Supplementary Material - Large-Scale Study of Effect Substitutability

  1. Introduction
  2. Analyses and Output Details
  3. Implementation and Results
    1. Exception
    2. Synchronization
    3. I/O
    4. Method Call
    5. Combined Effect Analysis

Introduction

This page provides supplementary material for our effect substitutability study. We used the Boa infrastructure, and specifically their September 2015 GitHub dataset to complete this study. Here we provide access to our analyses implementations coupled with the raw results and an explanation of the output files.

Analyses and Output Details

Each of the analyses were written in the Boa domain-specific language, and links to the implementations and raw outputs are given in the next section. Here we will discuss what one can expect to find in the outputs.

In the outputs, each line has the form “x[y] = z” where x is the output type’s name, y is the key, and z is the value. There are two output types that are the most important. The first is lines with the format “stat[key] = # occurrences”, which provides statistical information such as the number of source files examined or the number of private methods that do not throw exceptions. The second has the format “out[] = value”, which is used by the exception, synchronization, and I/O analyses to output information on each method pair with that effect type. The value is a #-delimited list with the following format:

  1. GitHub repository name
  2. Method name for the method pair
  3. Subclass name
  4. Supermethod effect
  5. Submethod effect
  6. Category of effect difference between the two methods
  7. Further information dependent on the analysis

In general, the categories begin with an exclamation and compare the sub and supermethod effects, stating which method has “more” effects than the other. For example, a category of !n is used to state the effects of both methods in a pair are the same and !y is used to state the “size” of the effects are the same, but the effect itself is different.

Implementation and Results

There are 5 Boa analyses, 4 for each of the side-effect types: exception, synchronization, I/O, and method call. The last analysis combines each of the previous analyses into one and provides aggregate information. For each analysis, a link is provided to the Boa job, whose page allows one to download both the implementation and the raw output. Note that each of these jobs were ran on the full September 2015 GitHub dataset.

Exception

Boa job: Exception Effect Analysis

The methods effects are the set of exception types thrown in the format of a comma delimited list. The last item is the set of exception types that the supermethod declare it may throw in the method signature. An exception of type !UNKNOWN! indicates that the type could not be decided by the analysis. The category is a set-based comparison of the effects of the sub and supermethods.

Synchronization

Boa job: Synchronization Effect Analysis

Method effects are the way synchronization is used: none (!NONE), only acquiring a lock (!ACQUIRE), only releasing (!RELEASE), or both (!BOTH). The last entry denotes the most fine-grained synchronization used in either of the methods. So if one method uses locks it would be !hasLock, if blocks then !hasBlock, and if only the synchronized modifier is used then !hasModifier.

I/O

Boa job: I/O Effect Analysis

Method effects are type of I/O identified: none (NONE), output only (OUT), input only (IN), and both (BOTH). Last entry denotes the type of I/O classes used: !CONSOLE if any console-related objects were used, !FILE if file objects are used but no console ones, otherwise !BUS.

Method Call

Boa job: Method Call Effect Analysis

Due to the number of methods and method calls in the dataset, we only output statistics here.

Combined Effect Analysis

Boa job: All Effects Combined Analysis

This output mainly provides statistics regarding the kinds of side-effects used by all methods and by all method pairs where the submethod has more of an effect. The method pair outputs that are shown are a small subset of pairs with effects as decided by a random number generator.