Assessing Comment Quality in Object-Oriented Languages

Previous studies have shown that high-quality code comments support developers in software maintenance and program comprehension tasks. However, the semi-structured nature of comments, several conventions to write comments, and the lack of quality assessment tools for all aspects of comments make comment evaluation and maintenance a non-trivial problem. To understand the specification of high-quality comments to build effective assessment tools, our thesis emphasizes acquiring a multi-perspective view of the comments, which can be approached by analyzing (1) the academic support for comment quality assessment, (2) developer commenting practices across languages, and (3) developer concerns about comments. Our findings regarding the academic support for assessing comment quality showed that researchers primarily focus on Java in the last decade even though the trend of using polyglot environments in software projects is increasing. Similarly, the trend of analyzing specific types of code comments (method comments, or inline comments) is increasing, but the studies rarely analyze class comments. We found 21 quality attributes that researchers consider to assess comment quality, and manual assessment is still the most commonly used technique to assess various quality attributes. Our analysis of developer commenting practices showed that developers embed a mixed level of details in class comments, ranging from high-level class overviews to low-level implementation details across programming languages. They follow style guidelines regarding what information to write in class comments but violate the structure and syntax guidelines. They primarily face problems locating relevant guidelines to write consistent and informative comments, verifying the adherence of their comments to the guidelines, and evaluating the overall state of comment quality. To help researchers and developers in building comment quality assessment tools, we contribute: (i) a systematic literature review (SLR) of ten years (2010–2020) of research on assessing comment quality, (ii) a taxonomy of quality attributes used to assess comment quality, (iii) an empirically validated taxonomy of class comment information types from three programming languages, (iv) a multi-programming-language approach to automatically identify the comment information types, (v) an empirically validated taxonomy of comment convention-related questions and recommendation from various Q&A forums, and (vi) a tool to gather discussions from multiple developer sources, such as Stack Overflow, and mailing lists. Our contributions provide various kinds of empirical evidence of the developer’s interest in reducing efforts in the software documentation process, of the limited support developers get in automatically assessing comment quality, and of the challenges they face in writing high-quality comments. This work lays the foundation for future effective comment quality assessment tools and techniques

Assessing Comment Quality in Object-Oriented Languages

Previous studies have shown that high-quality code comments support developers in software maintenance and program comprehension tasks. However, the semi-structured nature of comments, several conventions to write comments, and the lack of quality assessment tools for all aspects of comments make comment evaluation and maintenance a non-trivial problem. To understand the specification of high-quality comments to build effective assessment tools, our thesis emphasizes acquiring a multi-perspective view of the comments, which can be approached by analyzing (1) the academic support for comment quality assessment, (2) developer commenting practices across languages, and (3) developer concerns about comments. Our findings regarding the academic support for assessing comment quality showed that researchers primarily focus on Java in the last decade even though the trend of using polyglot environments in software projects is increasing. Similarly, the trend of analyzing specific types of code comments (method comments, or inline comments) is increasing, but the studies rarely analyze class comments. We found 21 quality attributes that researchers consider to assess comment quality, and manual assessment is still the most commonly used technique to assess various quality attributes. Our analysis of developer commenting practices showed that developers embed a mixed level of details in class comments, ranging from high-level class overviews to low-level implementation details across programming languages. They follow style guidelines regarding what information to write in class comments but violate the structure and syntax guidelines. They primarily face problems locating relevant guidelines to write consistent and informative comments, verifying the adherence of their comments to the guidelines, and evaluating the overall state of comment quality. To help researchers and developers in building comment quality assessment tools, we contribute: (i) a systematic literature review (SLR) of ten years (2010–2020) of research on assessing comment quality, (ii) a taxonomy of quality attributes used to assess comment quality, (iii) an empirically validated taxonomy of class comment information types from three programming languages, (iv) a multi-programming-language approach to automatically identify the comment information types, (v) an empirically validated taxonomy of comment convention-related questions and recommendation from various Q&A forums, and (vi) a tool to gather discussions from multiple developer sources, such as Stack Overflow, and mailing lists. Our contributions provide various kinds of empirical evidence of the developer’s interest in reducing efforts in the software documentation process, of the limited support developers get in automatically assessing comment quality, and of the challenges they face in writing high-quality comments. This work lays the foundation for future effective comment quality assessment tools and techniques

