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.

AbstractÐWhile empirical studies in software engineering are beginning to gain recognition in the research community, this subarea is also entering a new level of maturity by beginning to address the human aspects of software development. This added focus has added a new layer of complexity to an already challenging area of research. Along with new research questions, new research methods are needed to study nontechnical aspects of software engineering. In many other disciplines, qualitative research methods have been developed and are commonly used to handle the complexity of issues involving human behavior. This paper presents several qualitative methods for data collection and analysis and describes them in terms of how they might be incorporated into empirical studies of software engineering, in particular how they might be combined with quantitative methods. To illustrate this use of qualitative methods, examples from real software engineering studies are used throughout.

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Reverse engineering software systems has become a major concern in software industry because of their sheer size and complexity. This problem needs to be tackled, since the systems in question are of considerable worth to their owners and maintainers. In this article we present the concept of a polymetric view, a lightweight software visualization technique enriched with software metrics information. Polymetric views help to understand the structure and detect problems of a software system in the initial phases of a reverse engineering process. We discuss the benefits and limits of several predefined polymetric views we have implemented in our tool CodeCrawler. Moreover, based on clusters of different polymetric views we have developed a methodology which supports and guides a software engineer in the first phases of a reverse engineering of a large software system. We have refined this methodology by repeatedly applying it on industrial systems, and illustrate it by applying a selection of polymetric views to a case study.

Abstract—Understanding source code is an important task in the maintenance of software systems. Legacy systems are not only limited to procedural languages, but are also written in object-oriented languages. In such a context, understanding classes is a key activity as they are the cornerstone of the object-oriented paradigm and the primary abstraction from which applications are built. Such an understanding is however difficult to obtain because of reasons such as the presence of late binding and inheritance. A first level of class understanding consists of the understanding of its overall structure, the control flow among its methods, and the accesses on its attributes. We propose a novel visualization of classes called class blueprint that is based on a semantically enriched visualization of the internal structure of classes. This visualization allows a software engineer to build a first mental model of a class that he validates via opportunistic code-reading. Furthermore, we have identified visual patterns that represent recurrent situations and as such convey additional information to the viewer. The contributions of this article are the class blueprint, a novel visualization of the internal structure of classes, the identification of visual patterns, and the definition of a vocabulary based on these visual patterns. We have performed several case studies of which one is presented in depth, and validated the usefulness of the approach in a controlled experiment. Index Terms—Object-oriented programming, software visualization, reverse engineering, visual patterns, smalltalk. 1

The maintenance, reengineering, and evolution of object-oriented software systems has become a vital matter in today’s software industry. Although most systems start off in a clean and well-designed state, with time they tend to gradually decay in quality, unless the systems are reengineered and adapted to the evolving requirements. However, before such legacy software systems can be reengineered and evolved, they must be reverse engineered, i.e., their structure and inner working must be understood. This is difficult because of several factors, such as the sheer size of the systems, their complexity, their domain specificity, and in general the bad state legacy software systems are in. In this thesis we propose a visual approach to the reverse engineering of object-oriented software systems by means of polymetric views, lightweight visualizations of software enriched with metrics and other types of semantic information about the software, e.g., its age, version, abstractness, location, structure, function, etc. We present and discuss several polymetric views which allow us to understand three different aspects of object-oriented software, namely 1. coarse-grained aspects which allow for the understanding of very large systems.

To effectively perform a change to an existing software system, a software engineer needs to have some understanding of the structure of the system. All too often, though, an engineer must proceed to change a system without sufficient structural information because existing software understanding techniques are unable to help the engineer acquire the desired knowledge within the time and cost constraints specified for the task. The thesis of this research is that an approach based on summarization can overcome the limitations associated with existing approaches, enabling an engineer to assess, plan, and execute changes to a software system more effectively. Summarization involves the production of overviews of vast amounts of user-selected information in a timely manner. I describe two tech...

maintenance of large-scale software

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 an approach to establish and maintain traceability links between the source code and free text documents. A premise of our work is that programmers use meaningful names for program's 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. In this paper, the approach is applied to software written in an object-oriented language, namely C++, to trace classes to manual sections. Keywords: traceability, versions compliance check, object orientation 1.

This paper reports on a software understanding experiment during corrective maintenance of large- scale software. Participants were professional software maintenance engineers. The paper reports on the general understanding process, the types of actions programmers preferred during the debugging task, and the level of abstraction at which they were working. The results of the observation are also interpreted in terms of the information needs of these software engineers during the debugging task. 1.