ICSE 2011 Workshops
33rd International Conference on Software Engineering
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Sixth International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE 2011), May 23, 2011, Waikiki, Honolulu, HI, USA

TEFSE 2011 – Proceedings

Contents - Abstracts - Authors

Sixth International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE 2011)


Title Page

The Sixth International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE 2011) will bring together researchers and practitioners to examine the challenges of recovering and maintaining traceability for the myriad forms of software engineering artifacts, ranging from user needs to models to source code.
The objective of the 6th edition of TEFSE is to build on the work the traceability research community has completed in identifying the open traceability challenges. In particular, it is intended to be a working event focused on discussing the main problems related to software artifact traceability and propose possible solutions for such problems. Moreover, the workshop also aims at identifying key issues concerning the importance of maintaining the traceability information during software development, to further improve the cooperation between academia and industry and to facilitate technology transfer.

Full Papers

Traceability Research: Taking the Next Steps
Jane Cleland-Huang
(DePaul University, USA)

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Source Code Indexing for Automated Tracing
Anas Mahmoud and Nan Niu
(Mississippi State University, USA)
Requirements-to-source-code traceability employs information retrieval (IR) methods to automatically link requirements to the source code that implements them. A crucial step in this process is indexing, where partial and important information from the software artifacts is converted into a representation that is compatible with the underlying IR model. Source code demands special attention in the indexing process. In this paper, we investigate source code indexing for supporting automatic traceability. We introduce a feature diagram that captures the key components and their relationships in the domain of source code indexing. We then present an experiment to examine the features of the diagram and their dependencies. Results show that utilizing comments has a significant effect on traceability link generation, and stemming is required when comments are considered.

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Traceability between Function Point and Source Code
Paulo José Azevedo Vianna Ferreira and Márcio De Oliveira Barros
(UNIRIO, Brazil)
Software development can achieve interesting benefits through the use of requirements traceability, including improved program comprehension, easier maintenance, component reuse, impact analysis, and measure of project progress and completeness. On the other hand, while the cost of a new IS can be estimated by applying Function Point Analysis, this technique has limited application on maintenance. By determining the impact of changing a given set of features, IS development organizations can build a clear understanding of the effort that these changes will require. In this paper, we propose a technique which uses traceability to build a bridge between function points and source code. We believe that this technique can support negotiations between IS development organizations and their clients regarding changes to Information Systems.

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Grand Challenges, Benchmarks, and TraceLab: Developing Infrastructure for the Software Traceability Research Community
Jane Cleland-Huang, Adam Czauderna, Alex Dekhtyar, Olly Gotel, Jane Huffman Hayes, Ed Keenan, Greg Leach, Jonathan Maletic, Denys Poshyvanyk, Yonghee Shin, Andrea Zisman, Giuliano Antoniol, Brian Berenbach, Alexander Egyed, and Patrick Maeder
(DePaul University, USA; Cal Poly, USA; University of Kentucky, USA; Kent State University, USA; College of William and Mary, USA; City University London, UK; École Polytechnique Montréal, Canada; Siemens Corporate Research, USA; Johannes Kepler University, Austria)

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Traceclipse: An Eclipse Plug-in for Traceability Link Recovery and Management
Samuel Klock, Malcom Gethers, Bogdan Dit, and Denys Poshyvanyk
(College of William and Mary, USA)
Traceability link recovery is an active research area in software engineering with a number of open research questions and challenges, due to the substantial costs and challenges associated with software maintenance. We propose Traceclipse, an Eclipse plug-in that integrates some similar characteristics of traceability link recovery techniques in one easy-to-use suite. The tool enables software developers to specify, view, and manipulate traceability links within Eclipse and it provides an API through which recovery techniques may be added, specified, and run within an integrated development environment. The paper also presents initial case studies aimed at evaluating the proposed plug-in.

