A Recommender Agent for Software Libraries: An Evaluation of Memory-Based and Model-Based Collaborative Filtering

Abstract—Software Agents can conveniently facilitate knowl-edge discovery and knowledge sharing across an organisation. We contend that programming tasks are often mimicked, that knowledge concerning reusable libraries can be extracted auto-matically from source code repositories, and that this knowledge can then be filtered and presented to a developer in a manner that will encourage and support future software reuse. We introduce RASCAL, a recommender agent that continually recommends a set of task relevant library methods to a developer. RASCAL learns information regarding how a particular reusable library is used and then employs this insight to make task relevant recommendations to a developer. In this paper we detail our RASCAL agent and describe two recommendation techniques; namely Model-Based and Memory-Based Collabora-tive Filtering. We are interested in producing a scalable and efficient realtime recommender and thus ideally would favor a Model-Based approach. However, each scheme is evaluated against both runtime performance and recommendation accu-racy. We present results and discuss the merits and limitations of each technique. I

SERVICE-BASED AUTOMATION OF SOFTWARE CONSTRUCTION ACTIVITIES

The reuse of software units, such as classes, components and services require professional knowledge to be performed. Today a multiplicity of different software unit technologies, supporting tools, and related activities used in reuse processes exist. Each of these relevant reuse elements may also include a high number of variations and may differ in the level and quality of necessary reuse knowledge. In such an environment of increasing variations and, therefore, an increasing need for knowledge, software engineers must obtain such knowledge to be able to perform software unit reuse activities. Today many different reuse activities exist for a software unit. Some typical knowledge intensive activities are: transformation, integration, and deployment. In addition to the problem of the amount of knowledge required for such activities, other difficulties also exist. The global industrial environment makes it challenging to identify sources of, and access to, knowledge. Typically, such sources (e.g., repositories) are made to search and retrieve information about software unitsand not about the required reuse activity knowledge for a special unit. Additionally, the knowledge has to be learned by inexperienced software engineers and, therefore, to be interpreted. This interpretation may lead to variations in the reuse result and can differ from the estimated result of the knowledge creator. This makes it difficult to exchange knowledge between software engineers or global teams. Additionally, the reuse results of reuse activities have to be repeatable and sustainable. In such a scenario, the knowledge about software reuse activities has to be exchanged without the above mentioned problems by an inexperienced software engineer. The literature shows a lack of techniques to store and subsequently distribute relevant reuse activity knowledge among software engineers. The central aim of this thesis is to enable inexperienced software engineers to use knowledge required to perform reuse activities without experiencing the aforementioned problems. The reuse activities: transformation, integration, and deployment, have been selected as the foundation for the research. Based on the construction level of handling a software unit, these activities are called Software Construction Activities (SCAcs) throughout the research. To achieve the aim, specialised software construction activity models have been created and combined with an abstract software unit model. As a result, different SCAc knowledge is described and combined with different software unit artefacts needed by the SCAcs. Additionally, the management (e.g., the execution of an SCAc) will be provided in a service-oriented environment. Because of the focus on reuse activities, an approach which avoids changing the knowledge level of software engineers and the abstraction view on software units and activities, the object of the investigation differs from other approaches which aim to solve the insufficient reuse activity knowledge problem. The research devised novel abstraction models to describe SCAcs as knowledge models related to the relevant information of software units. The models and the focused environment have been created using standard technologies. As a result, these were realised easily in a real world environment. Softwareengineers were able to perform single SCAcs without having previously acquired the necessary knowledge. The risk of failing reuse decreases because single activities can be performed. The analysis of the research results is based on a case study. An example of a reuse environmenthas been created and tested in a case study to prove the operational capability of the approach. The main result of the research is a proven concept enabling inexperienced software engineers to reuse software units by reusing SCAcs. The research shows the reduction in time for reuse and a decrease of learning effort is significant

Semantic Component Retrieval in Software Engineering

In the early days of programming the concept of subroutines, and through this software reuse, was invented to spare limited hardware resources. Since then software systems have become increasingly complex and developing them would not have been possible without reusable software elements such as standard libraries and frameworks. Furthermore, other approaches commonly subsumed under the umbrella of software reuse such as product lines and design patterns have become very successful in recent years. However, there are still no software component markets available that would make buying software components as simple as buying parts in a do-it-yourself hardware store and millions of software fragments are still lying un(re)used in configuration management repositories all over the world. The literature primarily blames this on the immense effort required so far to set up and maintain searchable component repositories and the weak mechanisms available for retrieving components from them, resulting in a severe usability problem. In order to address these issues within this thesis, we developed a proactive component reuse recommendation system, naturally integrated into test-first development approaches, which is able to propose semantically appropriate, reusable components according to the specification a developer is just working on. We have implemented an appropriate system as a plugin for the well-known Eclipse IDE and demonstrated its usefulness by carrying out a case study from a popular agile development book. Furthermore, we present a precision analysis for our approach and examples of how components can be retrieved based on a simplified semantics description in terms of standard test cases

IOS Press Knowledge Reuse for Software Reuse

Abstract. Software reuse can provide significant improvements in software productivity and quality whilst reducing development costs. Expressing software reuse intentions can be difficult though. A developer may aspire to reuse a software component but experience difficulty expressing their reuse intentions in a manner that is compatible with, or understood by, the component retrieval system. Various intelligent retrieval techniques have been developed that assist a developer in locating or discovering components in an efficient manner. These solutions share a common shortcoming: the developer must be capable of anticipating all reuse opportunities and initiating the retrieval process. There is a need for a comprehensive technique that not only assists with retrievals but that can also identify reuse opportunities. This paper advocates that component-based reuse can be supported through knowledge collaboration. Often programming tasks and solutions are replicated; this characteristic of software can be exploited for the benefit of future developments. Through the mining of existing source code solutions, knowledge, relating to how components are used by developers, can be extracted. Based on a developer’s current programming task, this knowledge can subsequently be filtered and used to recommend a candidate set of reusable components. This novel recommendation approach applies and extends commonly used Information Retrieval and Information Filtering techniques such as Collaborative Filtering, Content-Based Filtering, and Bayesian Clustering Models, to the software reuse domain. This recommendation technology is applied to several thousand open-source Java classes. The most effective recommendation algorithm produces recommendations of a high quality at a low cost