Abstract—Software system documentation is almost always expressed informally in natural language and free text. Examples include requirement specifications, design documents, manual pages, system development journals, error logs, and related maintenance reports. We propose a method based on information retrieval to recover traceability links between source code and free text documents. A premise of our work is that programmers use meaningful names for program items, such as functions, variables, types, classes, and methods. We believe that the application-domain knowledge that programmers process when writing the code is often captured by the mnemonics for identifiers; therefore, the analysis of these mnemonics can help to associate high-level concepts with program concepts and vice-versa. We apply both a probabilistic and a vector space information retrieval model in two case studies to trace C++ source code onto manual pages and Java code to functional requirements. We compare the results of applying the two models, discuss the benefits and limitations, and describe directions for improvements.

An information retrieval technique, latent semantic indexing, is used to automatically identi traceability links from system documentation to program source code. The results of two experiments to identi links in existing software systems (i.e., the LEDA library, and Albergate) are presented. These results are compared with other similar type experimental results of traceability link identification using different types of information retrieval techniques. The method presented proves to give good results by comparison and additionally it is a low cost, highly flexible method to apply with regards to preprocessing and/or parsing of the source code and documentation.

To facilitate software maintenance and evolution, a helpful step is to locate features concerned in a particular maintenance task. In the literature, both dynamic and interactive approaches have been proposed for feature location. In this paper, we present a static and non-interactive method for achieving this objective. The main idea of our approach is to use the information retrieval (IR) technology to reveal the basic connections between features and computational units in source code. Due to the characteristics of the retrieved connections, we use a static representation of the source code named BRCG to further recover both the relevant and the specific computational units for each feature. Furthermore, we recover the relationships among the relevant units for each feature. A premise of our approach is that programmers should use meaningful names as identifiers. We perform an experimental study based on a GNU system to evaluate our approach. In the experimental study, we present the detailed quantitative experimental data and give the qualitative analytical results. 1.

Requirements traceability (RT) aims at defining relationships between stakeholder requirements and artifacts produced during the software development life-cycle. Although techniques for generating and validating RT are available, RT in practice often suffers from the enormous effort and complexity of creating and maintaining traces or from incomplete trace information that cannot assist engineers in real-world problems. In this paper we will present a tool-supported technique easing trace acquisition by generating trace information automatically. We will explain the approach using a video-on-demand system and show that the generated traces can be used in various engineering scenarios to solve RT-related problems.

The paper describes the use of an XML format to store and represent program source code. A new XML application, srcML (SouRCe Markup Language), is presented. srcML presumes a document view of source code where information about the syntactic structure is layered over the original source code document. The resultant multi-layered document has a base layer of all the original text (and formatting). The second layer is the syntactic information, derived from the grammar of the programming language, and is encoded in XML. This multilayered view supports both the creation and viewing of the source code in its original form and the use of XML technologies (for tasks such as analysis and transformation of the source). Although directed at source code documents, (particularly C++) srcML is also applicable to other programming languages and to languages with a strict syntax. srcML represents a departure from the compiler centric manner in which source code is commonly stored, instead a document point of view is taken thus better supporting the manipulation and management of the large numbers of source documents typical in modern software systems.

When a software system evolves, features are added, removed and changed. Moreover, refactoring activities are periodically performed to improve the software internal structure. A class may be replaced by another, two classes can be merged, or a class may be split in two others. As a consequence, it may not be possible to trace software features between a release and another. When studying software evolution, we should be able to trace a class lifetime even when it disappears because it is replaced by a similar one, split or merged. Such a capability is also essential to perform impact analysis. This paper proposes an automatic approach, inspired on vector space information retrieval, to identify class evolution discontinuities and, therefore, cases of possible refactoring. The approach has been applied to identify refactorings performed over 40 releases of a Java open source domain name server. Almost all the refactorings found were actually performed in the analyzed system, thus indicating the helpfulness of the approach and of the developed tool.

A number of techniques for semi-automated traceability link recovery between source code and documentation have recently been proposed to support the reverse engineering and maintenance of legacy systems. This is only the first step in supporting the long term maintainability of such systems. A crucial issue, after recovering traceability links is analyzing their general conformance over time. That is, as a system is changed during evolution the validity and conformance of the links may change. Thus, conformance analysis must be performed to identify possible non-conformance of the links. The paper presents a holistic view of how to combine link recovery with conformance analysis that is facilitated by a formal hypertext model. This hypertext model not only supports complex linking structures (e.g., multi links) but also supports versioning of individual links. Such a model preserves and maintains over time the results of the reverse engineered traceability links. 1

An approach for the semi-automated recovery of traceability links between software documentation and source code is presented. The methodology is based on the application of information retrieval techniques to extract and analyze the semantic information from the source code and associated documentation. A semi-automatic process is defined based on the proposed methodology. The paper advocates the use of latent semantic indexing (LSI) as the supporting information retrieval technique. Two case studies using existing software are presented comparing this approach with others. The case studies show positive results for the proposed approach, especially considering the flexibility of the methods used.

Traceability links provide support for software engineers in understanding the relations and dependencies among software artifacts created during the software development process. In this research, we focus on re-establishing traceability links between existing source code and documentation to support reverse engineering. We present a novel approach that addresses this issue by creating formal ontological representations for both the documentation and source code artifacts. These representations are then aligned to establish traceability links at the semantic level. Our approach recovers traceability links by utilizing the structural and semantic information in various software artifacts and the linked ontologies are also supported by ontology reasoners to infer implicit relations among these software artifacts.

Abstract. Software maintainers routinely have to deal with a multitude of artifacts, like source code or documents, which often end up disconnected, due to their different representations and the size and complexity of legacy systems. One of the main challenges in software maintenance is to establish and maintain the semantic connections among all the different artifacts. In this paper, we show how Semantic Web technologies can deliver a unified representation to explore, query and reason about a multitude of software artifacts. A novel feature is the automatic integration of two important types of software maintenance artifacts, source code and documents, by populating their corresponding sub-ontologies through code analysis and text mining. We demonstrate how the resulting “Software Semantic Web ” can support typical maintenance tasks through ontology queries and Description Logic reasoning, such as security analysis, architectural evolution, and traceability recovery between code and documents.