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Recovering Traceability Links between Source Code and Fixed Bugs via Patch Analysis
Christopher S. Corley, Nicholas A. Kraft, Letha H. Etzkorn, and Stacy K. Lukins
(University of North Alabama, USA; The University of Alabama, USA; The University of Alabama at Huntsville, USA)
Traceability links can be recovered using data mined from a revision control system, such as CVS, and an issue tracking system, such as Bugzilla. Existing approaches to recover links between a bug and the methods changed to fix the bug rely on the presence of the bug's identifier in a CVS log message. In this paper we present an approach that relies instead on the presence of a patch in the issue report for the bug. That is, rather than analyzing deltas retrieved from CVS to recover links, our approach analyzes patches retrieved from Bugzilla. We use BugTrace, the tool implementing our approach, to conduct a case study in which we compare the links recovered by our approach to links recovered by manual inspection. The results of the case study support the efficacy of our approach. After describing the limitations of our case study, we conclude by reviewing closely related work and suggesting possible future work.

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Short Papers

Tracing Requirements for Adaptive Systems using Claims
Kristopher Welsh, Nelly Bencomo, and Peter Sawyer
(Lancaster University, UK; INRIA Paris, France)
The complexity of environments faced by dynamically adaptive systems means that the RE process will often be iterative with analysts revisiting the system specifications based on new environmental understanding product of experiences with experimental deployments, or even after final deployments. An ability to trace backwards to an identified environmental assumption, and to trace forwards to find the areas of a DAS's specification that are affected by a change in environmental understanding aids in supporting this necessarily iterative RE process. This paper demonstrates how claims, a record in an i* SR model of an assumption made, can be used as markers for areas of uncertainty in a DAS specification. The paper demonstrates backward tracing using claims to identify faulty environmental understanding, and forward tracing to allow generation of new behaviour in the form of policy adaptations and models for transitioning the running system.

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Formalizing Traceability Relations for Product Lines
Luis C. Lamb, Waraporn Jirapanthong, and Andrea Zisman
(Federal University of Rio Grande do Sul, Brazil; Dhurakij Pundit University, Thailand; City University London, UK)
Traceability is considered an important activity during the development of software systems. Despite the various classifications that have been proposed for different types of traceability relations, there is still a lack of standard semantic definitions for traceability relations. In this paper, we present an ontology-based formalism for semantic representation of various types of traceability relations for product line systems and associations between these various types of traceability relations.

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Improving Traceability Link Recovery Methods through Software Artifact Summarization
Jairo Aponte and Andrian Marcus
(Universidad Nacional de Colombia, Colombia; Wayne State University, USA)
Analyzing candidate traceability links is a difficult, time consuming and error prone task, as it usually requires a detailed study of a long list of software artifacts of various kinds. One option to alleviate this problem is to select the most important features of the software artifacts that the developers would investigate. We discuss in this position paper how text summarization techniques could be used to address this problem. The potential gains in using summaries are both in terms of time and correctness of the traceability link recovery process.

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Software Verification and Validation Research Laboratory (SVVRL) of the University of Kentucky: Traceability Challenge 2011: Language Translation
Jane Huffman Hayes, Hakim Sultanov, Wei-Keat Kong, and Wenbin Li
(University of Kentucky, USA)
We present the process and methods applied in undertaking the Traceability Challenge in addressing Grand Challenge C-GC1 – Trace recovery. The Information Retrieval methods implemented in REquirements TRacing On target .NET (RETRO.NET) were applied to the tracing of the eTour and EasyClinic datasets. Our work focused on the nuances of native language (Italian, English). Datasets were augmented with additional terms derived from splitting function and variable names with Camel-Back notation and using the Google Translate API to translate Italian terms into English. Results based on the provided answer set show that the augmented datasets significantly improved recall and precision for one of the datasets.

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Creating Operational Profiles of Software Systems by Transforming their Log Files to Directed Cyclic Graphs
Meiyappan Nagappan and Brian Robinson
(North Carolina State University, USA; ABB Corporate Research, USA)
Most log files are of one format - a flat file with the events of execution recorded one after the other. Each line in the file contains at least a timestamp, a combination of one or more event identifiers, and the actual log message with information of which event was executed and what the values for the dynamic parameters of that event are. Since log files have this trace information, we can use it for many purposes, such as operational profiling and anomalous execution path detection. However the current flat file format of a log file is very unintuitive to detect the existence of a repeating pattern. In this paper we propose a transformation of the current serial order format of a log file to a directed cyclic graph (such as a non-finite state machine) format and how the operational profile of a system can be built from this representation of the log file. We built a tool (in C++), that transforms a log file with a set of log events in a serial order to an adjacency matrix for the resulting graphical representation. We can then easily apply existing graph theory based algorithms on the adjacency matrix to analyze the log file of the system. The directed cyclic graph and the analysis of it can be visualized by rendering the adjacency matrix with graph visualization tools, like Graphviz.

