to improve their accuracy. Very few papers investigate how developers (i) use IR-based traceability recovery tools and (ii) analyse the list of suggested links to validate correct links or discard false positives. We focus on this issue and suggest exploiting link count information in IR-based traceability recovery tools to improve the performances of the developers during a traceability recovery process.MethodTwo empirical studies have been conducted to evaluate the usefulness of link count information. The two studies involved 135 University students that had to perform (with and without link count information) traceability recovery tasks on two software project repositories. Then, we evaluated the quality of the recovered traceability links in terms of links correctly and erroneously traced by the students.ResultsThe results achieved indicate that the use of link count information significantly increases the number of correct links identified by the participants.ConclusionsThe results can be used to derive guidelines on how to effectively use traceability recovery approaches and tools proposed in the literature.     

Maintaining traceability links during object‐oriented software evolution

This paper presents a method to build and maintain traceability links and properties of a set of object‐oriented software releases. The method recovers an ‘as is’ design from C++ software releases, compares recovered designs at the class interface level, and helps the user to deal with inconsistencies by pointing out regions of code where differences are concentrated. The comparison step exploits edit distance and a maximum match algorithm. The method has been experimented with on two freely available C++ systems. Results as well as examples of applications to the visualization of the traceability information and to the estimation of the size of changes during maintenance are reported in the paper. Copyright © 2001 John Wiley & Sons, Ltd.     

Recovering test-to-code traceability using slicing and textual analysis

Test suites are a valuable source of up-to-date documentation as developers continuously modify them to reflect changes in the production code and preserve an effective regression suite. While maintaining traceability links between unit test and the classes under test can be useful to selectively retest code after a change, the value of having traceability links goes far beyond this potential savings. One key use is to help developers better comprehend the dependencies between tests and classes and help maintain consistency during refactoring. Despite its importance, test-to-code traceability is not common in software development and, when needed, traceability information has to be recovered during software development and evolution. We propose an advanced approach, named SCOTCH+ (Source code and COncept based Test to Code traceability Hunter), to support the developer during the identification of links between unit tests and tested classes. Given a test class, represented by a JUnit class, the approach first exploits dynamic slicing to identify a set of candidate tested classes. Then, external and internal textual information associated with the classes retrieved by slicing is analyzed to refine this set of classes and identify the final set of candidate tested classes. The external information is derived from the analysis of the class name, while internal information is derived from identifiers and comments. The approach is evaluated on five software systems. The results indicate that the accuracy of the proposed approach far exceeds the leading techniques found in the literature.     

Graph-based traceability: a comprehensive approach

In recent years, traceability has been globally accepted as being a key success factor of software development projects. However, the multitude of different, poorly integrated taxonomies, approaches and technologies impedes the application of traceability techniques in practice. This paper presents a comprehensive view on traceability, pertaining to the whole software development process. Based on the state of the art, the field is structured according to six specific activities related to traceability as follows: definition, recording, identification, maintenance, retrieval, and utilization. Using graph technology, a comprehensive and seamless approach for supporting these activities is derived, combining them in one single conceptual framework. This approach supports the definition of metamodels for traceability information, recording of traceability information in graph-based repositories, identification and maintenance of traceability relationships using transformations, as well as retrieval and utilization of traceability information using a graph query language. The approach presented here is applied in the context of the ReDSeeDS project (Requirements Driven Software Development System) that aims at requirements-based software reuse. ReDSeeDS makes use of traceability information to determine potentially reusable architectures, design, or code artifacts based on a given set of reusable requirements. The project provides case studies from different domains for the validation of the approach.     

面向软件安全性需求分析过程的追踪模型

追踪性即关联一些制品及其中各种相关要素的机制或能力。安全关键系统开发不仅包括一般系统的开发过程,更重要的是必需要有独立的安全性分析,建立并验证系统的安全性需求。目前针对安全性分析过程的追踪性研究较少。安全相关标准如ARP-4761和DO 178C等提供了安全性分析过程的指导意见,然而其由于涉及的概念和方法很多,因此在实际应用和研究中常会忽略对一些关键信息的追踪。此外,软件安全性需求分析不仅应考虑系统到软件的安全性分析,还应考虑软件到系统的安全性分析。面向软件安全性需求分析过程建立安全性相关信息的双向追踪,有助于了解安全性需求的前因后果,为验证工作和影响分析提供便利。参照标准,构建面向软件安全性需求分析过程的追踪模型。     

Semi-automated architectural abstraction specifications for supporting software evolution

In this paper we present an approach for supporting the semi-automated architectural abstraction of architectural models throughout the software life-cycle. It addresses the problem that the design and implementation of a software system often drift apart as software systems evolve, leading to architectural knowledge evaporation. Our approach provides concepts and tool support for the semi-automatic abstraction of architecture component and connector views from implemented systems and keeping the abstracted architecture models up-to-date during software evolution. In particular, we propose architecture abstraction concepts that are supported through a domain-specific language (DSL). Our main focus is on providing architectural abstraction specifications in the DSL that only need to be changed, if the architecture changes, but can tolerate non-architectural changes in the underlying source code. Once the software architect has defined an architectural abstraction in the DSL, we can automatically generate architectural component views from the source code using model-driven development (MDD) techniques and check whether architectural design constraints are fulfilled by these models. Our approach supports the automatic generation of traceability links between source code elements and architectural abstractions using MDD techniques to enable software architects to easily link between components and the source code elements that realize them. It enables software architects to compare different versions of the generated architectural component view with each other. We evaluate our research results by studying the evolution of architectural abstractions in different consecutive versions of five open source systems and by analyzing the performance of our approach in these cases.     

利用语义模型的需求可跟踪性的实现

需求的可跟踪性——一种可以把需求规格说明和其他在软件系统生命周期产生的产品联系起来的性能，很早就已经广泛地被认为是高效软件工程管理和软件系统质量的关键因素。该文提出了一种基于语义模型的方法，把从需求获取到编辑SRS的这样一个过程划分成若干阶段，并找出每一阶段的语义元素和联系。