Michalis Famelis

University of Toronto | U of T · Department of Computer Science

Code commit messages can contain useful information on why a developer has made a change. However, the presence and structure of rationale in real-world code commit messages is not well studied. Here, we detail the creation of a labelled dataset to analyze the code commit messages of the Linux Kernel Out-Of-Memory Killer component. We study aspects...

Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents to software engineering researchers the six key challenges that a domain expert faces in addressing their problem with a computational workflow, and the underlying executable implementation. These challenges arise out of our con...

Extracting rationale information from commit messages allows developers to better understand a system and its past development. Here we present our ongoing work on the Kantara end-to-end rationale reconstruction pipeline to a) structure rationale information in an ontologically-based knowledge graph, b) extract and classify this information from co...

The logic behind design decisions, called design rationale, is very valuable. In the past, researchers have tried to automatically extract and exploit this information, but prior techniques are only applicable to specific contexts and there is insufficient progress on an end-to-end rationale information extraction pipeline. Here we outline a path t...

Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents six key challenges that a domain expert faces in transforming their problem into a computational workflow, and then into an executable implementation. These challenges arise out of our conceptual framework which presents the "ro...

A typical approach to programming is to first code the main execution scenario, and then focus on filling out alternative behaviors and corner cases. But, almost always, there exist unusual conditions that trigger atypical behaviors, which are hard to predict in program specifications, and are thus often not coded. In this paper, we consider the pr...

Code recommendation aims to help programmers in their coding endeavors by suggesting appropriate code snippets to complete their program. Code recommendation approaches such as code search or code repair may rely on code snippets or code templates extracted from existing projects to provide these suggestions. In this context, extracting and charact...

Uncertainty is present in model-based developments in many different ways. In the context of composing model-based analysis tools, this chapter discusses how the combination of different models can increase or decrease the overall uncertainty. It explores how such uncertainty could be more explicitly addressed and systematically managed, with the g...

Refactoring does not always improve monotonically the quality of software. In this exploratory study, we analyze the revision history of JFreechart to see if fluctuations in internal quality metrics in commits containing refactoring can be used as indicators for the presence of design tradeoffs. We present qualitative and quantitative results sugge...

Although Model-Based Software Engineering (MBE) is a widely accepted Software Engineering (SE) discipline, no agreed-upon core set of concepts and practices (i.e., a Body of Knowledge) has been defined for it yet. With the goals of characterizing the contents of the MBE discipline, promoting a global consistent view of it, clarifying its scope with...

A software system's design determines many of its properties, such as maintainability and performance. An understanding of design is needed to maintain system properties as changes to the system occur. Unfortunately, many systems do not have up-to-date design documentation and approaches that have been developed to recover design often focus on how...

Managing design-time uncertainty, i.e., uncertainty that developers have about making design decisions, requires creation of “uncertainty-aware” software engineering methodologies. In this paper, we propose a methodological approach for managing uncertainty using partial models. To this end, we identify the stages in the lifecycle of uncertainty-re...

Understanding the experiences of instructors teaching modelling and model-driven engineering is of great relevance to determining how MDE courses should be managed in terms of content, assessment, and teaching methods. In this paper, we report the results of a survey of 47 instructors in this field. Questions address course content, tools and techn...

Model-based Software Engineering (MBSE) is now accepted as a Software Engineering (SE) discipline and is being taught as part of more general SE curricula. However, an agreed core of concepts, mechanisms and practices --- which constitutes the Body of Knowledge of a discipline --- has not been captured anywhere, and is only partially covered by the...

When contributing code to a software system, developers are often confronted with the hard task of understanding and adhering to the system's design. This task is often made more difficult by the lack of explicit design information. Often, recorded design information occurs only embedded in discussions between developers. If this design information...

As a software system is iteratively developed, software developers engage in many discussions, often through written forms. Some of these discussions occur on pull requests and include information about the design of the system to which the code in the pull request is being contributed. Although previous work has shown that design is discussed in f...

Model Transformations have been called the “heart and soul” of Model-Driven software development. However, they take a lot of effort to build, verify, analyze, and debug. It is thus imperative to develop good reuse strategies that address issues specific to model transformations. Some of the effective reuse strategies are adopted from other domains...

Software Product Lines (SPL) are widely used to manage variability in the automotive industry. In a rapidly changing industrial environment, model transformations are necessary to aid in automating the evolution of SPLs. However, existing transformation technologies are not well-suited to handling industrial-grade variability in software artifacts....

Models are typically used for expressing information that is known at a particular stage in the software development process. Yet, it is also important to express what information a modeler is still uncertain about and to ensure that model refinements actually reduce this uncertainty. Furthermore, when a refining transformation is applied to a mode...

Software development is a social process: tasks such as implementing a requirement or fixing a bug typically spark conversations between the stakeholders of a software project, where they identify points of uncertainty in the solution space and explore proposals to resolve them. Due to the fluid nature of these interactions, it is hard for project...

Software product lines and model transformations are two techniques used in industry for managing the development of highly complex software. Product line approaches simplify the handling of software variants while model transformations automate software manipulations such as refactoring, optimization, code generation, etc. While these techniques a...

Model transformation techniques typically operate under the assumption that models do not contain uncertainty. In the presence of uncertainty, this forces modelers to either postpone working or to artificially remove it, with negative impacts on software cost and quality. Instead, we propose a technique to adapt existing model transformations so th...

We apply the “Physics of Notations” theory to design MAV-Vis, a concrete syntax for partial models, i.e., models where design uncertainty is explicitly captured. To validate our implementation of this theory in creating MAV-Vis, we designed and executed an empirical user study comparing the cognitive effectiveness of MAV-Vis with the existing, ad-h...

Uncertainty is pervasive in Model-based Software Engineering. In previous work, we have proposed partial models as a way to explicate uncertainty during modeling. Using partial models, modelers can perform certain forms of reasoning, like checking properties, without the having to prematurely resolve uncertainty. In this paper, we present a strateg...

Model transformations are traditionally designed to operate on models that do not contain uncertainty. In previous work, we have developed partial models, i.e., models that explicitly capture uncertainty. In this paper, we study the transformation of partial models. We define the notion of correct lifting of transformations so that they can be appl...

Models are good at expressing information about software but not as good at expressing modelers' uncertainty about it. The highly incremental and iterative nature of software development nonetheless requires the ability to express uncertainty and reason with models containing it. In this paper, we build on our earlier work on expressing uncertainty...

Software development in application domains where model-based techniques are employed faces challenges related to managing sets of inter-dependent models of various types. In such settings, capturing the semantic structure of sets of models, as well as being able to check the validity of relationships between models that constitute this structure,...

Models express not only information about their intended domain but also about the way in which the model is incomplete, or "partial". This partiality supports the modeling process because it permits the expression of what is known without premature decisions about what is still unknown, until later refinements can fill in this information. A key o...

Model-based software development inevitably involves dealing with incomplete information. Yet, MDE methodologies rarely, if ever, address uncertainty in a systematic way. Drawing inspiration from the field of behavioural modeling [6, 4], we propose to use partial models as first-class development artifacts to abstract, reason with, visualize and ma...