Abstract-This paper addresses the issues related to improving the overall quality of the dynamic candidate link generation for the requirements tracing process for Verification and Validation and Independent Verification and Validation analysts. The contribution of the paper is four-fold: We define goals for a tracing tool based on analyst responsibilities in the tracing process, we introduce several new measures for validating that the goals have been satisfied, we implement analyst feedback in the tracing process, and we present a prototype tool that we built, RETRO (REquirements TRacing On-target), to address these goals. We also present the results of a study used to assess RETRO's support of goals and goal elements that can be measured objectively.

This paper presents an approach for improving requirements tracing based on framing it as an information retrieval (IR) problem. Specifically, we focus on improving recall and precision in order to reduce the number of missed traceability links as well as to reduce the number of irrelevant potential links that an analyst has to examine when performing requirements tracing. Several IR algorithms were adapted and implemented to address this problem. We evaluated our algorithms by comparing their results and performance to those of a senior analyst who traced manually as well as with an existing requirements tracing tool. Initial results suggest that we can retrieve a significantly higher percentage of the links than analysts, even when using existing tools, and do so in much less time while achieving comparable signal-to-noise levels.

Abstract

The requirements traceability matrix (RTM) supports many software engineering and software verification and validation (V&V) activities such as change impact analysis, reverse engineering, reuse, and regression testing. The generation of RTMs is tedious and error-prone, though. Thus RTMs are often not generated or maintained. Automated techniques have been developed to generate candidate RTMs with some success. Automating the process can save time and potentially improve the quality of the results. When using RTMs to support the V&V of mission-or safety-critical systems, however, a human analyst is required to vet the candidate RTMs. The focus thus becomes the quality of the final RTM. This thesis introduces an experimental framework for studying human interactions with decision support software and reports on the results from a study which applies the framework to investigate how human analysts perform when vetting candidate RTMs generated by automated methods. Specifically, a study was undertaken at two universities and had 33 participants analyze RTMs of varying accuracy for a Java code formatter program. The study found that analyst behavior differs depending on the initial candidate RTM given to the analyst, but that all analysts tend to converge their final RTMs toward a hot spot in the recall-precision space.iv Acknowledgements

Software traceability is a sought-after, yet often elusive quality in software-intensive systems. Required in safety-critical systems by many certifying bodies, such as the USA Federal Aviation Authority, software traceability is an essential element of the software development process. In practice, traceability is often conducted in an ad-hoc, after-the-fact manner and, therefore, its benefits are not always fully realized. Over the past decade, researchers have focused on specific areas of the traceability problem, developing more sophisticated tooling, promoting strategic planning, applying information retrieval techniques capable of semi-automating the trace creation and maintenance process, developing new trace query languages and visualization techniques that use trace links, and applying traceability in specific domains such as Model Driven Development, product line systems, and agile project environments. In this paper, we build upon a prior body of work to highlight the state-of-the-art in software traceability, and to present compelling areas of research that need to be addressed.

No abstract

We address the assessment and improvement of the software maintenance function by proposing a maturity model for daily software maintenance activities: the Software Maintenance Maturity Model (SMmm). The software maintenance function suffers from a scarcity of management models to facilitate its evaluation, management, and continuous improvement. The SMmm addresses the unique activities of software maintenance while preserving a structure similar to that of the Capability Maturity Model integration (CMMi). It is designed to be used as a complement to that model. The SMmm is based on practitioners' experience, international standards, and the seminal literature on software maintenance. We present the model's purpose, scope, foundation, and architecture, followed by its initial validation. Copyright © 2005 John Wiley & Sons, Ltd.

Abstract-Assisted requirements tracing is a process in which a human analyst validates candidate traces produced by an automated requirements tracing method or tool. The assisted requirements tracing process splits the difference between the commonly applied time-consuming, tedious, and error-prone manual tracing and the automated requirements tracing procedures that are a focal point of academic studies. In fact, in software assurance scenarios, assisted requirements tracing is the only way in which tracing can be at least partially automated. In this paper, we present the results of an extensive 12 month study of assisted tracing, conducted using three different tracing processes at two different sites. We describe the information collected about each study participant and their work on the tracing task, and apply statistical analysis to study which factors have the largest effect on the quality of the final trace.