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Towards a Model of Analyst Effort for Traceability Research
Alex Dekhtyar, Jane Huffman Hayes, and Matt Smith
(California Polytechnic State University, USA; University of Kentucky, USA)
This paper posits that a theoretical model of analyst effort in tracing tasks is necessary to assist with study of the analyst. Specifically, it is clear from prior work by numerous research groups that the important factors in such a model are: the amount of time it takes for an analyst to vet a given candidate link and the amount of time it takes an analyst to find a missing link. This paper introduces a theoretical model of analyst effort as well as a simplified model. A number of simulations were undertaken in order to build effort curves to assist in evaluating numerous tracing scenarios, such as determining at what point in time an analyst should switch from vetting candidate links to manually searching for links not in the candidate list.

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A Rich Traceability Model for Social Interactions
Maurício Serrano and Julio Cesar Sampaio do Prado Leite
(Pontifícia Universidade Católica do Rio de Janeiro, Brazil)
In 1993, Goguen published a research note addressing the social issues in Requirements Engineering. He identified in the requirements process three major social groups: the client organization; the requirements team; and the development team. However, nowadays there is a lack of technological support that traces requirements to social issues on the requirements team or development team. From early published traceability metamodels to current requirements traceability literature, the client organization and the stakeholders are first-class citizens, but the software engineers and the interactions between these groups are not. In this paper we present a partially formalized RichPicture traceability model to fill this gap. ITrace is a flexible model to weave together the social network graph, the information sources graph, the social interactions graph, and the Requirements Engineering artifacts evolution graph. We empirically developed our traceability model tracking a Transparency catalogue evolution. We also compare our model structure to Contribution Structures.

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On the Use of Eye Tracking in Software Traceability
Bonita Sharif and Huzefa Kagdi
(Ohio University, USA; Winston Salem State University, USA)
The paper advocates for the induction of eye tracking technology in software traceability and takes a position that the use of eye tracking metrics can contribute to several software traceability tasks. The authors posit that the role of eye tracking is not simply restricted to an instrument for empirical studies, but also could extend to providing a foundation of a new software traceability methodology. Several scenarios where eye-tracking metrics could be meaningful are presented. The specific research directions include conducting empirical studies with eye-tracking metrics and replicating previously reported empirical studies, eye-tracking enabled traceability link recovery and management methodology, and visualization support.

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Analyzing the Role of Tags as Lightweight Traceability Links
Matthew L. Hale, Noah M. Jorgenson, and Rose F. Gamble
(University of Tulsa, USA)
Tagging offers a traceability mechanism for software development by connecting artifacts in a meaningful way. Our integrated courseware, SEREBRO, provides a framework of tools that capture conversation and artifact creation and modification throughout the software development lifecycle by student team members developing non-trivial software products in a Software Engineering course. Using a data driven approach, we investigate the use of lightweight tagging mechanisms applied by student software project teams and present some preliminary results of this investigation.

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Traceability Challenge 2011: Using TraceLab to Evaluate the Impact of Local versus Global IDF on Trace Retrieval
Adam Czauderna, Marek Gibiec, Greg Leach, Yubin Li, Yonghee Shin, Ed Keenan, and Jane Cleland-Huang
(DePaul University, USA)
Numerous trace retrieval algorithms incorporate the standard tf-idf (term frequency, inverse document frequency) technique to weight various terms. In this TEFSE challenge report we address Grand Challenge C-GC1 by comparing the effectiveness of computing idf based only on the local terms in the query, versus computing it based on general term usage as documented in the American National Corpus. We also address Grand Challenges L-GC1 and L-GC2 by setting ourselves the additional task of designing and conducting the experiments using the alpha-release of TraceLab. TraceLab is an experimental workbench which allows researchers to graphically model and execute a traceability experiment as a workflow of components. Results of the experiment show that the local idf approach exceeds or matches the global approach in all of the cases studied.

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