On Using UML Diagrams to Identify and Assess Software Design Smells

Deficiencies in software design or architecture can severely impede and slow down the software development and maintenance progress. Bad smells and anti-patterns can be an indicator for poor software design and suggest for refactoring the affected source code fragment. In recent years, multiple techniques and tools have been proposed to assist software engineers in identifying smells and guiding them through corresponding refactoring steps. However, these detection tools only cover a modest amount of smells so far and also tend to produce false positives which represent conscious constructs with symptoms similar or identical to actual bad smells (e.g., design patterns). These and other issues in the detection process demand for a code or design review in order to identify (missed) design smells and/or re-assess detected smell candidates. UML diagrams are the quasi-standard for documenting software design and are often available in software projects. In this position paper, we investigate whether (and to what extent) UML diagrams can be used for identifying and assessing design smells. Based on a description of difficulties in the smell detection process, we discuss the importance of design reviews. We then investigate to what extent design documentation in terms of UML2 diagrams allows for representing and identifying software design smells. In particular, 14 kinds of design smells and their representability in UML class and sequence diagrams are analyzed. In addition, we discuss further challenges for UML-based identification and assessment of bad smells

Self and peer assessment: A necessary ingredient in developing and tracking students' graduate attributes

Recently there has been a shift to focus on assessing students' learning outcomes in terms of graduate attributes which they should develop and demonstrate during the course of their degree. A number of universities have tried to address these issues for example by using software tools such as ReView to track attribute development or by producing both academic and professional skill development transcripts. However, many attributes such as teamwork and the ability to give and receive feedback are typically practised in collaborative peer exercises. Furthermore these exercises are often conducted outside of regular class sessions, hence thorough assessment of these attributes should include input from both individual students and their peers. Hence we propose that any method of developing and tracking student's graduate attributes should include self and peer assessment. © 2009 Keith Willey & Anne Gardner

Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

<p>Abstract</p> <p>Background</p> <p>In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior.</p> <p>Results</p> <p>We introduce <it>PathwayOracle</it>, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates <it>PathwayOracle </it>from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, <it>PathwayOracle </it>includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model.</p> <p>Conclusion</p> <p><it>PathwayOracle </it>provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models. The application has been developed in Python and is designed to be easily extensible by groups interested in adding new or extending existing features. <it>PathwayOracle </it>is freely available for download and use.</p

DESIGNING A WEBSITE FOR A RECRUITMENT AGENCY WITH PMBOK METHODOLOGY

Project management refers to a set of activities that contribute to to achieve a successful project: defining the objectives, establishing the team, planning the tasks and providing the resources and deadlines for completing them, continuous assessing the performance and making adjustments when is necessary. The case study used the PMBOK methodology and software tools to design a website for a recruitment agency. The project was accomplished by a group of master students guided by a teacher, at Software for Project Management class. As future work, the authors of this paper aim to continue this experience by enlarging the research study to other projects and by using different project management methodologies

Software Measurement Activities in Small and Medium Enterprises: an Empirical Assessment

An empirical study for evaluating the proper implementation of measurement/metric programs in software companies in one area of Turkey is presented. The research questions are discussed and validated with the help of senior software managers (more than 15 years’ experience) and then used for interviewing a variety of medium and small scale software companies in Ankara. Observations show that there is a common reluctance/lack of interest in utilizing measurements/metrics despite the fact that they are well known in the industry. A side product of this research is that internationally recognized standards such as ISO and CMMI are pursued if they are a part of project/job requirements; without these requirements, introducing those standards to the companies remains as a long-term target to increase quality