Senthil Karthikeyan Sundaram

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.

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.

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.

Baselines in requirements tracing

We summarize the results of our requirements tracing work to date, focusing on our empirical results with open source datasets. Specifically, we describe the problem of after-the-fact requirements tracing for Verification and Validation (V&V) analysts, we provide a brief overview of Information Retrieval methods we have applied as well as measures used to evaluate them, we describe our tracing tool, and we present the results of a number of empirical studies. Two of the open source datasets that we have used are available to the research community at <u>http://promise.site.uottawa.ca/SERepository/.</u>

Technique Integration for Requirements Assessment

In determining whether to permit a safety-critical software system to be certified and in performing independent verification and validation (IV&V) of safety- or mission-critical systems, the requirements traceability matrix (RTM) delivered by the developer must be assessed for accuracy. The current state of the practice is to perform this work manually, or with the help of general-purpose tools such as word processors and spreadsheets Such work is error-prone and person-power intensive. In this paper, we extend our prior work in application of Information Retrieval (IR) methods for candidate link generation to the problem of RTM accuracy assessment. We build voting committees from five IR methods, and use a variety of voting schemes to accept or reject links from given candidate RTMs. We report on the results of two experiments. In the first experiment, we used 25 candidate RTMs built by human analysts for a small tracing task involving a portion of a NASA scientific instrument specification. In the second experiment, we randomly seeded faults in the RTM for the entire specification. Results of the experiments are presented.

Will Johnny/Joanie Make a Good Software Engineer? Are Course Grades Showing the Whole Picture?

Predicting future success of students as software engineers is an open research area. We posit that current grading means do not capture all the information that may predict whether students will become good software engineers. We use one such piece of information, traceability of project artifacts, to illustrate our argument. Traceability has been shown to be an indicator of software project quality in industry. We present the results of a case study of a University of Waterloo graduate-level software engineering course where traceability was examined as well as course grades (such as mid-term, project grade, etc.). We found no correlation between the presence of good traceability and any of the course grades, lending support to our argument