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

Toward Automating Requirements Satisfaction Assessment

This paper introduces the automation of satisfaction assessment: the process of determining the satisfaction mapping of natural language textual requirements to natural language design elements. Satisfaction assessment is useful because it assists in discovering unsatisfied requirements early in the lifecycle when such issues can be corrected with lower cost and impact than later. We define the basic terms and concepts for this process and explore the feasibility of developing baseline methods for its automation. This paper describes the satisfaction assessment approach algorithmically and then evaluates the effectiveness of two proposed information retrieval (IR) methods in two industrial studies - one based on a large dataset including a complete requirements specification and design specification for a NASA science instrument, and one based on a smaller dataset for an open source project management dataset. We found that both approaches have merit, and that the more sophisticated approach outperformed the simpler approach in terms of overall accuracy of the results

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