Jane Huffman Hayes

Advancing candidate link generation for requirements tracing: the study of methods

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 RETROs support of goals and goal elements that can be measured objectively.

Improving requirements tracing via information retrieval

We present 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.

Software traceability: trends and future directions

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.

Software Maintenance Maturity Model (SMmm): the software maintenance process model

SUMMARY We address the assessment and improvement of the software maintenance function by proposing improvements to the software maintenance standards and introducing a proposed maturity model for daily software maintenance activities: Software Maintenance Maturity Model (SM mm ). The software maintenance function suffers from a scarcity of management models to facilitate its evaluation, management, and continuous improvement. The SM mm addresses the unique activities of software maintenance while preserving a structure similar to that of the CMMi ©4 maturity model. It is designed to be used as a complement to this model. The SM mm 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

Helping analysts trace requirements: an objective look

This work addresses the issues related to improving the overall quality of the requirements tracing process for independent verification and validation analysts. The contribution of the paper is three-fold: we define requirements for a tracing tool based on analyst responsibilities in the tracing process; we introduce several measures for validating that the requirements have been satisfied; and we present a prototype tool that we built, RETRO (REquirements TRacing On-target), to address these requirements. We also present the results of a study used to assess RETROs support of requirements and requirement elements that can be measured objectively.

REquirements TRacing On target (RETRO): improving software maintenance through traceability recovery

A number of important tasks in software maintenance require an up-to-date requirements traceability matrix (RTM): change impact analysis, determination of test cases to execute for regression testing, etc. The generation and maintenance of RTMs are tedious and error-prone, and they are hence often not done. In this paper, we present REquirements TRacing On-target (RETRO), a special- purpose requirements tracing tool. We discuss how RETRO automates the generation of RTMs and present the results of a study comparing manual RTM generation to RTM generation using RETRO. The study showed that RETRO found significantly more correct links than manual tracing and took only one third of the time to do so.

Automated Requirements Traceability: The Study of Human Analysts

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. When using RTMs to support the V&V of mission-or safety-critical systems, however, a human analyst must vet the candidate RTMs. The focus thus becomes the quality of the final RTM. This paper investigate show human analysts perform when vetting candidate RTMs. Specifically, a study was undertaken at two universities and had 26 participants analyze RTMs of varying accuracy for a Java code formatter program. The study found that humans tend to move their candidate RTM toward the line that represents recall = precision. Participants who examined RTMs with low recall and low precision drastically improved both.

Evaluating individual contribution toward group software engineering projects

It is widely acknowledged that group or team projects are a staple of undergraduate and graduate software engineering courses. Such projects provide students with experiences that better prepare them for their careers, so teamwork is often required or strongly encouraged by accreditation agencies. While there are a multitude of educational benefits of group projects, they also pose considerable challenge in fairly and accurately discerning individual contribution for evaluation purposes. Issues, approaches, and best practices for evaluating individual contribution are presented from the perspectives of the University of Kentucky, University of Ottawa, University of Southern California, and others. The techniques utilized within a particular course generally are a mix of (1) the group mark is everybodys mark, (2) everybody reports what they personally did, (3) other group members report the relative contributions of other group members, (4) pop quizzes on project details, and (5) cross-validating with the results of individual work.

Humans in the traceability loop: can't live with 'em, can't live without 'em

The human analyst is required as an active participant in the trace-ability process. Work to date has focused on automated methods that generate traceability information. There is a need for study of what the analysts do with traceability information as well as a study of how they make decisions.

Assessing traceability of software engineering artifacts

The generation of traceability links or traceability matrices is vital to many software engineering activities. It is also person-power intensive, time-consuming, error-prone, and lacks tool support. The activities that require traceability information include, but are not limited to, risk analysis, impact analysis, criticality assessment, test coverage analysis, and verification and validation of software systems. Information Retrieval (IR) techniques have been shown to assist with the automated generation of traceability links by reducing the time it takes to generate the traceability mapping. Researchers have applied techniques such as Latent Semantic Indexing (LSI), vector space retrieval, and probabilistic IR and have enjoyed some success. This paper concentrates on examining issues not previously widely studied in the context of traceability: the importance of the vocabulary base used for tracing and the evaluation and assessment of traceability mappings and methods using secondary measures. We examine these areas and perform empirical studies to understand the importance of each to the traceability of software engineering artifacts.