NDLI: The power of probabilistic thinking

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Program generation for performance

An empirical investigation into the nature of test smells

Predicting semantically linkable knowledge in developer online forums via convolutional neural network

Automatically recommending code reviewers based on their expertise: an empirical comparison

Visualization of combinatorial models and test plans

Local-based active classification of test report to assist crowdsourced testing

Taming Android fragmentation: characterizing and detecting compatibility issues for Android apps

Locus: locating bugs from software changes

StraightTaint: decoupled offline symbolic taint analysis

Radius aware probabilistic testing of deadlocks with guarantees

An empirical evaluation of two user interfaces of an interactive program verifier

Inferring annotations for device drivers from verification histories

On essential configuration complexity: measuring interactions in highly-configurable systems

Symbolic execution of stored procedures in database management systems

Identifying domain elements from textual specifications

Greedy combinatorial test case generation using unsatisfiable cores

Move-optimized source code tree differencing

Bugram: bug detection with n-gram language models

Practical guidelines for change recommendation using association rule mining

Reflection-aware static analysis of Android apps

CORRECT: code reviewer recommendation at GitHub for Vendasta technologies

TeeVML: tool support for semi-automatic integration testing environment emulation

Towards efficient and effective automatic program repair

Changing microsoft's build: revolution or evolution

Evaluating non-adequate test-case reduction

Testing advanced driver assistance systems using multi-objective search and neural networks

Evaluating the evaluations of code recommender systems: a reality check

Finding access control bugs in web applications with CanCheck

Multi-objective test report prioritization using image understanding

Automated model-based Android GUI testing using multi-level GUI comparison criteria

Fine-tuning spectrum based fault localisation with frequent method item sets

IncA: a DSL for the definition of incremental program analyses

LockPeeker: detecting latent locks in Java APIs

Traceability maintenance: factors and guidelines

Array length inference for C library bindings

Precise semantic history slicing through dynamic delta refinement

Conc-iSE: incremental symbolic execution of concurrent software

Continuous detection of design flaws in evolving object-oriented programs using incremental multi-pattern matching

Towards automatically generating descriptive names for unit tests

Migrating cascading style sheets to preprocessors by introducing mixins

Mining input grammars from dynamic taints

Learning a dual-language vector space for domain-specific cross-lingual question retrieval

Relda2: an effective static analysis tool for resource leak detection in Android apps

ProcessPAIR: a tool for automated performance analysis and improvement recommendation in software development

The interactive verification debugger: effective understanding of interactive proof attempts

Automated testing and notification of mobile app privacy leak-cause behaviours

The power of probabilistic thinking

Optimizing customized program coverage

Privacy preserving via interval covering based subclass division and manifold learning based bi-directional obfuscation for effort estimation

Too much automation? the bellwether effect and its implications for transfer learning

SOFIA: an automated security oracle for black-box testing of SQL-injection vulnerabilities

CrowdService: serving the individuals through mobile crowdsourcing and service composition

HybriDroid: static analysis framework for Android hybrid applications

Recommending relevant classes for bug reports using multi-objective search

What developers want and need from program analysis: an empirical study

Sound static deadlock analysis for C/Pthreads

Usage, costs, and benefits of continuous integration in open-source projects

APEx: automated inference of error specifications for C APIs

Goal-conflict detection based on temporal satisfiability checking

Model-based whitebox fuzzing for program binaries

Efficient detection of inconsistencies in a multi-developer engineering environment

Applying combinatorial test data generation to big data applications

Automatic runtime recovery via error handler synthesis

Phrase-based extraction of user opinions in mobile app reviews

An end-user oriented tool suite for development of mobile applications

CVExplorer: identifying candidate developers by mining and exploring their open source contributions

Verifying simulink stateflow model: timed automata approach

Factoring requirement dependencies in software requirement selection using graphs and integer programming

What makes killing a mutant hard

Deep learning code fragments for code clone detection

Automatic microbenchmark generation to prevent dead code elimination and constant folding

Supporting oracle construction via static analysis

QUICKAR: automatic query reformulation for concept location using crowdsourced knowledge

An empirical study on dependence clusters for effort-aware fault-proneness prediction

DistIA: a cost-effective dynamic impact analysis for distributed programs

Static race detection for device drivers: the Goblint approach

DSL-maps: from requirements to design of domain-specific languages

Symbolic execution of complex program driven by machine learning based constraint solving

How good are the specs? a study of the bug-finding effectiveness of existing Java API specifications

Generating test cases to expose concurrency bugs in Android applications

Mining revision histories to detect cross-language clones without intermediates

Model driven design of heterogeneous synchronous embedded systems

Lightweight collection and storage of software repository data with DataRover

GUICat: GUI testing as a service

Statistical analysis of large sets of models

Test case permutation to improve execution time

The IDE as a scriptable information system

Towards bounded model checking using nonlinear programming solver

Automatic test image generation using procedural noise

Battery-aware transformations in mobile applications

MACKE: compositional analysis of low-level vulnerabilities with symbolic execution

Visual contract extractor: a tool for reverse engineering visual contracts using dynamic analysis

An automated collaborative requirements engineering tool for better validation of requirements

Developer targeted analytics: supporting software development decisions with runtime information

BovInspector: automatic inspection and repair of buffer overflow vulnerabilities

SuperMod: tool support for collaborative filtered model-driven software product line engineering

An extensible framework for variable-precision data-flow analyses in MPS

API recommendation system for software development

AnModeler: a tool for generating domain models from textual specifications

SimilarTech: automatically recommend analogical libraries across different programming languages

The power of probabilistic thinking

Content Provider	ACM Digital Library
Author	Rosenblum, David S.
Abstract	Traditionally, software engineering has dealt in absolutes. For instance, we talk about a system being "correct" or "incorrect", with the shades of grey in between occasionally acknowledged but rarely dealt with explicitly. And we typically employ logical, algebraic, relational and other representations and techniques that help us reason about software in such absolute terms. There of course have been notable exceptions to this, such as the use of statistical techniques in testing and debugging. But by and large, both researchers and practitioners have favored the relative comfort of an absolutist viewpoint in all aspects of development. In this talk, I will argue the benefits of taking a more thoroughly probabilistic approach in software engineering. Software engineering is rife with stochastic phenomena, and the vast majority of software systems operate in an environment of uncertain, random behavior, which suits an explicit probabilistic characterization. Furthermore, this uncertainty is becoming ever more pronounced in new software systems and platforms, such as the Internet of Things and autonomous vehicles, with their frequent imprecise outputs and heavy reliance on machine learning. To illustrate more deeply some of the considerations involved in taking a probabilistic approach, I will talk about some recent research I have been doing in probabilistic verification. .
Starting Page	3
Ending Page	3
Page Count	1
File Format	PDF
ISBN	9781450338455
DOI	10.1145/2970276.2985780
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-08-25
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Stochastic behavior Probabilistic reasoning Software engineering
Content Type	Text
Resource Type	Article

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