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Despite the positive effects of reuse claimed in a significant amount of research, anecdotal evidence indicates that industry is not yet experiencing the expected benefit. This dissertation proposal aims to investigate these indicators and therefore addresses reuse from an industrial point of view. As a first step, it empirically assesses the general state of reuse in practice. This is achieved via a large-scale online questionnaire distributed to multiple companies. Complementing the questionnaire, extensive interviews are being scheduled with developers and project managers of the respective companies. The goal is to interview approximately 10 employees per company. Three companies have already committed to the interview phase and contact with seven further companies is currently being established. In a second step, the findings of the study will be used to extract the context and type of reuse, as well as success factors and hindrances. This information forms the basis for an analytical assessment model for internal code reuse, which is developed in a third step. It will capture a range of different aspects of reuse in practice and will be combined with a process to evaluate the adequacy of reuse. The planned result is a larger assessment framework for evaluating the reuse (management) process within a project as well as a multi-project context. As a result, guidelines for code organization should be developed and tested for their effects in improving reuse in one or more of the industrial partners projects. [ABSTRACT FROM PUBLISHER]

Reuse recommendation systems support the developer by suggesting useful API methods, classes or code snippets based on code edited in the IDE. Existing systems based on structural information, such as type and method usage, are not effective in case of general purpose types such as String. To alleviate this, we propose a recommendation system based on identifiers that utilizes the developer's intention embodied in names of variables, types and methods. We investigate the impact of several variation points of our recommendation algorithm and evaluate the approach for recommending methods from the Java and Eclipse APIs in 9 open source systems. Furthermore, we compare our recommendations to those of a structure-based recommendation system and describe a metric for predicting the expected precision of a recommendation. Our findings indicate that our approach performs significantly better than the structure-based approach. [ABSTRACT FROM PUBLISHER]

Reuse of third-party libraries promises significant productivity improvements in software development. However, dependencies on external libraries and their APIs also introduce risks to a project and impact strategic decisions during development and maintenance. Informed decision making therefore requires a thorough understanding of the extent and nature of dependencies on external APIs. As realistically sized applications are often heavily entangled with various external APIs, gaining this understanding is infeasible with manual inspections only. To address this, we present an automated approach to analyze the dependencies of software projects on external APIs. The approach is supported by a static analysis tool featuring a visualization of the analysis results. We evaluate the approach as well as the tooling on multiple open source Java systems. [ABSTRACT FROM PUBLISHER]

Organizational structures (e. g., separate accounting, heterogeneous infrastructure, or different development processes) can restrict systematic reuse among projects within companies. As a consequence, code is often copied between projects which increases maintenance costs and can cause failures due to inconsistent bug fixing. Assessing cross-project clones helps to uncover organizational obstacles for code reuse and to leverage other ways of systematic reuse. Furthermore, knowing how strongly clones are entangled with the surrounding code helps to decide if and how to extract them to commonly used libraries. We propose to combine cross-project clone detection and dependency analyses to detect (1) what is cloned between projects, (2) how far the cloned code is entangled with the surrounding system and (3) what are candidates for extraction into common libraries. [ABSTRACT FROM PUBLISHER]

Clone detection results are often voluminous and difficult to present. Most clone presentations focus on the quantitative clone results but do not relate them to the structure of the analyzed system. This makes it difficult to interpret the results and draw conclusions. We suggest using edge bundle views to interrelate the system's structure with the clone detection results. Using this technique, it is easier to interpret the clone results and direct further analysis effort. [ABSTRACT FROM PUBLISHER]